# PALO Framework > PALO means Principled AI Lifecycle Orchestration. Created and maintained by Fabrizio Degni, it connects AI governance decisions with risk and impact assessment, controls, indicators and reviewable evidence. PALO supports governance and educational assessment; it does not certify compliance. PALO-AI is a developer preview, with production limits documented in its capability and readiness pages. Worked examples use synthetic data unless explicitly stated otherwise. This is a curated index of public resources. Canonical pages remain authoritative. This file grants no permissions and does not change crawler access. The following text is generated from the main content of the selected public HTML pages; navigation and forms are omitted. It is not the entire site archive. --- ## PALO Framework Canonical URL: https://paloframework.org/ Editorial date: 2026-09-25 Open-source AI governance | PALO Framework # AI governance, from principles to evidence. 17 September update: ANS, agent swarms and the evidence boundary Assess AI risks, document fundamental-rights impacts and connect controls to evidence. Start with one use case and build a reviewable dossier using PALO's local-first governance tools. Run the 10-minute evidence case Find my route No account. No mandatory telemetry. Voluntary export only. One framework. Three connected governance routes. ## Choose the governance problem, not the product name. PALO covers the complete AI lifecycle. PALO-AM and PALO-AI deepen the agentic route when delegated authority or runtime enforcement becomes the problem to solve. PALO provides the governance system. PALO-AM defines agentic authority. PALO-AI makes selected controls executable and verifiable. - Umbrella systemPALO Framework - Specialist methodologyPALO-AM - Technical enforcementPALO-AI 01 / PALO Framework ### Govern the AI lifecycle Executive, Governance, Risk, Product owner, Auditor Frame the use case, classify risk, assess impacts, select controls, define measurements and connect evidence to review. OutcomeProportionate route, Case File or evidence bundle, reviewable decision trail Ask PALO for a routeDetailed onboardingExplore guided tools 02 / PALO-AM ### Govern agentic systems Governance, Product, Risk, Assurance, Engineering Define agent identity, delegated authority, autonomy level, oversight, reversibility and the assurance evidence required. PALO-AM is the agentic governance modality inside PALO. Explore PALO-AMRun the simulator 03 / PALO-AI ### Enforce agent actions Developer, Platform engineer, Security, No-code builder Apply policy gates, exact claims, approval, one-time capability, protected execution, trusted receipt and outcome verification. PALO-AI is the technical control-plane component of PALO and remains a Developer Preview. Explore PALO-AIOpen Governance HubChoose a quickstart PALO technical extension. Current v2.7 data-assurance developer preview. ## PALO-AI: from authorized action to verified outcome New: ANS identity integration and verified offline demo Inside the broader PALO Framework, PALO-AI binds agent authority and oversight to current purpose-fit data, a signed disclosure contract, a one-time execution capability and evidence of the information flow and effect actually produced. ProposeAuthorizeApproveExecuteReceiptVerifyIncident / review Governance Hub: eight-step builder - Define purpose - Register the agent - Bound authority - Choose oversight - Define outcome - Connect integration - Test boundary - Publish profile Developer Preview: realistic illustrative/local data; not an authenticated production console or authorization boundary. Why PALO-AI?Open the guided builderChoose a quickstart Guided journeys already available ## Start from an outcome. Leave with an artifact. These are working guided flows, not a flat catalogue. The cognitive start recommends which one matters now. Orient ### PALO Guide Find a transparent route for your role, objective, system and impact. Artifact: Accountable steps and integration classAsk PALO Govern agent actions ### Governance Hub builder Bind purpose, identity, authority, oversight and verified effects in eight steps. Artifact: Governance profile and enforcement summaryOpen the builder Connect evidence ### Assessment Path Route classification, impact, controls and evidence. Artifact: Versioned evidence bundleOpen Assessment Path Bound delegation ### PALO-AM Simulator Test action space, autonomy and reversibility. Artifact: Agentic authority tierOpen PALO-AM Frame ### AI Model Canvas Make purpose, ownership and assumptions explicit. Artifact: AI use-case canvasBuild the canvas Classify ### Risk Tiering Establish an initial EU AI Act risk route. Artifact: Classification rationaleCalculate the tier Assess ### FRIA Assessment Structure fundamental-rights impact questions. Artifact: FRIA assessment recordStart the FRIA Measure ### KPI/KRI Generator Turn governance intent into observable indicators. Artifact: KPI/KRI registerGenerate indicators Control coding agents ### Vibe Coding gate Preview a governance check before every coding-agent tool call. Artifact: Pre-tool decision evidenceOpen the gate preview Understand, apply, review ## Put AI governance into practice ### Build a reviewable evidence record Follow a fictional invoice agent through its authority boundary, expected effects and human review conditions. Read the worked governance case ### Choose indicators that support decisions Define a useful KPI or KRI with a denominator, evidence source, accountable owner and review action. Explore KPI and KRI examples ### Trace the research behind PALO Read the publications, doctoral-thesis context and source record maintained by Fabrizio Degni. Research and preferred citation Explore framework background and specialist modules History, principles, complementary lifecycle context and the full module catalogue The PALO value proposition ## From theory to practice PALO operationalizes responsible AI governance by turning principles into decisions, controls, measurements, and evidence that a team can use. Find your operating path 01 Frame02 Classify03 Assess04 Control05 Measure06 Prove and review 01 ### Frame the use case Make the purpose, stakeholders, affected people, lifecycle owner, and intended outcome explicit before implementation begins. AI Model Canvas Human Agency Risk Map Tech Trends Observatory AI Incident Observatory 02 ### Classify the case Translate the context into an initial risk route, check relevant obligations, and record why the classification is justified. Risk Tiering Calculator Framework Comparison Regulatory Watch 2026 03 ### Assess impacts and delegated action Identify fundamental-rights impacts and, where systems can act or use tools, define authority, autonomy, action space, and human oversight. FRIA Assessment PALO-AM Assessment Path 04 ### Design and operate controls Connect the risk to engineering, process, and review controls. Use specialist modules when the risk concerns AI-assisted development, hidden behavior, or data integrity. Vibe Coding Governance AuditBench Explorer Poisoning Boomerang 05 ### Measure, evidence, and review Turn the governance intent into KPI/KRI, collect the route and sources, export the evidence bundle, and keep the work usable in the next review. KPI and KRI Generator Evidence Bundle Documentation Library P.A.L.O. Toolbox European policy contribution / September 2026 ## Governing delegated AI action in Europe Explore PALO's complementary proposal for the AI Act and enacted Digital Omnibus: accountable mandates, bounded agent actions, verified effects and a proportionate institutional pathway. Read the EU proposal and use the review toolkit Independent discussion proposal. PALO-AI remains a developer preview; no EU endorsement is implied. PALO v3.1.0 ## Start here Three clear entries for the first governance conversation. Choose a starting point, then keep the decision connected to evidence. 01 Classify ### Classify the case Translate purpose, actor, context, and affected people into an initial risk route. Open Risk Tiering 02 Assess ### Assess impacts Use the guided path to check Article 27 context and fundamental-rights questions. Start Assessment Path 03 Evidence ### Build the evidence Route the work to controls and KPI/KRI, then export a versioned local evidence bundle. Build the bundle Regulatory Watch 2026 ## Dates with sources Article 4 literacy, Article 50 transparency, GPAI enforcement and the high-risk timeline, with official sources reviewed on 22 September 2026. Open Regulatory Watch PALO Assessment Path ## From case to record Risk Tiering, contextual FRIA, controls, KPI/KRI, and a local JSON or Markdown bundle with version, sources, and disclaimer. Open the guided path Documentation Library ## Readable online Browse the lifecycle, interactive modules, primary PDFs, worksheets, source links, and contribution notes in one indexable hub. Open Documentation Library Platform Map ## Navigate by decision See implemented, foundation, and research states; follow stakeholder intent to a module and the artifact it should produce. Open Platform Map Release verification ## PALO 3.1 and PALO-AI 2.7 baseline Review the source revision, CI run, validation totals, negative-test coverage, tagged artifact checksum and current maturity limits. Open release record Proof and Community ## See the public record Review public references, the Human Economic Forum context, app store links, source notes, and the media kit. PolicyWatcher adds an external policy-monitoring companion. Open RecognitionCommunityPolicyWatcher ## The Problem: "ROI Myopia" Traditional frameworks focus narrowly on immediate financial returns, ignoring the "hidden iceberg" of risks: algorithmic bias, reputational damage, and regulatory penalties. - Ignoring long-term ethical debt - Lack of standardized governance - Reactive instead of proactive compliance ## Why PALO? Principled. Actionable. Live. PALO isn't just a checklist. It's a comprehensive Lifecycle Orchestration paradigm. We convert abstract ethical principles into concrete KPIs, decision gates, and operational realities. 360 deg Evaluation Ethical, technical, business, and legal. 5 System activities Ideation through responsible retirement. See It In Action ## The Framework Explained The YouTube player loads when you select Play. Read the framework guide. Discover how PALO integrates ancient wisdom with modern AI governance. Play the PALO trailer 1 ### Ideation & Screening Before coding, we screen for ethical red flags. Is the project aligned with human values? 2 ### Ethical KPIs We translate "fairness" into measurable metrics like Demographic Parity Difference. 3 ### Responsible Deployment Continuous monitoring ensures the AI remains aligned with its original ethical intent. Core Tenets ## Built on Universal Values PALO synthesizes global standards into actionable business logic. ### Fairness & Non-Discrimination Proactive bias detection and mitigation strategies embedded from the very first data collection phase. ### Human Agency & Oversight Ensuring AI empowers humans. Implementing "Human-in-the-loop" protocols for critical decisions. ### Societal & Environmental Well-being Moving beyond "do no harm" to actively measuring carbon footprints and societal impact. Complementary system-lifecycle view ## Five system lifecycle activities This implementation roadmap from ideation to retirement complements, and does not replace, the canonical six-phase PALO governance loop: Frame, Classify, Assess, Control, Measure, Prove & Review. - Frame the purpose ### Ideation & Screening Ethical red flags check & strategic alignment. - Set the route ### Assessment & Planning ISO 42005 Impact Assessment & Risk Tiering. - Build the controls ### Dev & Validation Ethical-by-design & bias mitigation. - Monitor the system ### Deployment Continuous monitoring & feedback loops. - Close responsibly ### Decommissioning Responsible end-of-life & data disposal. Not sure where governance should enter this system lifecycle? Find your PALO route New Tool Available ## PALO Model Canvas AI A comprehensive evaluation framework for responsible AI use cases. Assess risks, ensure compliance, and make informed decisions aligned with global standards. ### Strategic Alignment Evaluate AI projects against organizational objectives and societal well-being. ### Risk Assessment Dynamic benchmarking based on EU AI Act risk tiers and PALO framework metrics. ### Integrated KPIs Track technical, business, and ethical KPIs with real-time compliance scoring. ### Standards Mapping Aligned with ISO 42001, ISO 42005, OECD AI Principles, and NIST AI RMF. Launch Model Canvas Free to use - No registration required - Export your analysis EU AI Act Readiness ## Fundamental Rights Impact Assessment A governance-support assessment for identifying fundamental-rights impacts before deployment. It supports Article 27 readiness for deployers within its scope. ### What is FRIA? A Fundamental Rights Impact Assessment (FRIA) is a systematic evaluation that supports Article 27 readiness for certain deployers of high-risk AI systems. It identifies, analyzes, and documents how an AI system may affect the fundamental rights enshrined in the EU Charter, including dignity, privacy, non-discrimination, and fair trial. ### When is a FRIA required? - Legal Scope: Article 27 applies to specific in-scope deployers, not every high-risk deployment - Public Services: Relevant for public authorities and private entities providing public services - Accountability: Documents due diligence and risk mitigation efforts ### 51 EU Charter Rights Complete coverage of all fundamental rights from the EU Charter of Fundamental Rights. ### Scenario-Based Analysis Identify up to 5 impact scenarios with affected groups and root cause analysis. ### Risk Prioritization Automatic severity x likelihood calculation with visual risk matrix. ### Import & Export Save your assessment, resume later, or download a comprehensive report. Start FRIA Assessment Free online tool - Client-side processing - Your data stays local Mobile toolbox Available ## P.A.L.O. Framework Toolbox Carry a private, offline pre-screening workspace for responsible AI decisions across Android, iPhone, and iPad. Open Toolbox details Google Play App Store Offline by design. Preliminary self-assessment only; no compliance certification or legal advice. - Risk and impact screeningRisk Tiering and FRIA preparation. - Audit-ready checklistsLocal progress across major governance references. - Evidence and reportsEvidence Vault, PDF dossiers, and Markdown export. - Specialist toolsAuditBench, KPI Generator, and Model Canvas access. Alignment research Interactive ## AuditBench Explorer Investigate hidden model behaviors, practice alignment auditing, and turn findings into PALO-aligned mitigation evidence. Open AuditBench Explorer Based on the AuditBench alignment auditing benchmark by Sheshadri et al. (2026). - 14 hidden behaviorsInspect concealment, sycophancy, and policy bias. - Investigator simulatorPractice prefilling, persona sampling, and probes. - Readiness assessmentUse a 14-point checklist and radar view. - Exportable findingsRecord mitigations for each behavior category. Forensic systems analysis Case 001 ## PALO AI Incident Observatory Compare the reported July 2026 OpenAI / Hugging Face agentic incident with the authority gates of a production-hardened PALO deployment. Open Case 001 Read September updates Report facts and conditional PALO counterfactuals remain explicitly separated and source-auditable. - Source-bounded recordEvery incident claim carries a report page reference. - Two-layer incident railObserved behavior paired with exact authority gates. - Independent cut pointsAdmission, capability, receipt, verification, and hold. - Technical infographic labLandscape and vertical SVG/PNG compositions. Governance study March 2026 ## The Poisoning Boomerang Examine when crawler defenses become model-governance risks, with practical detection routes and lifecycle controls. Open Poisoning Study Research and governance analysis by Fabrizio Degni, covering EU AI Act Articles 10 and 15. - 6 poisoning toolsCompare tarpits, perturbations, and labyrinths. - 5 detection strategiesMove from policy analysis to spectral checks. - Regulatory analysisUnderstand data integrity and resilience tensions. - Lifecycle controlsMap poisoning risks across the five system lifecycle activities. ## Get in Touch Interested in adopting the PALO Framework? Connect with us directly. ### Email Us For general inquiries and implementation support. info@paloframework.org ### Connect on LinkedIn Follow Fabrizio Degni for updates and insights. View Profile ## Changelog Recent updates and new features. Platform releases and independently versioned components remain distinct. Full changelog Version inventory Release verification Release RSS RELEASE August 2026 - PALO-AI v2.7 - Data Assurance Control Plane: Added Action Claim 1.4, payload-minimized context evidence, purpose-bound Data Fitness, signed Disclosure Contracts and Receipts, tenant-bound MCP operations, continuous invalidation and fail-closed disclosure incidents. It remains a non-production developer preview. - v3.1.0 - Governance Control Plane: Added twelve applicability-aware control packs, 31 controls, 38 indicators, ten evidence-contract families and a fail-closed PALO-AI production-admission boundary. - v3.0.1 - Evidence Pack Activation: Made Evidence Pack the primary route with a preloaded local case, three gold cases, a voluntary SHA-256 validation receipt, Community Casebook tooling and a 30-day new-module freeze. - v3.0.0 - Semantic Foundation: Added stable semantic identity, lifecycle and append-only gate decisions, atomic evidence contracts, RDF/SHACL invariants, versioned mappings, a generated Semantic Inspector and digest-bound release inventory. - v2.5.0 - Full-Cycle Agentic Assurance: Added Effect Contracts, one-time capabilities, trusted Execution Receipts, authoritative Outcome Attestations, Assurance Incidents and the n8n Governed Action preview. An allowed action is no longer presented as a verified result. - v2.4.1 - PALO-AI Developer Preview: Published versioned governance contracts, a non-production MCP reference server, draft Rego v1 policies, prototype approval and evidence flows, and non-production n8n/Dify examples. Runtime enforcement, production cryptographic evidence, authenticated mobile approval workflows, production connectors and collaborative-agent-team execution remain under development. - v2.4.0 - Reliable Operational Evidence: Added deterministic publication, interoperable local case/evidence files, import/resume handoffs, board packs, the PALO-AM Simulator MVP, and critical browser flows. - v2.3.2 - Stakeholder Onboarding: Added a three-question local onboarding route, personalized module guidance, local JSON and Markdown export, and a guided handoff into the weighted workflow and 3D operational graph. - v2.3.1 - From Theory to Practice: Added the operating loop that connects all core PALO modules to concrete decisions, controls, KPI/KRI, evidence bundles, and review. - v2.2.0 - Guided Assessment and Evidence Hub: Added three Start Here entries, the PALO Assessment Path with local JSON and Markdown evidence bundle export, Regulatory Watch 2026, the web-native Documentation Hub, a unified shell, and Proof & Community media kit links. - v2.1.0 - Regulatory Readiness and Trust Foundations: Updated Article 27 and Article 50 wording, added current Commission timeline notes, refreshed privacy/security/accessibility status, completed page metadata, and published the Recognition and Sources page. NEW MODULE June 2026 - v2.0.0 - PALO-AM Agentic Governance Modality: New PALO extension for governing AI agents and agentic systems. Features five operational object cards (Identity, Authority, Risk Matrix, Control Layer, Evidence Layer), the Action-Space vs Autonomy Matrix with four tiers, a complementary five-activity system lifecycle overlay for agentic systems, 11 KPI/KRI indicators and worked enterprise scenarios. Aligned with IMDA MGF v1.5, EU AI Act, ISO/IEC 42001/42005 and NIST AI RMF. - v2.0.1 - Documentation Sync: README, roadmap, CHANGELOG, sitemap, RSS feed, store links and homepage release notes aligned with the live framework state. NEW EXTENSION May 2026 - v1.8.0 - Enterprise Security & Governance for AI-Assisted Software Development Environments (Section 4.7.X): New PALO extension covering governance of AI-assisted software delivery - functional analysis, rapid prototyping and development. Features a three-layer model (Functional Intent, Controlled Environment, Evidence & Assurance), six decision gates, KPIs/KRIs. Includes vibe coding and AI coding assistant governance. MOBILE RELEASE April 2026 - v1.7.1 - P.A.L.O. Framework Toolbox for iOS/iPadOS: App Store release for iPhone and iPad with Evidence Vault, biometric protection, PDF report generation and direct access to PALO web modules. NEW MODULE March 2026 - v1.7.0 - The Poisoning Boomerang: New research module analyzing the data poisoning ecosystem - 6 tools (Miasma, Nepenthes, Nightshade, Glaze, Cloudflare AI Labyrinth, AttackAI), 5 detection strategies, EU AI Act governance analysis (Articles 10 & 15), and full PALO lifecycle integration for data integrity governance - v1.6.0 - Android Companion App: P.A.L.O. Framework Toolbox released on Google Play as an offline, privacy-first mobile pre-screening toolkit for AI governance workflows. - v1.5.0 - AuditBench Explorer: Interactive deep-dive into 14 hidden AI behaviors, auditing techniques, investigator simulations and PALO-aligned mitigation strategies. - v1.5.0 - Companion App Landing Page: Dedicated page for the offline mobile app, with Evidence Vault, assessment tools and mobile-first governance workflow messaging. - PALO Governance Notes: Data poisoning recognized as a cross-cutting risk across all five system lifecycle activities - new compliance advisories for Article 10 & 15 obligations, FRIA integration guidance, and data integrity KPI recommendations 2026 SPOTLIGHT January 2026 - Community & Open Collaboration: Dedicated page for open-source contributors, peer review, and partner organizations - Human Agency Risk Map: New observatory tracking 18 activities humans are delegating to AI, with PALO mitigation strategies and psychological impact analysis for the age of automation - 2026 Tech Trends Observatory: Comprehensive analysis of technology predictions from McKinsey, BCG, Accenture, PwC, EY, KPMG, and Gartner with PALO governance impact assessments NEW December 2025 - Risk Tiering Calculator: 3-step wizard to classify AI use cases into EU AI Act risk tiers (Minimal, Limited, High, Unacceptable) with required documentation guidance - KPI Generator: Generate personalized Technical, Business, and Ethical KPIs based on PALO Table 2 with export to CSV/Markdown - FRIA Module: Interactive Fundamental Rights Impact Assessment tool for EU AI Act Article 27 compliance with 51 EU Charter rights, scenario analysis, and risk matrix - Accessibility: Public accessibility statement and review status, with the detailed policy available in the footer - SEO & Trust: Enhanced meta tags, Open Graph, robots.txt, sitemap.xml, and security.txt for better categorization - RSS Feed: Subscribe to PALO news and updates via RSS at feed.xml UPDATE November 2025 - Model Canvas AI: Enhanced wizard mode, use case templates, import/export functionality, and dynamic risk assessment - Comparison Tool: Side-by-side assessment comparison with visual scoring - Responsive Design: Mobile-optimized layouts across all tools LAUNCH October 2025 - Initial Launch: PALO Framework website with Model Canvas AI tool for responsible AI governance - Documentation: PALO Principles, Lifecycle stages, and KPI framework Download governance datasets and worked indicator examples --- ## AI governance assessment path Canonical URL: https://paloframework.org/PALO_AssessmentPath.html Editorial date: 2026-09-25 PALO Evidence Pack | v3 starter experience # From one AI use case to reviewable evidence. In less than ten minutes, turn one AI use case into a traceable evidence dossier that another person can review. This is a routing and evidence aid, not certification or a substitute for legal, technical, or independent assurance. Allowed is not verified. Use my own case Free browser tool. JavaScript required. No account. No answer is sent. Export is voluntary. Local-first assessment ## Five linked governance gates The path is a routing and evidence aid. It does not certify compliance or replace a legal, technical, or fundamental-rights review. 01 ### Risk Tiering Describe the system and its intended use. 02 ### Contextual FRIA Route fundamental-rights questions when the context calls for them. 03 ### Controls Identify oversight, transparency, data, and incident controls. 04 ### KPI and KRI Turn the governance intent into measurable follow-up. 05 ### Evidence bundle Export the route, readiness, sources, and disclaimer. Built on the PALO Assessment Path. Case workspace | Step 1 to 4 ## Classify the case and build the route The form runs in your browser. No answer is sent to a server and no account is needed. No case loaded. Start below or import a PALO case/evidence JSON file. Import JSON The synthetic agentic invoice case is ready to load. ## Your PALO route ### Recommended next steps Inspect full Evidence Bundle JSON Voluntary local export ### Local validation receipt Check this evidence case against the published schema and create a SHA-256 digest. The receipt records a local validation result; it is not certification or independent assurance. No validation receipt created yet. Optional after-deployment monitoring signal Import a PolicyWatcher observation only when the core case route is ready. External monitoring companion | local receiver ### PolicyWatcher monitoring signal Import a structured observation locally. PALO preserves the complete signal and flags Measure and Prove for accountable review; confidence does not determine legal significance or control effectiveness. Optional companion. After deployment, PolicyWatcher can follow public privacy-policy and terms-of-service changes that may affect the operating context. Keep the original source and human review in the PALO evidence record. Import signal JSON Signal schema PolicyWatcher Observatory Confidence methodology Trust & Quality No signal imported. PolicyWatcher remains separate from PALO and no case data is sent to the portal. Use the route as a starting point. The export includes PALO version, route logic, evidence readiness, official source links, and a plain-language disclaimer so the next reviewer can see what was assessed and what remains open. --- ## Fundamental rights impact assessment Canonical URL: https://paloframework.org/PALO_FRIA.html Editorial date: 2026-09-25 Free browser tool; JavaScript required. Use PALO FRIA to organize evidence about how an AI use case may affect fundamental rights. Record the deployment context, affected people, mitigation and review decisions. See what a useful assessment record contains. ## What is FRIA and How to Use This Tool Click to expand the guide Collapse ### What is FRIA? A Fundamental Rights Impact Assessment (FRIA) is an Article 27 assessment for certain deployers of high-risk AI systems under Article 6(2). It helps identify how an AI system may affect the fundamental rights protected by the EU Charter in its specific deployment context. Who must conduct FRIA? - Public authorities deploying in-scope high-risk AI - Private entities providing public services - Deployers of in-scope creditworthiness and life or health insurance risk systems - Other organizations using this tool voluntarily as a readiness assessment ### How to Use This Tool - Step 1 - Context: Enter AI system details and classification - Step 2 - Checklist: Answer governance and compliance questions - Step 3 - Scenarios: Identify potential negative impact scenarios - Step 4 - Assessment: Rate severity and likelihood of each impact - Step 5 - Mitigation: Document risk mitigation measures - Step 6 - Decision: Make deployment decision and generate report Important: This tool processes all data locally in your browser. No information is sent to any server. Use the Export button to save your progress and Import to resume later. Regulatory status, reviewed 11 July 2026: The European Commission currently indicates that Annex III high-risk rules apply from 2 December 2027 and product-embedded high-risk rules from 2 August 2028. This tool is a governance-support and pre-screening resource, not legal advice or a compliance certification. Review the current Commission guidance. 1 Context 2 Checklist 3 Scenarios 4 Assessment 5 Mitigation 6 Decision ## AI System Context Provide information about the AI system being assessed. Tip: Use this assessment to prepare evidence before deployment. Article 27 applies to specific in-scope deployers, including public authorities, public-service providers, and certain creditworthiness and insurance use cases. AI System Name * Deployer Organization * AI System Description * AI Act Risk Classification FRIA supports Article 27 readiness. A legal obligation applies only to deployers within its scope. Intended Use Context Assessment Date Assessor Name ## Context Analysis Checklist Answer these questions about your AI system's governance, data, and oversight. ## Impact Scenarios Identify up to 5 scenarios where the AI system could negatively affect fundamental rights. ## Severity & Likelihood Assessment Assess the severity and likelihood of each identified impact. ## Mitigation Measures Document existing and planned measures to mitigate identified risks. ## Deployment Decision Review your assessment and make a deployment decision. Confidence in Assessment Deployment Decision Decision Rationale Step 1 of 6 ## Build a reviewable fundamental-rights impact record A useful fundamental-rights impact assessment connects a defined use case to affected people, plausible harms, safeguards and accountable decisions. Completing a checklist alone does not demonstrate that risks are adequately controlled. ### What to prepare - The intended purpose, deployment setting, responsible organization and people affected. - The evidence supporting each impact judgment, including uncertainty and information still missing. - Mitigation owners, human oversight, routes for raising concerns and conditions for reassessment. - A dated record of decisions and the reasons for accepting, changing or stopping the planned use. ### Example: an AI-supported service decision Map the decision path from data collection to human review and the outcome experienced by the individual. Consider who may be excluded, how errors can be challenged and whether the reviewer can meaningfully change the outcome. Keep the assessment tied to the actual deployment rather than a generic model description. Does PALO determine whether Article 27 applies? PALO supports preliminary readiness and voluntary governance work. Determine the applicable duties from the current official sources, actor role and deployment context with the responsible reviewer. The tool is not a legal opinion or certification. Review official regulatory sourcesStart with risk screeningConnect impacts, controls and evidence ## Try a completed fictional FRIA record A public-service triage example records an affected group, two rights, illustrative impact ratings, missing evidence, mitigation owners and a decision to halt deployment. It uses synthetic information and leaves legal classification unresolved. Download the worked FRIA JSON. Save your current work first, then use Import to inspect the example across all six steps. Explore governance registers. --- ## AI governance KPI and KRI generator Canonical URL: https://paloframework.org/PALO_KPIGenerator.html Editorial date: 2026-09-25 Free browser tool; JavaScript required. Select a model type, objective and sector to generate technical, business and ethical indicators. Export the selection, then assign owners and context-specific targets. See how to turn metrics into a governance register. Model Type Primary Objective Sector ## Your Personalized KPIs Technical KPIs 0 Business KPIs 0 Ethical KPIs 0 ## From AI metrics to accountable governance A KPI describes performance against an objective. A KRI signals exposure or a condition that needs intervention. The same measure can serve either role depending on its threshold, owner and agreed response. PALO's generator provides a starting selection, not a universal scorecard. ### Define the decision behind each indicator - Purpose: identify the outcome, risk or affected group the measure represents. - Method: record the formula, denominator, sampling period, data source and known limitations. - Ownership: name the reviewer, review frequency and response when evidence is missing or a threshold is crossed. - Evidence: preserve the relevant test or observation and link it to the governance decision. ### Example: a support assistant Track answer quality alongside unsupported claims, escalation quality and handling time. A faster response is not automatically a better outcome. Review a defined sample with an accountable owner and preserve the reasons for accepting or rejecting a result. Use subgroup analysis only where the data and purpose support a valid interpretation. Can I use the suggested target without calibration? Treat suggested targets as examples. Calibrate them against your system, evaluation data, affected people and risk appetite. Record uncertainty and avoid claiming fairness or safety from a single metric. Read worked KPI and KRI examplesConnect indicators to the evidence bundleInspect the versioned indicator registry ## Inspect a worked indicator register The synthetic CSV records supported answers (86/100), authority-boundary attempts (4/200) and escalation completion (18/20), with owners, review actions and limitations. These are teaching examples, not PALO deployment results or recommended targets. Download the worked KPI/KRI register · Inspect all 38 indicator definitions and reuse terms --- ## AI risk screening Canonical URL: https://paloframework.org/PALO_RiskTiering.html Editorial date: 2026-09-25 Free browser tool; JavaScript required. Use this EU AI Act screening tool to explore a preliminary route for one AI use case. Have the intended use, operating sector and level of autonomy ready. Read the method and limitations. Step 1: Sector Step 2: AI Function Step 3: Autonomy Results ## Select Your Sector Choose the industry where your AI system will be deployed. Healthcare HR / Recruitment Finance / Banking Critical Infrastructure Legal / Justice Public Sector Education Retail / E-commerce Marketing / Advertising ## Select AI Function What is the primary function of your AI system? Chatbot / Virtual Assistant Biometric Recognition Credit Scoring CV / Resume Screening Medical Diagnosis Content Generation Recommendation Engine Predictive Policing Social Scoring Fraud Detection ## Select Autonomy Level How much decision-making authority does the AI have? Human Assistant AI provides suggestions, human makes all decisions Human-in-the-Loop AI makes decisions, human reviews critical ones Autonomous Decision AI makes decisions without human intervention ## How to use the AI risk screening result This calculator helps governance, product and risk teams structure an initial screening conversation. It produces a hypothesis based on the answers supplied, together with issues that need further review. A short questionnaire cannot establish the legal classification of a deployed system. ### Prepare one defined use case - Describe the intended use and the people whose access, opportunities or rights could be affected. - Select the operating sector, AI function and degree of autonomy in the wizard. - Review the result against the actual actor role, deployment context, exceptions and current primary sources. - Carry the assumptions and open questions into the Assessment Path, then link the relevant controls and evidence. ### Example: recruitment support For an assistant that summarizes applications, distinguish administrative support from a system that filters, ranks or materially influences candidate decisions. Document what the system actually does and who can override it before relying on a risk route. This is an illustrative review question, not a classification of every recruitment tool. Does a low screening result mean the system is approved? No. Data protection, fundamental rights, security, contractual duties and sector-specific requirements may still require review. Record uncertainty and obtain accountable review before consequential deployment. Continue with the guided assessmentCheck dated regulatory sourcesAssess fundamental-rights impacts --- ## KPI and KRI worked examples Canonical URL: https://paloframework.org/docs/ai-governance-kpi-kri-examples.html Editorial date: 2026-09-25 Start and adoption | Public documentation # AI governance KPI and KRI examples: from measures to decisions Define useful AI governance indicators with worked formulas, denominators, evidence owners and review actions, without treating sample targets as assurance. By Fabrizio Degni | 2026-09-25 LevelguideAudiencegovernance | technical | builderProductPALO CoreStatusCurrent GuidanceLifecycleCurrentRead4 min Published HTML view | Source: docs/ai-governance-kpi-kri-examples.md On this page - What distinguishes a KPI from a KRI? - Three worked indicator definitions - Numerical example with a stated denominator - Choose thresholds from the decision context - Minimum fields for an indicator register - Keep measurement connected to review - Download the worked register AI governance indicators are useful when they connect a defined objective or risk to evidence, an accountable reviewer and an action. A dashboard with many metrics is not a substitute for that connection. PALO's KPI Generator suggests technical, business and ethical measures based on model type, objective and sector. The examples below explain how to turn a selection into a reviewable indicator register. They are illustrative definitions, not measured PALO deployment results or universal thresholds. ## What distinguishes a KPI from a KRI?# A key performance indicator tracks an intended outcome, such as the quality of reviewed answers. A key risk indicator signals exposure, such as consequential actions attempted outside a declared authority boundary. Whether a measure is useful depends on its scope, denominator, observation quality and the response it triggers. ## Three worked indicator definitions# | Indicator | Illustrative calculation | Evidence and owner | Review action | Supported-answer rate | Reviewed answers meeting the documented support rubric / all answers in the review sample | Versioned rubric, sampled answers and source checks; knowledge-service owner | Investigate failure categories and evaluate a revised system before expanding use | Authority-boundary attempt rate | Observed action requests outside the allowed scope / all observed action requests | Policy decisions with reason codes and a stated logging boundary; agent-service owner | Examine prompting, tool permissions, delegation and blocked-attempt patterns | Escalation completion rate | Escalations receiving a recorded accountable disposition within the agreed window / escalations due for review | Queue timestamps and decision records; operational review owner | Investigate overdue decisions, workload and whether escalation reaches a person able to act A blocked unauthorized request and a completed unauthorized action are different events. Track them separately. A low observed rate can also reflect missing logs rather than effective controls. ## Numerical example with a stated denominator# Suppose a reviewer examines 100 synthetic support answers using a documented rubric. If 86 satisfy every required support criterion, the supported-answer rate in that sample is 86%. That figure describes the selected sample only. It does not establish the population rate, fairness across groups, safety of consequential actions or performance after a model change. Record how the sample was selected, whether the cases are representative, the review procedure and unresolved disagreements. If some records cannot be evaluated, report that missingness rather than silently dropping it from the denominator. ## Choose thresholds from the decision context# Set targets and escalation conditions with the accountable owner. Consider the consequence of failure, exposure, user needs, baseline evidence and the ability to detect or reverse an unwanted effect. Do not adopt a suggested numerical threshold solely because it appears in a template. Pair efficiency measures with quality and risk measures. Lower handling time could accompany worse answers, reduced oversight or a larger review backlog. Investigate the trade-off before describing a change as an improvement. ## Minimum fields for an indicator register# - Name, purpose and relevant decision or control. - Formula, unit, numerator, denominator and exclusions. - Data source, observation boundary and known missingness. - System version, population or sample, and measurement period. - Owner, review cadence and agreed escalation action. - Supporting evidence, limitations and next review date. Use the versioned PALO KPI/KRI registry for the framework's indicator definitions. A project-specific register should preserve the relationship between a selected measure and the evidence that supports it. ## Keep measurement connected to review# After generating indicators, carry them into the Assessment Path. Review them alongside the use-case context and controls, rather than treating the export as an independent assurance conclusion. The invoice-agent worked example shows how an expected effect becomes a verification question. The board review template helps record the accountable decision and follow-up actions. ## Download the worked register# Download the synthetic CSV register with three rows: 86/100 supported answers, 4/200 authority-boundary attempts and 18/20 completed escalations. The file records denominators, missing-record counts, owners, review actions and limitations. These figures describe a teaching example, not a deployed PALO system. A zero missing-record count is an assumption of the example; it must not be copied into an operational register without checking completeness. For the complete definitions and reuse terms, open the governance data catalog. --- ## AI governance evidence example Canonical URL: https://paloframework.org/docs/ai-governance-evidence-worked-example.html Editorial date: 2026-09-25 Start and adoption | Public documentation # AI governance evidence: a worked invoice-agent example Follow a fictional invoice-agent case from authority boundaries to expected effects, review conditions and a locally exported PALO evidence bundle. By Fabrizio Degni | 2026-09-25 LevelguideAudiencegovernance | technical | builderProductPALO CoreStatusCurrent GuidanceLifecycleCurrentRead4 min Published HTML view | Source: docs/ai-governance-evidence-worked-example.md On this page - Start with the decision and authority boundary - Follow the six governance phases - Separate permission from the observed result - Read the example decision carefully - Export and hand over a useful record - Sources and related methodology - Compare the case with an impact-assessment record An AI governance evidence bundle connects a decision to its context, accountable owner, controls, observations and unresolved questions. It helps another reviewer understand what was assessed and what still needs to be established. A valid file format is only one part of that evidence. This walkthrough uses PALO's existing fictional invoice-exception case. It is an educational example with synthetic data and no payment, supplier or production connection. The reported sample outcome is not a measurement of a deployed system. ## Start with the decision and authority boundary# The question is whether an agent may collect invoice-exception evidence and draft a proposed resolution while a named person retains release authority. The sample permits reading synthetic invoice metadata and drafting an exception summary. It prohibits releasing a payment, changing supplier data or contacting the supplier. These distinctions belong in the record before the agent acts; an instruction to "handle the invoice" would leave the boundary unclear. Open the worked case in PALO Assessment Path or inspect the source Case File. ## Follow the six governance phases# | Phase | Question for the reviewer | Evidence to preserve | Frame | What use is intended, who is affected and who owns the decision? | Purpose, system boundary, owner and explicitly prohibited actions | Classify | Which risk route is plausible, and what context still needs review? | Screening assumptions, source references and unresolved classification questions | Assess | What could go wrong for people or delegated actions? | Impact questions, authority boundaries and oversight requirements | Control | What prevents or detects actions outside that boundary? | Proposed tool restrictions, reviewer identity and verification requirements | Measure | What observation would show that the intended effect occurred? | An expected draft and an independently checked, unchanged payment state | Prove and review | What can the evidence support, and what remains open? | Dated records, provenance, limitations, reviewer decision and follow-up The framework's phases organize the review. They do not make the sample's proposed controls production controls. ## Separate permission from the observed result# A policy decision allowing draft_exception says what may be attempted. It does not prove that the agent produced the right draft or avoided every prohibited effect. The sample's expected post-state is: json code { "draftCreated": true, "paymentReleased": false } A reviewer should also consider the other prohibited effects: supplier data must remain unchanged and no external supplier message should be sent. In a real implementation, the verification method, observation source and its trust boundary need separate validation. A tool's own success message is not independent evidence of all external effects. ## Read the example decision carefully# The source case records proceed-with-conditions. Its conditions are to keep payment release outside the agent's tool set, require reviewer identity and verify the post-state independently. That record is an illustrative decision, not an approval of your use case. Reviewers must establish whether those controls exist, are effective in the intended environment and cover the actual risks. Missing evidence should remain visible rather than becoming an implicit pass. ## Export and hand over a useful record# Use the Assessment Path to connect the context, screening and impact questions to controls and indicators. Export the local evidence bundle and review its version, source references, assumptions and unresolved questions before sharing it. Keep the original Case File and subsequent observations distinguishable. A schema-validation receipt proves that the file conforms to a contract; it does not establish legal compliance, security effectiveness or production authorization. The Case File and Evidence Bundle guide describes the interoperable record. Use the board review template to structure an accountable handover and the indicator examples to plan follow-up measurement. ## Sources and related methodology# The worked facts above come from the versioned PALO sample. The sample references the NIST AI Risk Management Framework as a starting point. Its inclusion is not an endorsement or a certification of PALO. For the wider operating model, read the PALO lifecycle guide, semantic foundation and agentic governance modality. ## Compare the case with an impact-assessment record# Download the fictional public-service FRIA record and inspect it in the FRIA tool. Save any current work before importing. Its context, affected groups, illustrative ratings, mitigation notes and halt decision show what an incomplete evidence base looks like. It is a separate teaching case, not an assessment of the invoice agent above. Use the worked indicator register to inspect formulas and denominators alongside review actions. These samples are educational inputs; they are not an executed runtime evidence bundle. --- ## Governance datasets and registers Canonical URL: https://paloframework.org/PALO_DataCatalog.html Editorial date: 2026-09-25 Open governance resources # AI governance datasets and registers Download the structured definitions behind PALO's indicators and security crosswalk. Each resource includes its scope, version, provenance, reuse terms and practical limits. These are curated governance definitions and mappings, not observations of deployed systems. A dataset download does not establish control effectiveness or compliance. ## PALO KPI and KRI registry A structured register of 38 AI governance indicator definitions. Entries connect a formula and unit to lifecycle phases, responsible roles, evidence and an action when a threshold is crossed. Suggested thresholds are illustrative and need calibration. Creator Fabrizio Degni, PALO Framework Version Schema 1.0.0; updated 23 August 2026 Status Educational, non-production Format JSON; 38 indicator definitions License MIT, under the PALO repository license Download registry JSONInspect JSON SchemaDownload a worked CSV register Start with the worked formulas and denominator examples, then use the KPI Generator to select indicators for a defined use case. ## PALO OWASP GenAI 2026 crosswalk An independent mapping of ten OWASP GenAI risk categories to three PALO routes, controls and evidence requirements. Direct, supporting and gap ratings describe design fit; they are not measurements of a deployment or proof of equivalence. Creator Fabrizio Degni, PALO Framework Version Analysis 1.0.2; reviewed 20 August 2026 Status Source-backed context; source editorial status marked provisional in the register Format JSON; 10 risks and 3 governance routes License CC BY-SA 4.0, as declared in the crosswalk Source OWASP GenAI Security Project; based on the OWASP Top 10 for LLM Applications 2026. Independent PALO mapping; no OWASP endorsement is implied. Download crosswalk JSONInspect JSON Schema Explore the crosswalk or read its method and attribution. The register preserves the scope and credit of the named technical contributor. ## Use and cite a specific version Save the original JSON, its version and retrieval date with your assessment. Preserve the license and attribution. Review the source record before reusing a mapping or threshold, and document changes you make. PALO means Principled AI Lifecycle Orchestration. The framework was created and is maintained by Fabrizio Degni. For research provenance, use the publication and evidence ledger. Curated resource index · Text of the selected public resources --- ## OWASP GenAI crosswalk Canonical URL: https://paloframework.org/PALO_OWASPGenAI2026.html Editorial date: 2026-09-25 Documentation reference | source-backed crosswalk | technically reviewed 20 August 2026 # OWASP GenAI / LLM Top 10 2026 x PALO PALO is a governance and assurance system; OWASP is a security risk catalog. The relationship is complementary, not equivalent. This page is a documentation reference - not a new PALO module or activation route. Overall verdictStrong governance fit. Incomplete technical resolution. Open Assessment Path Open source PDF View crosswalk JSON OWASP GenAI initiative Overall conclusion ## PALO routes the work. It does not erase the risk. The crosswalk is strongest where security requires ownership, bounded decisions, evidence and review. Mechanism-specific safeguards - retrieval authorization, model and data integrity, rate controls, output encoding and production identity - remain separate engineering obligations. 01 ### No elimination or certification claim PALO does not eliminate any OWASP risk and does not certify OWASP compliance. 02 ### Lifecycle assurance The framework supplies ownership, decision gates, control records, evidence and residual-risk review. 03 ### Delegated authority PALO-AM addresses identity, authority and blast radius when an LLM becomes an actor. 04 ### Selected action-path enforcement PALO-AI can enforce exact claims, policy, approval, capability and outcome evidence, but remains a non-production Developer Preview. Evidence boundary: a verified effect proves authoritative post-state against an Effect Contract. It does not prove factual truth or causal correctness. One framework | three connected routes ## Coverage deepens as the system gains authority. Read each route as a distinct governance layer. A "Direct" rating in one layer does not replace an OWASP-specific safeguard in another. 01 / Umbrella system ### PALO Framework 6Direct4Supporting0Gap Lifecycle governance, accountable owners, control selection, evidence, monitoring and review. See the framework route 02 / Specialist method ### PALO-AM 5Direct5Supporting0Gap Agent identity, delegated authority, autonomy, tool boundaries, meaningful human oversight and circuit breakers. Open PALO-AM 03 / Technical route ### PALO-AI Developer Preview 4Direct4Supporting2Gap Exact claims, policy, approval, one-time capability, trusted receipt and outcome verification. Production security gaps remain. Review the evidence boundary Coverage matrix ## Ten risks. Three governance lenses. Ratings describe design fit - not implementation effectiveness, compliance or certification. Direct A first-class PALO artifact or control materially addresses the risk. Supporting PALO contributes governance or containment; OWASP-specific safeguards are still required. Gap No specific current PALO-AI coverage for the main mechanism. Showing all 10 risks. Coverage ratings for the OWASP GenAI / LLM Top 10 2026 across the PALO Framework, PALO-AM and PALO-AI | OWASP risk | PALO Framework | PALO-AM | PALO-AI | LLM01 Prompt Injection | Direct | Direct | Direct | LLM02 Sensitive Information Disclosure | Direct | Supporting | Supporting | LLM03 Excessive Agency | Direct | Direct | Direct | LLM04 Supply Chain | Direct | Supporting | Supporting | LLM05 Data and Model Poisoning | Direct | Supporting | Gap | LLM06 Unbounded Consumption | Supporting | Direct | Supporting | LLM07 Misinformation | Direct | Direct | Direct | LLM08 Hidden Context Exposure | Supporting | Direct | Direct | LLM09 Vector and Embedding Weaknesses | Supporting | Supporting | Gap | LLM10 Improper Output Handling | Supporting | Supporting | Supporting Interpretation: "Direct" means a relevant route exists in PALO. It never means that the risk is prevented, resolved in every deployment or safe without the listed technical safeguards. Can PALO solve it? ## A precise answer, risk by risk. Each dossier separates PALO's governance contribution from the safeguards that must exist in the model, data, retrieval, infrastructure or application layer. LLM01 Prompt InjectionContain - do not promise prevention ### PALO contribution Treat model output as untrusted; apply least privilege, deterministic mediation, meaningful approval and adaptive testing around consequential actions. ### External safeguards required Multimodal filters, Unicode normalization, content provenance and red teaming that reflects the defenses actually disclosed and deployed. ### Minimum evidence Threat model, injection test suite, policy decision logs, approval records and failed-path evidence showing that privileged execution cannot bypass mediation. LLM02 Sensitive Information DisclosureGovern exposure; engineer isolation ### PALO contribution Set data-minimization and provenance requirements, establish accountable ownership, and connect detection to incident and residual-risk review. ### External safeguards required Retrieval-time chunk ACLs, tenant isolation, DLP, log and trace redaction, and protection of vector stores and credentials. ### Minimum evidence Data-flow map, access-control tests, redaction samples, tenant-boundary tests, incident route and approved retention decisions. LLM03 Excessive AgencyStrongest PALO fit ### PALO contribution Define the authority profile, minimum tools and permissions, user context, meaningful approval, one-time capability and evidence of both execution and outcome. ### External safeguards required Production identity, tenant-aware RBAC and execution architecture in which the governed path is unavoidable remain prerequisites. ### Minimum evidence Agent registry, authority profile, tool inventory, policy tests, immutable approval, capability record, trusted receipt and authoritative post-state verification. LLM04 Supply ChainGate suppliers and change ### PALO contribution Route supplier due diligence, ownership, acceptance criteria and material component changes through evidence-backed review gates. ### External safeguards required AIBOM or ML-BOM, pinned artifacts, signatures and transparency, vulnerability management, patching, and connector attestation. ### Minimum evidence Supplier assessment, component inventory, artifact digest, verification result, vulnerability status, connector attestation and approved change record. LLM05 Data and Model PoisoningGovern integrity; technical gap in PALO-AI ### PALO contribution Maintain lineage, change control, adversarial test expectations, accountable release decisions and rollback governance. LLM05 owns persistent corruption of source data, chunks, training inputs or the embedding model; the Data or Model Owner and MLOps Owner remain accountable. ### External safeguards required Pipeline integrity, poisoning and backdoor detection, signed artifacts, sandboxing and monitored feedback loops. ### Minimum evidence Dataset and model lineage, artifact signatures, persistent corpus-poisoning and retrieval-impact results, pipeline attestations, monitored feedback records and a tested rollback decision. LLM06 Unbounded ConsumptionBound action; add production abuse controls ### PALO contribution PALO-AM circuit breakers and a bounded action space constrain delegated behavior and supply escalation and stop conditions. ### External safeguards required PALO-AI lacks production rate limiting and abuse controls. Add token, action, time and cost caps, queue limits, loop detection, graceful degradation and infrastructure hardening. ### Minimum evidence Limit configuration, exhaustion and loop tests, cost alerts, circuit-breaker events, degradation test and capacity or resilience review. LLM07 MisinformationVerify decisions and effects - not truth by default ### PALO contribution Require source-backed decisions, claim-check-act separation, human review and authoritative post-state verification for consequential actions. ### External safeguards required Grounding and verified effect do not prove factual truth. Add domain evaluation, omission checks and evidence-freshness controls. ### Minimum evidence Claim-to-source trace, domain evaluation set, omission tests, reviewer decision, freshness threshold and effect-verification record. LLM08 Hidden Context ExposureExternalize authority from prompts ### PALO contribution PALO-AM and PALO-AI move critical authorization out of the prompt and into explicit authority, policy and protected execution contracts. ### External safeguards required Remove secrets from hidden context, externalize credentials and configuration, and test systematic extraction across supported modalities. ### Minimum evidence Prompt and context inventory, secret-scanning result, credential-flow diagram, extraction tests and proof of external policy enforcement. LLM09 Vector and Embedding WeaknessesCurrent targeted gap ### PALO contribution and ownership PALO can assign ownership, classify data, require controls, record evidence and decide residual risk, but does not implement the retrieval mechanism. LLM09 and the Vector Store Owner own attacks that depend on embedding geometry, similarity ranking, collisions, membership inference or inversion. Persistent source or chunk corruption is handed to the LLM05 Data or Model Owner. ### External safeguards required Pre-retrieval chunk authorization, trust-zone-separated indexes, embedding provenance and lifecycle controls, inversion resistance assessment, adversarial-query retrieval-evasion and similarity-collision testing, deletion reconciliation, ranking anomaly detection and immutable retrieval logs. Treat exported vectors and backups at source-data sensitivity. ### Minimum evidence Index topology; tenant and chunk-ACL tests; provenance and deletion reconciliation; quantified Vec2Text, ZSInvert, Zero2Text or threat-model-equivalent inversion results; retrieval-evasion, collision and threshold-straddling tests; vector-layer poisoning and ranking-manipulation results; tamper-evident trace; residual-risk decision. LLM10 Improper Output HandlingCurrent targeted extension ### PALO contribution PALO validates governance claims and can mediate consequential actions, but does not validate or sanitize every downstream content sink. ### External safeguards required Context-specific encoding, prepared queries, CSP, terminal-control sanitization, outbound fetch restrictions and generated-code security tests. ### Minimum evidence Sink inventory, encoding and injection tests, CSP policy, query binding evidence, egress controls and generated-code security results. Governance operating model ## Make the crosswalk a living review object. OWASP supplies risk context. PALO supplies the accountable loop that keeps applicability, controls, tests, evidence and decisions reviewable as the system changes. Classification Informative security source - not law, standard or certification. Accountable owner Product Security or AI Governance owns the crosswalk process; system-level risk owners remain accountable for treatment decisions. Review cadence Every 90 days, and immediately after an OWASP revision, architecture/tool/memory/data-scope change, material incident or failed critical test. Required per-risk record Applicability, owner, implemented control, test, evidence link, residual risk, decision and reopen trigger. Source discipline Preserve version, date, hash, attribution and source status. Treat mappings as source-backed context, never canonical equivalence. Model as component ### Apply this LLM Top 10 Use the present crosswalk for applications in which the model is a component within a bounded product or workflow. Tools | persistent memory | multi-step or autonomous action ### Pair with the OWASP Agentic Top 10 Apply the PALO-AM and PALO-AI route when delegated authority, tool execution, persistence or autonomous action expands the control surface. Seven-step operating loop ### A source becomes useful when it changes a decision. - 01RegisterPin the source and hash. - 02ScopeDecide applicability. - 03AssignName the risk owner. - 04ControlRecord treatment. - 05TestExercise the mechanism. - 06DecideAccept residual risk. - 07ReopenAct on change or failure. What was integrated ## Four artifacts. One explicit source boundary. The integration preserves the report as external security context. Nothing is silently promoted into a canonical PALO equivalence. - 01 / Source ### Version-pinned local PDF The reviewed OWASP GenAI / LLM Top 10 2026 v1.0 artifact. Open PDF - 02 / Registry ### Source registry entry Publisher, official URL, check date, freshness, authority and use boundary. - 03 / Data ### Versioned crosswalk JSON Machine-readable ratings and risk-level rationale, with the PDF hash pinned for downstream review. Open JSON - 04 / Analysis ### This web dossier A board-readable comparison of fit, safeguards, evidence and governance cadence. Review matrix No silent promotion: source terms remain attributed to OWASP; PALO mappings remain interpretive governance context and must be revalidated as either source changes. Limitations and attribution ## Use the mapping. Preserve the boundary. - PALO support does not imply OWASP endorsement. - The OWASP source is licensed under CC BY-SA 4.0. This page's source-derived category names, summaries and crosswalk are also published under CC BY-SA 4.0; consult the source for the complete risk descriptions and guidance. - The credited personal contribution does not mean that OWASP reviewed or endorsed the PALO analysis. - The report covers LLM applications. Agentic deployments require the paired Agentic list and the PALO-AM/PALO-AI route. PDF SHA-256ef87993a4e50ae9d83b41ff7a3d3e6320a82dfa8d4ec6bf98d0ce264b2e6108e Download the versioned crosswalk JSON and inspect its license and provenance. --- ## PALO-AM methodology Canonical URL: https://paloframework.org/PALO_AgenticGovernance.html Editorial date: 2026-10-12 PALO-AM v2.0 - CURRENT METHODOLOGY BASELINE - JUNE 2026 # Agentic Governance Modality From Model Governance to Delegated-Action Governance PALO-AM is the agentic governance modality inside the PALO Framework. It is distinct from the PALO-AI runtime. It defines the identity, delegated authority, autonomy, oversight, reversibility and assurance model for AI systems that select tools, write to systems, trigger workflows and act on behalf of the organization. Open PALO-AI Governance HubView Production Readiness Assessment: 17 September 2026. An unreleased swarm snapshot demonstrates central coordination of remote workers, shared budgets, membership revisions and supported cancellation. Evidence and remaining gaps. The baseline contract and tool counts below refer to the published runtime. FD Fabrizio DegniChief AI Officer 5Object Cards 4Risk Tiers 11KPIs / KRIs 6Canonical Lifecycle Gates ## Taxonomy and controlled dictionaries Explore lifecycle, identity, delegated authority, action states, data, controls, indicators and evidence as separate classification axes. The catalogue includes 65 JSON Schemas, including the PolicyWatcher batch, operational signal registry and browser-local review ledger. Lexical values retain their schema and field context. Read the taxonomy and dictionaries Search the complete technical catalogues ## Ontologies and their operational grounding Inspect the 27 core OWL classes, 18 object properties, 18 datatype properties and 12 SHACL shapes, then follow their relationship to JSON contracts and reference execution records. The separate stack extension remains draft; ontology validation does not grant authority to act or establish production effectiveness. Read the ontology deep dive Download the complete technical dossier ## European delegated-action governance proposal How PALO complements the AI Act and enacted Digital Omnibus: legal crosswalk, an open technical profile, a proposed pilot and operational review tools. Independent discussion proposal; no EU endorsement. Open the EU proposal PALO-AM ## The Governance Shift Model governance asks whether the model behaves responsibly. Delegated-action governance asks whether the authority delegated to the system has been justified, bounded, monitored and evidenced. ### Model Governance Does the model behave responsibly? Accuracy, bias, explainability, robustness, privacy, data lineage, output safety. -> ### Delegated-Action Governance Is the delegated authority justified, bounded, monitored and evidenced? Identity, permissions, tools, memory, autonomy, checkpoints. A hallucinated sentence can mislead. A hallucinated tool call can alter a customer record, leak sensitive data, trigger a transaction or damage an operational environment. P1 MVP ## PALO-AM Simulator Route a delegated-action configuration to a governance tier and a practical control, evidence, and KPI/KRI starting set. Results are educational governance support, not legal advice, certification, or a compliance determination. ### Developer-preview contract & approval viewer Demonstrates profile, decision and approval exchange in Web and mobile clients. It is not a production authorization interface. Import trusted agent profile Import policy decision Import approval packet Gateway URL Gateway bearer token Resolver identity Decision rationale No runtime contract loaded. Developer preview: the online endpoint is Internet-reachable but is not production-ready. Its bearer token is only a coarse developer control and does not authenticate an accountable reviewer or separate administrative roles. Use isolated test data and non-consequential tools. For a local evaluation, replace the URL with http://127.0.0.1:8787. 01 ## Five Operational Object Cards Each object is a governance domain that can be documented, implemented, tested and audited. Together they translate PALO-AM from a concept into a working operational model. 1 ### Agent Identity Profile Defines who or what the agent is inside the enterprise environment. Records the agent identifier, cryptographic provenance, accountable human owner, business unit, topology, credential lifecycle, data clearance and revocation procedure. Eliminates anonymous or shared AI execution contexts and provides the basis for attribution. 2 ### Agent Authority Profile Defines what the agent may do. Lists permitted tools, environments, data classes, read/write/delete privileges, financial thresholds, approval requirements, external endpoints, multi-agent coordination rules and abort conditions. The enforceable contract between the business and the agentic system. 3 ### Agentic Risk Matrix Determines the risk tier by examining action-space impact, autonomy level, reversibility, data sensitivity, third-party dependency, speed/volume and multi-agent complexity. Acts as the routing mechanism for required controls and decision gates. 4 ### Agentic Control Layer Implements structural safeguards around the agent: policy-as-code, API gateway constraints, token scopes, rate limits, schema validation, tool allow-lists, sandboxing, circuit breakers, human checkpoints and change-management rules. 5 ### Agentic Evidence Layer Captures auditable execution evidence without relying on private model chain-of-thought: planning artifacts, tool calls, structured inputs/outputs, policy decisions, human approvals, overrides, anomalies, incidents, KPI values and decommissioning proofs. 02 ## Engineering Control Layer PALO-AM treats governance as an enforceable architecture, not a policy statement. The language model is treated as an untrusted reasoning engine for purposes of authority. The model may propose an action; the orchestration layer decides whether it is allowed. #### Why Prompt-Layer Safeguards Are Insufficient A prompt instruction such as "do not access confidential data" is not equivalent to an access control. It can be misunderstood, bypassed, or contradicted. In agentic systems, the consequence is not merely an unsafe response - it may be an unauthorized action. High-impact actions require deterministic controls. #### Cryptographic Identity & Zero-Trust Every agent execution must carry a verifiable identity. Tool calls must include signed identity headers. Credentials must be short-lived, rotated and centrally managed. No agent may share credentials with another agent or a human user. Zero-trust: no implicit trust for any agent action. #### Tool Allow-Lists & Schema Validation Agents may only call tools explicitly listed in their Authority Profile. Each tool call must conform to a validated schema. Unrecognized tool calls must be blocked at the orchestration layer before execution. Block first, allow explicitly. #### Human-in-the-Loop Checkpoints (HITL) Human checkpoints must be designed structurally, not optionally. High-stakes or irreversible actions require explicit human approval via a decision packet - not a vague approval button. Approval telemetry must be measured against the Automation Bias Index (ABI). Meaningful oversight, not rubber-stamping. #### Circuit Breakers & Abort Conditions Each agent must have defined safe-state, rollback path and stop conditions. Circuit breakers must interrupt cascading failures in multi-agent topologies. Abort conditions must be tested in historical Phase 3 and validated against the CECR metric in historical Phase 4. Design for safe failure, not only for success. #### OpenTelemetry Observability All tool calls, approval events, policy decisions and anomalies must feed into a tamper-evident audit endpoint (SIEM, OpenTelemetry collector or governance dashboard). Evidence must be structured and machine-readable for KPI measurement. If it is not observed, it is not governed. 03 ## Action-Space vs Autonomy Matrix The primary PALO-AM routing instrument. Examines two dimensions: what can the agent change (action-space impact) and how independently can it decide (autonomy level). Any increase in autonomy or action-space after approval triggers historical Phase 2 reassessment. Scroll horizontally to inspect all matrix columns → ↔ Autonomy Level (rows) x → Action-Space Impact (columns) Low Impact (read-only, reversible) Medium Impact (internal write) High Impact (cross-system) Critical Impact (financial/safety/legal) High Autonomy Tier 2 Tier 1 Tier 1 Redesign required Medium Autonomy Tier 3 Tier 2 Tier 1 Tier 1 Low Autonomy Tier 3 Tier 3 Tier 2 Tier 2 Supervised Tier 4 Tier 4 Tier 3 Tier 3 Tier 1 - Maximum Controls Tier 2 - Controlled Tier 3 - Supervised Tier 4 - Monitored Redesign required Redesign required: Open-ended judgment combined with production, financial, physical, legal or safety-critical write authority. The use case must be redesigned into deterministic workflow, reduced authority or human-operated execution. This PALO routing outcome is not a legal finding that a practice is prohibited under the EU AI Act. This PALO routing outcome is not a legal finding that a practice is prohibited under the EU AI Act. 04 ## Six Canonical Phases and the Historical Five-Activity Overlay The current versioned lifecycle has six phases and six gate definitions: Frame, Classify, Assess, Control, Measure and Prove. The five activities below preserve the historical PALO-AM teaching view. They are not five alternative canonical gate identifiers. Use the six-phase registry for case records and interchange. Explanatory correspondence, version 1.0, reviewed 12 October 2026. This is a many-to-many teaching map; it does not replace canonical IDs or authorize a gate decision. | Historical activity | Canonical phases it informs | 1. Ideation and screening | Frame, Classify | 2. Assessment and planning | Classify, Assess, Control | 3. Development and validation | Control, Measure | 4. Deployment and monitoring | Measure, Prove | 5. Improvement and decommissioning | Prove and the next lifecycle iteration Canonical lifecycle registry · Complete taxonomy and dictionary 1 #### Ideation & Agentic Screening "Is an agent actually necessary?" Could a deterministic workflow, conventional automation or human-controlled assistant achieve the same value with lower risk? Historical checkpoint: Proceed only if delegated action is justified and action-space is bounded. 2 #### Assessment & Planning "What authority is being delegated?" Complete Agent Identity Profile, Agent Authority Profile, AI System Impact Assessment, threat model, HITL design and KPI framework. Historical checkpoint: Proceed only if all five objects are documented and residual risk is accepted by the correct governance body. 3 #### Development & Validation "Have structural controls been tested, not merely described?" Tool schema validation, sandbox tests, agentic red-team report, policy-as-code bundle and control test evidence. Historical checkpoint: Proceed only if critical vulnerabilities are closed and approval gates cannot be bypassed. 4 #### Ethical Deployment & Monitoring "Can the organization observe, interrupt and evidence the agent?" Shadow-mode, phased rollout, runtime monitoring dashboard, incident playbook, override telemetry and KPI baseline. Historical checkpoint: Proceed only with phased rollout, active monitoring and an accountable decision to expand authority. 5 #### Continuous Improvement & Decommissioning "Can the agent be retired without leaving hidden authority?" Tradecraft audit, credential revocation log, memory retention/deletion record and decommissioning certificate. Historical checkpoint: Close only after credentials are revoked, logs are archived and manual fallback has been validated. 05 ## KPI / KRI Registry for Agentic AI PALO-AM extends the PALO KPI compendium with indicators specific to delegated action. The goal: measure whether the organization can bound, observe, interrupt, recover from and retire autonomous behavior. CECR on this page means Cascading Error Containment Rate. The simulator also recommends control effectiveness and coverage as a separate measure and now names it without the ambiguous CECR acronym. These narrative measures do not create new entries in the canonical KPI/KRI registry. Versioned terminology and historical correspondence. Scroll horizontally to inspect all registry columns → | Metric | Category | Measurement | Governance Rationale | Phase | Human Override Rate (HOR) | Oversight | Overrides / total action checkpoints | Detects rubber-stamping or unusual intervention patterns. | 4 | Review-Time Distribution (RTD) | Oversight | Median and distribution of review time by action complexity | Flags superficial validation or alert fatigue. | 4 | Automation Bias Index (ABI) | Behavioral | Composite of approval speed, rationale quality, dismissal clustering | Measures whether human oversight remains meaningful. | 4/5 | Tool Call Error Rate (TCER) | Technical | Malformed + hallucinated + unauthorized calls / total calls | Detects semantic misalignment, poor schemas or tool-use drift. | 3/4 | Agent Identity Sprawl Index (AISI) | Security | Unregistered identities / total detected identities | Detects shadow agents, rogue subprocesses or unmanaged credentials. | 4/5 | Multi-Agent Conflict Rate (MACR) | Systemic | Terminated/deadlocked workflows / total multi-agent runs | Detects goal conflict, message loops or coordination failure. | 3/4 | Mean Time to Intervention (MTTI) | Response | Time from anomaly detection to human or automated intervention | Measures whether control is operationally real. | 4 | Cascading Error Containment Rate (CECR) | Systemic | Contained cascade events / total cascade events | Shows whether circuit breakers stop downstream propagation. | 3/4 | Agent Identity Revocation Time (AIRT) | Decommission | Time from decommission trigger to confirmed credential revocation | Validates retirement and shadow-agent prevention. | 5 | Tradecraft Degradation Score (TDS) | Human Agency | Score from manual drills, fallback proficiency and skill-retention audits | Measures human resilience and dependency risk. | 4/5 | Policy Violation Rate per 1k Actions (PVR) | Governance | Violations of authority, data classification or compliance boundaries / 1,000 actions | Signals control design failure or misuse. | 4 No single metric is decisive. Interpret HOR, RTD, ABI and sampled audit results as a pattern, not in isolation. 06 ## Worked Scenarios Concrete examples of PALO-AM applied to real enterprise agent configurations. Each shows the same pattern: define identity, bound authority, score risk, design controls, capture evidence, plan decommissioning. #### Software Engineering Agent Tier 2 initially - Tier 1 if production deployment or protected branch write access is added Inspects repository issues, writes code to non-protected branches, runs tests and opens pull requests. Controls: Restrict write to non-protected branches; deny secret access; require human approval for PR creation; log diffs, tests, tool calls and failed access attempts. A productivity tool becomes a deployment actor if authority expands. The matrix must be recalculated whenever the agent obtains new write or deployment privileges. #### Procurement Vendor Shortlisting Agent Tier 2 (draft only) - Tier 1 if it can send offers or trigger contracts Analyzes supplier proposals, ranks vendors and prepares negotiation questions. Controls: Separate ranking from final decision; audit fairness signals; prohibit direct vendor communication without approval; preserve scoring rationale and conflict-of-interest checks. Agentic procurement raises fairness and accountability risks. The agent should support deliberation, not silently replace governance judgement. #### Finance Payment Recommendation Agent Tier 2 for recommendations - Prohibited for autonomous payment execution Reads invoices, detects anomalies and recommends payment release. Controls: Read-only invoice access; no direct payment execution; dual approval for thresholds; anomaly escalation; strict evidence logging and revocation tests. Payment authority must never be hidden inside model autonomy. Financial execution demands deterministic workflow and human authorization. #### Customer Support Refund Agent Tier 2 - Controlled Retrieves order status, drafts refund recommendations, sends support summaries, requests human approval. Controls: Denied: refund execution above EUR 50; modification of customer master data; access to payment card data. HITL checkpoints for any refund above EUR 50, legal threats, vulnerable-customer flags. Authority scope must be written explicitly. If the profile does not permit it, the orchestration layer must block it regardless of what the model proposes. 07 ## PALO Agentic Interface (PALO-AI) Developer-preview contracts and reference components for exploring governance of autonomous agents and agent teams. Data-Assurance Developer Preview. Not for production authorization. PALO-AI v2.7 adds Action Claim 1.4, Context Bridge evidence references, Data Fitness Decisions, signed Data Disclosure Contracts/Receipts, AI system registry and continuous invalidation to the identity-bound Effect Contract cycle. The reference runtime can demonstrate zero-row egress and mismatch incidents with operator-provisioned in-process connectors and synthetic data, but its strict production profile denies the bundled runtime. Storage-level tenant isolation, KMS/HSM, distributed exactly-once guarantees, high availability and independently assessed non-bypass connectors remain under development. Open the PALO-AI Governance Hub PALO-AI overview Choose an adoption path ### Modality A: Hierarchical Subagents, Prototype Parent-child contract: The preview models identities, authority limits, delegation depth, subagent count and parent metadata. Trusted spawning, lineage verification and evidence handback are not complete. - Identity & Authority checks: Hashes the subagent's prompt and verifies allowed tools. - Reference evidence: The prototype can redact and HMAC-sign records with developer-supplied server-side key material. - Missing production controls: Parent authority, spawning, exactly-once execution and evidence handback require further implementation. & ### Modality B: Collaborative Agent Teams, Specified Proposed P2P Task Claims: This release documents the intended gatekeeper and Shared Task List model; it does not implement a collaborative-team runtime. - Specified: Team Registry, teammate capabilities, Shared Task Claims and team-level evidence. - Not implemented: Peer assignment, task leases, conflict handling, shared sequence state and production human escalation. - Current boundary: The reference runtime evaluates individual Action Claims only. ### Developer Integration Specs Use the schemas, OPA policies, and MCP server tools to connect PALO to your agent workflows: #### JSON Governance Schema Define profiles, policy inputs, Action Claims, Effect Contracts, capabilities, receipts, outcome attestations, incidents and signed evidence with 23 versioned contracts, including the unreleased local Swarm Mandate prototype. Open Schema Action Claim Effect Contract #### Policy-as-Code (Rego) Evaluate draft Rego v1 policy over registered tools, operations, scopes, network targets, delegation and approval metadata. Organization-specific production policy ownership and attestation are not included. Open Policy #### Model Context Protocol Evaluate 50 reference tools over stdio or experimental bearer/OIDC-authenticated MCP Streamable HTTP, including five unreleased swarm tools for mandates, membership, status, revocation and cancellation. Open MCP Spec Capability Matrix 08 ## Standards Alignment PALO-AM is designed as an operational extension that translates global governance standards into PALO-compatible lifecycle phases, templates, matrices, KPIs and evidence gates. #### IMDA MGF v1.5 (2026) Assess upfront, meaningful human accountability, technical controls, end-user responsibility. Matrix + Authority Profile -> Identity Profile + HITL -> Engineering Control Layer -> Tradecraft preservation + training. #### ISO/IEC 42001:2023 AI management system, risk treatment, operational control, monitoring and improvement. Agentic risk treatment plan, authority controls, monitoring dashboard, management review. #### ISO/IEC 42005:2025 AI system impact assessment and documentation of impacts on individuals, groups and society. Agentic AI System Impact Assessment with action-space, autonomy, reversibility and tradecraft sections. #### EU AI Act (2024/1689) Risk classification, prohibited-practice screening, high-risk obligations, post-market monitoring. historical Phase 1 legal screening, historical Phase 2 documentation, historical Phase 4 telemetry, incident and change records. #### NIST AI RMF 1.0 Govern, Map, Measure and Manage AI risks. Govern with object cards; Map with matrix; Measure with KPI/KRI registry; Manage with controls and decommissioning. #### GDPR Purpose limitation, data minimization, access control, retention, deletion or anonymization. Data scope in Authority Profile, memory governance, retention schedule, data deletion/anonymization records. ### Developer preview available v2.7 extends the reference assurance cycle with data-governed Action Claim 1.4, Data Fitness and Disclosure bindings, OIDC tenant checks, disclosure receipts and continuous invalidation. Effect Contract, one-time capability, trusted receipts, authoritative outcome attestation and held incidents remain developer-preview components and are not a production authorization or evidence service. Available 23 versioned contracts and 50 MCP tools, including the unreleased swarm worker prototype, plus full-cycle runtime tests and an n8n governed-action preview. Harden Add durable distributed processing, connector attestation, workload identity, KMS/HSM and policy attestation. Authenticate Add principal identity, role separation and meaningful action context for accountable human approval. Implement Complete collaborative-agent teams, production connectors, mobile delivery and distributed staging assurance. --- ## PALO-AI developer preview Canonical URL: https://paloframework.org/PALO_AIGovernance.html Editorial date: 2026-09-25 v2.7 data-assurance developer preview Internet-reachable evaluation endpoints Governance before, during and after execution # Make agent authority and its real-world effect verifiable. PALO-AI is the technical control-plane component of the PALO Framework. It operationalizes selected PALO-AM controls for n8n and agentic automation platforms by binding explicit authority and policy to a one-time execution capability, a trusted receipt and verification that the action produced the declared effect. Current boundary: this release is for interoperability evaluation with isolated data and non-consequential tools. It is not a production authorization service, certification, or independently assessed security boundary. Why PALO-AI? Open the guided workspace Choose a quickstart Choose your path Read the integration guide Explore full-cycle assurance Agent / workflowAction proposal PALO-AI control path - 01Normalize claim - 02Evaluate policy - 03Approve if required - 04Execute through capability - 05Verify the effect Verified Review required Denied A policy decision is only authoritative when protected execution cannot bypass the governed path. One connected governance journey ## Method, runtime contract, role-based workspace and evidence boundary Orientation: PALO-AM v2.0 remains the June 2026 methodology baseline. PALO-AI v2.7 is the August 2026 data-assurance runtime/contracts Developer Preview. Its production-admission check denies the bundled reference runtime. The Governance Hub uses illustrative/local data and is not a production console. 17 September 2026: the experimental ANS bridge and the unreleased swarm snapshot have separate evidence. Shared budgets, dynamic membership and supported cancellation are demonstrated with one central authority. Review current status and limits. Objective: govern agent actions ## Build mode refines the route. It does not replace accountability. First choose your organizational role in the guided Start. Only then choose how you build. PALO-AI keeps the Action Claim, policy decision, approval and evidence vocabulary consistent across all three implementation modes. 01 / CODE ### Code-first developer Integrate JSON Schema, MCP, OPA/Rego, CI gates and a brokered executor into an application or agent runtime. First move Validate a canonical Action Claim and force one mock tool through the governed path. Use SDK contracts, stdio or remote MCP, Rego tests, gateway adapter. Build my code-first routeRead the guide 02 / VISUAL ### No-code / low-code builder Use the visual decision gate for comparison, then move the protected action into the PALO Governed Action node and verify its outcome. First move Run the synthetic catalog demo and compare verified, mismatched and inconclusive outcomes. Use Local alpha node or native HTTP, Switch and Wait nodes. Build my visual routeRead the guide 03 / RAPID ### Rapid prototyper Connect Copilot Studio or a similar platform to a deliberately narrow set of PALO MCP tools, without writing policy code first. First move Select one authority profile, one reversible action and one accountable reviewer. Use Streamable HTTP MCP, guided profiles and evidence review. Build my rapid routeRead the guide New guided Governance Hub ## One control plane. Two role lenses. No JSON required to start. The same governance state is translated into an executive cockpit and a technical workbench. Leaders see coverage, authority, verified outcomes and exceptions. Builders configure the exact agent, tool, resource, oversight and outcome verifier through an eight-step guided flow. - Executive lensIndependent signals, portfolio exposure, decision queue and assurance reporting. - Technical lensRegistry, policies, executions, approvals, incidents and integrations. - Progressive disclosurePlain language first; generated Action Claims, Effect Contracts and policy inputs remain inspectable. Prototype boundary: this browser interface uses realistic evaluation data. Production multi-user operation still requires an authenticated backend-for-frontend, tenant-aware roles, managed keys and independent security assurance. Launch the white workspace Read the user guide Review the product specification Selected product direction: a guided governance builder that hides implementation complexity until the user asks for it. Portable governance lifecycle ## From intention to verifiable outcome - 01ProposeAn identified agent or workflow requests an action. - 02NormalizeResource, operation, path, host, network intent and arguments become one Action Claim. - 03EvaluateSchema, registry and Rego policy fail closed on malformed or missing context. - 04ApproveWhen required, a reviewer resolves the exact immutable claim. - 05ExecuteThe protected credential or tool is reachable only through the governed path. - 06ReceiptThe trusted executor records what was actually attempted without accepting caller-supplied success claims. - 07ObserveA separately registered verifier retrieves authoritative post-state. - 08Verify effectExpected and forbidden effects resolve to verified, mismatch or inconclusive. - 09EscalateMismatch and uncertainty create a resource hold and a reviewable assurance incident. Deployment choice ## Local remains possible. Cloud becomes a governed service boundary. The contract stays portable; identity, keys, persistence, availability and network trust change by deployment mode. Swipe horizontally to compare every deployment field. | Mode | Best fit | Current availability | Trust boundary | Local sidecar | Code-first development, self-hosted n8n and offline evaluation. | Implemented preview | Keep OPA, registry, ledger and credentials on the trusted host or private container network. | Hybrid | Local/private workflows calling a remote PALO decision service over HTTPS. | Prototype | Workflow data crosses the organization boundary; minimize claims and retain protected execution locally. | Managed cloud | Multi-team governance with central policies, approvals, evidence and operations. | Target architecture | Requires tenant isolation, workload identity, RBAC, KMS/HSM, HA and independent assurance. | Private cloud / VPC | Regulated or enterprise environments needing organizational control and network isolation. | Target architecture | Customer-owned identity, network, keys, retention and operational controls integrate with the PALO service. HTTPS Gateway: developer previewhttps://governance.paloframework.org/gateway Streamable HTTP MCP: developer previewhttps://governance.paloframework.org/mcp Internet-reachable does not mean production-ready. The current VPS adds HTTPS termination and network isolation, but not production workload identity, least-privilege RBAC, managed keys, high availability, distributed exactly-once semantics, attested execution or independent security review. Compare cloud architecturesDeploy the preview VPS stack Integration is not enforcement ## Platform capability matrix A visible check helps people understand a decision. It becomes an authorization boundary only when the protected tool and credential cannot be reached around it. Swipe horizontally to compare enforcement coverage. | Platform | Visual gate | Brokered execution | Runtime interception | Authoritative today? | n8n | Package 0.2 gate or MCP Knowledge Reader | Package 0.2 Governed Action prototype | Not implemented; alternate credentials or tool paths can bypass the node | No. MCP config validated; package unpublished and unverified | Copilot Studio | Reader/Curator over Streamable HTTP | Target via narrow PALO operational tools | Platform-owned controls | No. Config validated; live tenant pending | Dify | Native MCP Knowledge provider | Gateway example or Agent Strategy target | Plugin-owned target | No. Partial config; live build pending | LangChain / LangGraph | Middleware decision feedback | Recommended adapter shape | Before-tool middleware / interrupt | No. Adapter not packaged | Node-RED | Custom node or subflow target | Broker required | Self-hosted hook target | No. Specified pattern | Make | HTTP or custom-app step | PALO-controlled API target | No universal interceptor | No. Direct actions must be removed | Zapier | Private/public integration target | PALO-controlled action target | No universal interceptor | No. Direct actions must be removed Enforcement invariant: do not expose a direct privileged tool path beside its PALO-governed broker and then describe the flow as enforced. Knowledge integrations: the dedicated canonical-only Reader is a production candidate with separate live acceptance gates. Reader/Curator configurations for 11 MCP hosts are tracked in the Knowledge Copilot matrix; protocol or configuration validation is not live host qualification, and the Curator does not inherit Reader status. Assurance before scale ## What is real, and what still blocks production The developer preview includes canonical schemas, a trusted versioned registry, Rego v1 policy evaluation, replay controls, transactional local persistence, signed evidence and official-SDK MCP transports. These are evaluation primitives, not evidence of an independently assured production service. ### Required closure - OIDC or mTLS workload identity and least-privilege tenant RBAC - KMS/HSM-backed signing, rotation and separation of duties - Distributed durability for consumed one-time capabilities, workload identity, connector isolation and removal of alternate privileged execution paths - Durable approval resume, HA state, outbox, recovery and external evidence anchoring - Threat model, independent penetration test, cryptographic review and supply-chain assessment Open Production ReadinessSecurity and scale planCapability matrixDocumentation Library Current publication boundary ## Precisely what this release claims Prototype ### n8n visual decision gate Locally installable alpha package with Allowed, Approval Required and Denied outputs. It does not execute the protected target. Prototype ### Governed executor Package 0.2 binds an Effect Contract to a one-time capability, executes through a registered connector, records a signed receipt and verifies authoritative post-state. Alternate credentials or tool paths can still bypass this preview. Specified ### Secure approval resume Target flow binding authenticated reviewer authority, exact claim digest and one-time workflow continuation. Specified ### Workflow admission Target deployment gate that rejects flows containing bypass paths before activation. Publication status: n8n-nodes-palo-ai is unpublished, unverified and not accepted by n8n. npm publication, catalog discovery, n8n verification and connector submission are deferred until real integration and security gates pass. Architecture preview ## Bring one safe workflow. Challenge the boundary. We are looking for n8n builders, platform integrators, policy authors and security reviewers willing to test a non-production workflow with mock or reversible actions. Do not share secrets, personal data or production credentials. Read the community discussion draftDesign-partner intakeMarket-entry plan --- ## n8n governance guide Canonical URL: https://paloframework.org/docs/palo-ai-n8n-governance-control-plane.html Editorial date: 2026-09-23 Architecture and integration | Public documentation # PALO-AI Governance Control Plane for n8n and Agentic Automation Platforms Explore four PALO-AI integration patterns for n8n: policy gates, governed execution, human approval and workflow admission in a developer preview. By Fabrizio Degni | 2026-09-23 LevelguideAudiencetechnical | builderProductPALO-AIStatusDeveloper PreviewLifecycleCurrentRead8 min Published HTML view | Source: docs/palo-ai-n8n-governance-control-plane.md On this page - Product boundary - Design principles - Four visual integration patterns - Pattern A - Visual Governance Decision Gate - Pattern B - PALO Governed Executor - Pattern C - Digest-Bound Human Approval and Secure Resume - Pattern D - Workflow Admission and Continuous Governance - Reference architecture - n8n adapter contract - Proposed n8n package - Deployment profiles - Developer preview - Enforced self-hosted target - Enterprise/OEM target - Out-of-the-box policy packs - Delivery sequence - Public claim discipline - n8n references Status: current architecture preview updated for the PALO-AI v2.7 data-assurance developer preview on 25 August 2026. The patterns include implemented reference prototypes and future production controls; none is represented as production-ready. PALO-AI is an emerging governance control plane for n8n and agentic automation platforms, designed to make authority, policy enforcement, human oversight and cryptographic evidence visible and enforceable. For runnable setup and current limitations, use the PALO-AI Governance Integration Guide, Full-Cycle Assurance Guide, public Capability Matrix and Production Readiness route. Interface appearance does not determine readiness. ## Product boundary# n8n orchestrates what an automation does. PALO-AI governs whether an identified agent or automation is authorized to propose and execute a specific action, under which policy, with which human oversight, and with which evidence. PALO-AI complements native n8n security, access control, guardrails and human-review features. It does not replace platform hardening, credential security, network controls, legal review or organization-owned accountability. ## Design principles# - One trusted decision point. n8n connectors submit canonical Action Claims to the PALO Gateway; they do not evaluate authoritative policy or sign evidence locally. - Decision is not execution. A visual allow/deny node is advisory unless execution is bound to a short-lived capability or performed by a governed executor. - The exact action is approved. Approval binds to the digest of one immutable claim. Resume never regenerates the claim, arguments, nonce or idempotency material. - Credentials stay with executors. Agents and PALO claims use credential references and redacted arguments, never raw secrets. - Evidence follows outcome. An allowed decision is not evidence of successful execution. The ledger records decision, approval and verified outcome as distinct events. - Fail closed by deployment profile. Missing profiles, malformed claims, unavailable policy and expired capabilities deny execution in enforced profiles. - Portable governance semantics. Platform adapters map vendor-specific workflow data to the same versioned PALO contracts. ## Four visual integration patterns# ### Pattern A - Visual Governance Decision Gate# Enforcement class: advisory prototype unless paired with Pattern B or Pattern D. text code [Proposed Action] -> [PALO Decision Gate] |-- allowed ----------> [Explicit next step] |-- approval required -> [Approval flow] `-- denied -----------> [Stop and alert] The node submits a canonical Action Claim to the trusted PALO Gateway. It exposes distinct decision branches and human-readable reasons. It is valuable for workflow transparency and prototyping, but it can be removed or bypassed by a workflow editor and must not be called an execution interceptor on its own. ### Pattern B - PALO Governed Executor# Enforcement class: implemented reference prototype in v2.7; production hardening and connector certification remain open. text code [AI Agent] -> [PALO Governed Tool] | v [Registry + schema + OPA] | [Approval when required] | v [Allowlisted executor] | v [Outcome evidence] The agent can call only a PALO-governed tool. It supplies a registered executorId and schema-valid arguments. The gateway resolves the executor in the trusted registry, evaluates the immutable claim, obtains approval when required, and performs or delegates the action through an unavoidable execution path. An arbitrary targetTool string is not sufficient. Production executors require a versioned registration, an argument schema, an authority profile, allowed hosts and scopes, credential isolation, timeout and retry semantics, and evidence mapping. ### Pattern C - Digest-Bound Human Approval and Secure Resume# Enforcement class: approval-state prototype; authenticated delivery and resume remain specified. text code [Pending Action] -> [PALO Approval API] -> [PALO Web or Mobile] ^ | | approve / deny | | `---- signed result ----' | [Revalidate immutable claim] | [Secure n8n resume] The mobile client never receives authority to execute a tool and should not call an exposed n8n resume URL directly. It resolves an approval through PALO using authenticated reviewer identity. The PALO backend verifies the reviewer, device/session, claim digest, expiry and terminal state before issuing a one-time resume signal. The same claim is evaluated again immediately before execution. This pattern should integrate with n8n's native human-review and wait semantics rather than duplicate their workflow lifecycle. ### Pattern D - Workflow Admission and Continuous Governance# Enforcement class: specified self-hosted/OEM enforcement pattern. text code [Create or update workflow] | v [PALO Workflow Assessor] | [Coverage + risk + profile] | | complete incomplete | | [versioned digest] [block activation] | [pre-execution verification] The assessor analyzes workflow JSON, agent and tool connections, Code or Execute Command nodes, credential references, external hosts, webhooks, destructive operations, MCP exposure and missing governance coverage. A backend hook can reject activation or execution when the required PALO profile, workflow digest or governed execution path is absent. This is the layer that turns a collection of optional nodes into instance-level governance. ## Reference architecture# Mermaid diagram source flowchart LR A["n8n Canvas / AI Agent"] --> B["PALO Visual Nodes"] A --> C["PALO MCP Governance Proxy"] H["Workflow create, update and activation hooks"] --> D["PALO Workflow Assessor"] D --> E["Versioned workflow profile"] B --> F["Canonical Action Claim"] C --> F E --> G["Registry and OPA policy engine"] F --> G G -->|"deny"| X["Execution blocked"] G -->|"approval required"| I["PALO Web / Mobile approval"] I --> G G -->|"allow + capability"| J["Governed executor"] J --> K["n8n, MCP tool or external API"] J --> L["Signed append-only evidence ledger"] ## n8n adapter contract# Every n8n action should add platform correlation metadata to the canonical PALO Action Claim: - instance and tenant identifier; - project and workflow identifier; - published workflow version and workflow digest; - execution identifier and execution mode; - node identifier, node type and node version; - run index and input item index; - credential reference, never credential material; - registered executor identifier; - tool, operation, resource, normalized path and host; - explicit network intent: none, read, write or bidirectional; - arguments and trusted argument-schema digest; - data classification, reversibility and external-communication indicators where applicable. ## Proposed n8n package# The target community package is n8n-nodes-palo-ai and should contain: - PALO Assess Workflow; - PALO Governance Gate; - PALO Approval; - PALO Governed Action; - PALO Governed MCP Tool; - PALO Evidence; - a dedicated encrypted n8n credential type; - node versioning, icons, lint, unit tests, installation tests and npm provenance; - three reference workflow templates. The community package remains separable from the self-hosted enforcement package, which supplies backend hooks, the MCP proxy and deployment configuration. ## Deployment profiles# ### Developer preview# - n8n; - PALO Gateway and official-SDK MCP server; - OPA; - PALO-owned SQLite volume; - localhost or isolated test network only; - no consequential tools, sensitive data or production credentials. SQLite is never shared with n8n. Mobile biometrics may protect access to the client but do not constitute a cryptographic reviewer signature. The current evidence prototype uses server-side HMAC keys. ### Enforced self-hosted target# - n8n with PALO backend hooks; - PALO Gateway and MCP proxy replicas; - OPA policy bundles with version and provenance; - PostgreSQL transactional state and evidence outbox; - organization-owned KMS/HSM keys; - OAuth/OIDC workload and reviewer identity; - TLS, rate limiting, observability, backup and recovery; - one-time capability consumption and distributed idempotency. ### Enterprise/OEM target# - embedded governance coverage panel and node badges; - SSO, RBAC and separation of administrator, agent, reviewer and auditor roles; - signed policy distribution and environment promotion; - high-availability approval and evidence services; - retention, export, external anchoring and assurance controls. ## Out-of-the-box policy packs# - Observe Only - assessment and evidence with no write authority. - Human Controlled - approval for external communications, writes, deletion and purchases. - Enterprise Baseline - host allowlists, scope restrictions, credential references and separation of duties. - Regulated Data - declared purpose, redaction, approval obligations and retention controls. - Agent Team - roles, delegation depth and subagent constraints have prototype support; durable team task leases, conflict handling and team-level evidence remain specified. - Vibe Coding - gate metadata is prototyped, but an unavoidable proxy for shell, filesystem, Git, deployment and secret access is not implemented. ## Delivery sequence# - Publish this architecture and collect interoperability feedback. - Package the current visual decision gate with credentials, explicit network intent and immutable-claim resume. - Add n8n workflow correlation metadata and distributed connector tests. - Implement workflow assessment and activation/pre-execution hooks. - Implement the governed executor registry and one-time capability consumption. - Integrate authenticated Web/mobile approval and secure resume. - Replace preview storage and identity controls for a distributed staging E2E. - Request n8n community-node verification only after package and provenance requirements are met. ## Public claim discipline# Use: PALO-AI is an emerging visual governance control plane for n8n and similar agentic automation platforms. The v2.7 developer preview adds Authority Context, Data Fitness, disclosure controls and continuous invalidation to governed execution and authoritative outcome verification, while remaining limited to isolated evaluation. Do not yet use: - 'production security boundary'; - 'biometrically signed execution evidence'; - 'exactly-once execution'; - 'certified n8n connector'; - 'the standard' or 'de facto standard'; - 'all n8n tool calls are intercepted' without the enforced deployment profile. ## n8n references# - Creating and deploying community nodes - External hooks - Human-in-the-loop for AI tool calls - Instance-level MCP server - Community-node verification guidelines - Sustainable Use License --- ## PALO MCP services Canonical URL: https://paloframework.org/packages/palo-mcp-server/README.html Editorial date: 2026-09-23 Start and adoption | Public documentation # PALO MCP services Distinguish PALO's canonical-only Knowledge Reader from its operational developer-preview MCP server, including setup and trust boundaries. By Fabrizio Degni | 2026-09-23 LevelreferenceAudiencetechnical | builderProductPALO CoreStatusCurrent GuidanceLifecycleCurrentRead9 min Published HTML view | Source: packages/palo-mcp-server/README.md On this page - Operational PALO-AI reference server - Developer Preview - Safety notice - v2.7 data assurance evolution - v2.6 identity and durability baseline - MCP 2026 and OIDC resource-server mode - Full-cycle reference demo - Vendor-neutral enforcement providers - Local validation This directory now contains two deliberately different boundaries: - reader-http.js + reader-server.js: dedicated PALO Knowledge Reader v1.0.0, stateless and canonical-only, admitted as a production candidate with deployment-specific live qualification pending; - http.js + server.js + core.js: operational PALO-AI v2.7 reference runtime, still a non-production developer preview. The Reader final image does not copy core.js, the curation-capable knowledge class, SQLite, OPA, operational schemas or target credentials. It verifies data/knowledge-reader-release.json before listening, registers exactly six read-only tools and rejects production startup without OIDC and the strict transport boundary. See PALO Knowledge Reader: production profile. ## Operational PALO-AI reference server - Developer Preview# The unreleased swarm execution extension provides five MCP tools for mandate registration, status, member admission, revocation and cancellation. An opt-in dispatcher coordinates remote workers with expiring leases and single-use starts. Cancellation needs a supporting connector and an authoritative observer. Run npm run test:swarm and npm run demo:swarm:distributed from the repository root; production admission remains denied. This package is the non-production reference implementation shipped with PALO-AI v2.7. It uses the split MCP TypeScript SDK 2.0 over stdio and Streamable HTTP, serving the stateless 2026-07-28 protocol and a 2025-era compatibility path from the same tool factory. Remote MCP supports OIDC/JWKS with issuer, audience, expiry, algorithm and scope validation, or an explicit shared-token development mode. The runtime demonstrates data-governed Action Claim 1.4, Data Fitness Decisions, signed Data Disclosure Contracts and Receipts, external context evidence, continuous invalidation, an AI System & Agent Registry, Effect Contract 1.1, one-time capabilities, trusted in-process executors, authoritative outcome verification, evidence signatures, incidents and a hash-chained SQLite ledger. Action Claim 1.1/1.2/1.3 and HMAC Evidence Envelope 1.0 remain supported for compatibility. PALO platform v3.1.0 also exposes twelve applicability-aware governance control packs through the palo_guide_agent prompt and six Knowledge Reader tools. They explain the released PALO semantic model, infer a transparent starting route, plan a least-privilege product integration and search/get provenance-bearing knowledge records without mutating case state. See the PALO Knowledge Copilot integration matrix, PALO Guide Agent and MCP Integration and v3.1 Governance Control Plane. Keep these knowledge tools separate from protected-action authorization and execution. The VPS reference deployment defines a six-tool Reader route at https://governance.paloframework.org/mcp-guide and a ten-tool Curator route at /mcp-guide-curator. Reader production mode is OIDC-only, volume-free and bound to the immutable canonical release. Compatibility aliases add a terminal /mcp for clients that infer the transport from the path. Curator has separate authentication and storage, adds immutable draft and review operations over a knowledge volume and does not modify released repository sources. Both profiles exclude the operational /mcp surface. The server returns profile-specific MCP instructions: search and retrieve before factual PALO claims, cite recordId and sourcePath, treat retrieved content as untrusted data, preserve authority classes and do not claim legal advice, certification, case approval or production authorization. Curator instructions additionally constrain writes to explicit immutable draft/review workflows. Client examples and the machine-readable 11-host matrix are in examples/agentic-interface/knowledge-copilot. Run npm run validate:knowledge-copilot for the static configuration suite, then follow PALO MCP Host Qualification for a real tenant test. No host is live-qualified by repository tests alone. ## Safety notice# Do not use this package to authorize or execute production tools, access sensitive data, or support consequential decisions. It is not an audited security boundary, universal exactly-once executor, production identity service, trusted approval service, compliance certification, or production evidence platform. The following controls are not provided in v2.7: - an authorization server, interactive OAuth login, EMA ID-JAG exchange, proof-of-possession, workload attestation, token issuance or rotation; OIDC mode is the MCP resource-server side of that architecture; - TLS termination, device/session assurance, rate limiting, tenant data isolation, or network perimeter controls; - production policy-bundle signing, distribution, attestation, rollback, or availability; - a distributed transaction spanning external tools; exactly-once claims remain limited to connectors with reliable idempotency semantics; - durable approval and verification tasks are single-instance; job leasing and crash recovery across multiple runtime replicas are not provided; - production attestation of executor and verifier binaries, workloads or supply chains; - KMS/HSM key custody, rotation, revocation, separation of duties, or external ledger anchoring; - complete action context and authenticated reviewer identity outside the OIDC-protected MCP surface; the Gateway and demo routes retain their separately documented preview authentication; - trusted Vibe Gate attestation or an unavoidable pre-tool-call execution proxy; - Mode B Team Registry, Shared Task Claims, peer coordination, leases, conflict handling, or team-level evidence; - monitoring, backup/restore, retention, incident response, penetration testing, or distributed staging validation. The v2.7 runtime retains a strict production profile and fail-closed startup admission check, but the bundled capability attestation deliberately cannot satisfy that profile. This makes the remaining boundary executable instead of aspirational: the SQLite, process-key and in-process connector runtime cannot start with PALO_RUNTIME_MODE=production. Validate a deployment profile independently of runtime compatibility: bash code npm run production:admission -- schemas/fixtures/palo-production-profile.valid.json --schema-only Evaluate it against the bundled reference runtime: bash code npm run production:admission -- schemas/fixtures/palo-production-profile.valid.json The second command is expected to deny the fixture. For runtime startup, set PALO_RUNTIME_MODE=production and PALO_PRODUCTION_PROFILE_PATH to a deployment-specific profile. The bundled server compares the profile with its fixed reference capability declaration and therefore fails closed; a future production host must inject and independently attest a different capability implementation before admission can be possible. OIDC-protected Action Claim 1.3/1.4 processing additionally requires the token tenant to match the authority, Effect Contract and optional metadata tenant values. This request check does not provide tenant-isolated storage. Use only isolated development data and unprivileged mock executors. Read the repository-level capability matrix and integration guide before running the server. ## v2.7 data assurance evolution# Action Claim 1.4 binds the exact claim to an allowed, unexpired, non-invalidated palo-data-fitness-decision and a signed palo-data-disclosure-contract. The runtime revalidates both before policy evaluation and before issuing the one-time execution capability. The trusted executor returns a payload-minimized palo-data-disclosure-observation; PALO compares actual sources, fields, rows, sensitive categories, redactions, recipient, provider, model, region, endpoint, trace mode, retention and export behavior with the contract. The resulting signed palo-data-disclosure-receipt is bound into Execution Receipt 1.1 and the authoritative outcome attestation. A mismatch opens the same high-severity resource hold used for incorrect write effects. Executor result payloads are not persisted for Action Claim 1.4: the runtime stores only their digest and the disclosure receipt. This proves the declared observation boundary; it does not independently attest an in-process connector or make the connector non-bypassable. External context is imported as immutable palo-external-evidence-ref records. They retain source/version/URI, normalized claims, authority and connector provenance plus a source-payload digest, but not the source payload. Fitness decisions bind the evaluated normalized claims and treat conflicting current assertions conservatively. Signed disclosure contracts and observations must remain inside the bound fitness and contract time windows. The included Actian mapper is a read-only normalization profile, not an authenticated Actian SaaS client. Continuous assurance signals invalidate prior allowed fitness decisions and revoke matching capabilities that have not yet been consumed. See PALO Data Assurance Control Plane for contracts, tools, compliance boundaries and the testable Actian vertical slice. ## v2.6 identity and durability baseline# Action Claim 1.3 adds a human principal, workload identity, credential digests, agent instance and contiguous delegation chain. The runtime validates issuer/audience constraints, delegation time windows, non-widening scopes, tenant binding and terminal agent identity before policy evaluation. Configure trust constraints with PALO_IDENTITY_POLICY_JSON and provision an authorityVerifier callback in the runtime host to validate the bound credential digests against authenticated or attested material obtained out of band. Claim 1.3 fails closed when that verifier is absent; declared issuer strings alone never authorize an action. Effect Contract 1.1 adds notExists, numberWithin, containsAll and typeIs, delayed verification, retry metadata and an explicit compensation proposal. Compensation is never executed implicitly: it always requires a new governed Action Claim. Approval and delayed outcome verification are persisted as palo-assurance-task records. Use the task MCP tools or /v1/tasks Gateway endpoints to inspect and process due work. The Gateway polls due work every PALO_TASK_POLL_INTERVAL_MS and prevents overlapping polls inside one process. The MCP transport now supports 2026-07-28 and legacy clients, but these domain records are not yet implemented through the standard MCP Tasks extension or MRTR elicitation, and they have no multi-replica lease. Set PALO_EVIDENCE_ED25519_JSON to an object containing keyId, verificationMethod, privateKey and publicKey to emit Evidence Envelope 2.0. The envelope uses RFC 8785 canonicalization and Ed25519; verifiers must obtain the public key through a trusted channel. Retain rotated verification keys through PALO_EVIDENCE_PUBLIC_KEYS_JSON. Internal execution capabilities, receipts and attestations continue to use the profile HMAC key in this increment. Verify an exported envelope without opening the runtime database: bash code npm run palo:evidence:verify -- evidence-envelope.json trusted-public-key.pem The runtime emits redacted lifecycle events through an optional telemetry sink and exposes an operational snapshot. Set PALO_OTEL_ENABLED=true to translate those events into bounded OpenTelemetry spans correlated by the PALO trace ID. Only allowlisted identifiers and lifecycle fields are emitted. The package installs the OpenTelemetry API, not an SDK, sampler or exporter; the host must register those components. ## MCP 2026 and OIDC resource-server mode# The TypeScript SDK defaults clients to the legacy handshake, so conformance tests explicitly cover both a pinned 2026-07-28 client and legacy 2025 clients. Modern HTTP requests are stateless and the SDK validates the protocol, method and tool-name headers against the body metadata. Shared-token mode remains available for isolated development with PALO_MCP_HTTP_TOKEN. For an externally reachable MCP resource, configure OIDC instead: bash code export PALO_AUTH_MODE='oidc' export PALO_MCP_PUBLIC_URL='https://governance.example.org/mcp' export PALO_OIDC_ISSUER='https://identity.example.org' export PALO_OIDC_AUDIENCE='https://governance.example.org/mcp' export PALO_OIDC_JWKS_URI='https://identity.example.org/.well-known/jwks.json' export PALO_OIDC_ALGORITHMS='RS256 PS256 ES256 EdDSA' export PALO_OIDC_ALLOWED_CLIENT_IDS='approved-mcp-client' export PALO_OIDC_TENANT_CLAIM='tid' export PALO_OIDC_ALLOWED_TENANTS='approved-tenant' Any non-loopback OIDC listener fails closed unless both the client and tenant allowlists contain explicit values. Configure PALO_OIDC_CLIENT_ID_CLAIM and PALO_OIDC_TENANT_CLAIM for the issuer's access-token format. Loopback evaluation may omit the lists, but that compatibility mode must not be exposed remotely. Programmatic callers must pass the same normalized bind host to the listener that was validated when the app was created. Loopback recognition covers IPv4 127/8 plus canonical and expanded IPv6 loopback forms. The resource publishes RFC 9728 protected-resource metadata and sends scope-aware WWW-Authenticate challenges. Direct scopes are palo:guide, palo:knowledge:read, palo:knowledge:write, palo:knowledge:review, palo:read, palo:execute, palo:review, palo:audit and palo:admin; palo:* is reserved for administrators. Role aliases include palo-knowledge-reader, palo-knowledge-curator, palo-agent, palo-reviewer, palo-auditor, palo-observer and palo-admin, each expanding to fixed least-privilege scope sets. tools/list is filtered per authenticated request, and approval, incident or knowledge-review attribution uses the verified OIDC subject/client rather than trusting a supplied identity label. This is compatible with access tokens issued by an EMA-capable authorization server, but PALO does not implement the Enterprise-Managed Authorization ID-JAG exchanges itself. ## Full-cycle reference demo# Start OPA, then run the Gateway with the synthetic catalog adapter: bash code export PALO_OPA_URL='http://127.0.0.1:8181' export PALO_GATEWAY_TOKEN='palo-demo-only-gateway-token-32-bytes' export PALO_HMAC_KEYS_JSON='{"key-catalog-demo":"palo-demo-only-signing-secret-material-32-bytes"}' export PALO_ENABLE_DEMO_CATALOG='true' npm run palo:gateway In another terminal run npm run demo:hands-on -- --auto-approve. Add --wrong-effect to demonstrate an authorized action that produces a mismatched outcome and a held Assurance Incident. On Gateway startup, executing/pending outbox rows older than PALO_EXECUTION_RECOVERY_AGE_MS (30 seconds by default) are recovered fail-closed. The runtime creates a signed unknown receipt, an inconclusive attestation, and a held incident. Rows with a recorded receipt but no attestation resume outcome verification. This protects the reference single-instance lifecycle after interruption; it is not multi-replica leasing or a universal exactly-once guarantee. ## Vendor-neutral enforcement providers# OPA remains the default policy evaluator. The runtime now accepts a versioned palo-agentic-enforcement-provider implementation and records its provider, version, policy reference and optional decision/evidence references in each Policy Decision. The first optional provider maps PALO Action Claims to Microsoft Agent Governance Toolkit ACS pre_tool_call. It is a PALO-maintained interoperability proposal, not a Microsoft-maintained or endorsed integration. The upstream package is loaded only when selected and is not a mandatory PALO dependency. bash code npm install --no-save --package-lock=false agent-control-specification@0.3.1-beta.0 npm run demo:microsoft-agt See the PALO + Microsoft AGT quickstart for the environment configuration, trust boundaries and upgrade policy. ## Local validation# bash code npm ci npm run opa:install npm run validate:agentic Passing the included tests confirms the documented reference behavior only; it does not establish production readiness. --- ## Production readiness Canonical URL: https://paloframework.org/PALO_AIProductionReadiness.html Editorial date: 2026-09-23 Public delivery map | v2.7 developer preview # Nine gates between preview and production 17 September 2026: the experimental ANS bridge and the unreleased swarm snapshot have separate evidence. Shared budgets, dynamic membership and supported cancellation are demonstrated with one central authority. Review current status and limits. The v2.7 production profile keeps the boundary executable: data fitness, disclosure receipts and continuous invalidation are implemented as prototypes, while the bundled SQLite and in-process runtime remains denied for production until identity, tenancy, persistence, keys, connectors, resilience and independent assurance are externally implemented and evidenced. This remains a planning surface - not an authoritative project tracker, certification or release commitment. Why PALO-AI?Open data assuranceReview current capabilityDocumentation Library Conditional estimate Controlled single tenantabout 14-20 weeks Production candidate after the applicable gates and independent retest pass. Managed multi-tenantabout 24-36 weeks Production candidate / GA only after isolation, resilience and assurance evidence. Planning assumption: one dedicated product owner, one platform lead, two backend engineers, one frontend engineer, one DevSecOps engineer and fractional security/cryptography support. Ranges are directional, overlap by design and are not release commitments. Five overlapping waves ## Filter, inspect and export a local planning snapshot Browser-local only: checklist state is saved on this device for planning convenience. It is never submitted and is not evidence of implementation or approval. Wave Status Owner Wave 1 | Weeks 1-4Identity & BFFWave 2 | Weeks 3-8Keys & durable dataWave 3 | Weeks 7-12Connectors & policyWave 4 | Weeks 11-16Tenancy & resilienceWave 5 | Weeks 15-20Independent assurance 01 Wave 1 | Platform | In progress ### Workload identity and scoped authorization Local planning check Replace shared bearer tokens with workload identity, OIDC/OAuth and scoped principal/tenant RBAC. Acceptance criteria - Every machine and human request resolves to a verifiable principal and tenant. - Scopes are deny-by-default and enforced server-side. - Token rotation, revocation and negative authorization tests pass. 02 Wave 1 | Product / Platform | Planned ### Same-origin Governance Hub BFF Local planning check Put the Hub behind a same-origin backend-for-frontend with authenticated executive, reviewer and operator sessions. Acceptance criteria - No browser-held privileged runtime credential. - Role and tenant checks occur on every protected operation. - Session expiry, CSRF and privilege-escalation tests pass. 03 Wave 2 | Security | Planned ### KMS/HSM-backed key custody Local planning check Move secrets and signing keys to managed custody with rotation, revocation and separation of duties. Acceptance criteria - Application processes cannot export signing key material. - Rotation and emergency revocation are rehearsed. - Administrative and signing duties are separated and audited. 04 Wave 2 | Platform | Planned ### Durable, coordinated data plane Local planning check Replace SQLite and in-process recovery with PostgreSQL, a durable queue/outbox, multi-replica coordination, backup and tested restore. Acceptance criteria - Transactional outbox and idempotent consumers survive process loss. - Replica concurrency and lease recovery tests pass. - Encrypted backups meet documented RPO/RTO and restore is demonstrated. 05 Wave 3 | DevSecOps | Planned ### Isolated and attested connectors Local planning check Isolate and attest connector workloads, enforce egress policy and remove alternate privileged execution paths. Acceptance criteria - Protected credentials are available only to the governed connector. - Egress destinations and operations are allowlisted. - Bypass and compromised-connector scenarios are tested. 06 Wave 3 | Security | Planned ### Authenticated policy distribution Local planning check Verify policy and bundle provenance; authenticate distribution and use mTLS where the threat model requires it. Acceptance criteria - Only authorized publishers can promote versioned bundles. - Runtime verifies provenance and rejects stale, unsigned or invalid bundles. - Rollback and emergency policy procedures are audited. 07 Wave 4 | Security / Platform | Planned ### Tenant isolation and operational resilience Local planning check Add tenant-isolation, abuse/rate-limit, audit-retention and disaster-recovery tests. Acceptance criteria - Cross-tenant reads, writes and inference paths are denied under adversarial tests. - Rate limits and abuse controls fail safely. - Retention, deletion and disaster recovery meet approved policy. 08 Wave 4 | Product / Platform | Planned ### Fresh n8n package 0.2 validation Local planning check Validate package 0.2 on fresh supported n8n canvases and real reversible connectors before npm or template submission. Acceptance criteria - Clean installation and upgrade paths pass on declared n8n versions. - Allowed, denied, review, failure and verification branches pass with reversible tools. - Package provenance and documentation are independently reproducible. 09 Wave 5 | Independent assurance | Planned ### Independent cyber and cryptographic assurance Local planning check Commission threat modelling, application/API penetration testing, cryptographic design review and container/supply-chain assessment. Acceptance criteria - Independent reports define scope, methods, severity and reproducible findings. - Critical and high findings are remediated and retested. - Residual risk is explicitly accepted by accountable owners. No gates match these filters. --- ## Publications and evidence ledger Canonical URL: https://paloframework.org/PALO_Recognition.html Editorial date: 2026-09-23 01 / Research ## Research, with provenance intact. The research record includes Fabrizio Degni's doctoral thesis in Computer Science at EIMT, the foundational corporate-governance publication and a later, author-led research extension. The two published studies retain their own publication records below. Research publication · 2026 Il Framework PALO per la Corporate Governance dell’IA Fabrizio Degni Rivista Corporate Governance Numero Straordinario Research publication · Preferred citation ### Il Framework PALO per la Corporate Governance dell'IA: un paradigma per l'orchestrazione del ciclo di vita dell'Intelligenza Artificiale basato su principi in ambito aziendale The foundational journal publication presents PALO as a principle-based paradigm for orchestrating the AI lifecycle in a corporate-governance context. Author Fabrizio Degni Published 4 March 2026 Journal Rivista Corporate Governance Issue Numero Straordinario 2026 Publisher G. Giappichelli Editore Identifiers ISSN 2724-1068 · EISSN 2784-8647 Open the journal issue View issue index Published extension · Downstream research ### Orbital intelligence and the knightian Void: A Graduated Governance Model for Autonomous AI in Cosmic Exploration, Grounded in the P.A.L.O. Framework Political Science International, Volume 4, Issue 1, pages 1–20. Published 22 May 2026. ISSN 2995-326X. The paper develops the Graduated Cosmic Ethics model as an extension of PALO and adds seven cosmic KPIs for autonomous AI in space exploration. Provenance boundary: this extension is authored by Fabrizio Degni. It is published downstream research, not an independent citation of PALO. Open the published paper Primary research artifacts The repository PDFs preserve the PALO v1 research artifact and current framework document. They are primary sources, not additional journal publications. PALO v1 research PDF PALO Framework PDF Doctoral thesis · Computer Science ### THE P.A.L.O. FRAMEWORK Principled AI Lifecycle Orchestration: An Integrated Governance Architecture for Business AI Use Case Evaluation PALO Framework was the subject of Fabrizio Degni's doctoral thesis in Computer Science at the European Institute of Management and Technology (EIMT). Author Fabrizio Degni Field Computer Science Institution European Institute of Management and Technology (EIMT) Submitted to Research and Development Committee of the European Institute of Management and Technology (EIMT) 02 / Projects & GitHub ## Referenced in public work. These records show an explicit integration and an open interoperability proposal. They are evidence of public use or discussion—not proof of endorsement, upstream adoption or certification. Related project · Explicit PALO integration ### PolicyWatcher A separate civic-tech project by the same creator. Its public README aligns the methodology with PALO, locates PolicyWatcher in Deployment & Monitoring / Phase 4, and derives the KPI approach from PALO's ethical KPI paradigm. View GitHub repository Open live project PALO lifecycle Phase 4 Deployment & Monitoring Related project PolicyWatcher Public policy-change signals and ethical KPI alignment Public proposal workflow · select the image to open GitHub Discussion #3647. Community interoperability proposal · Evaluation open ### Microsoft Agent Governance Toolkit discussion The PALO-maintained adapter proposal connects AGT ACS pre-action policy evaluation to PALO downstream outcome assurance. The proposal is public and remains open for evaluation. Not maintained, certified, sponsored or endorsed by Microsoft. Open GitHub discussion Read local proposal 03 / Public record ## Coverage and public provenance. A dated record of programme listings, independent reporting and public references. Each source retains its own editorial responsibility. - 09 Dec 2025 Official programme / public provenance ### Human Economic Forum 2025 The official programme for the event at the Italian Chamber of Deputies lists Fabrizio Degni as creator of PALO. - 25 Mar 2026 Independent coverage ### Rivista AI Coverage of the P.A.L.O. Framework Toolbox 2.0 and its wider AI-governance context. - 17 Apr 2026 Public coverage ### Indie Hackers “Fabrizio Degni Introduces PALO Framework to Advance Responsible AI Governance.” - Public post Public reference ### World AI Council A public LinkedIn post refers to PALO and notes Reuters coverage. This ledger does not present the post as a direct Reuters source. Official PALO extensions & spin-offs ## An authored ecosystem, not independent recognition. - Author-maintained ### PALO-AM Agentic governance modality for delegated action and autonomy. Explore PALO-AM - Developer preview ### PALO-AI Technical control-plane for governance integration. Explore PALO-AI - PALO-owned product ### Framework Toolbox Mobile companion for local-first governance workflows. View the companion app - Research extension ### Graduated Cosmic Ethics Author-led extension in the published orbital-intelligence paper. Read the paper - Ecosystem companion ### PolicyWatcher Separate civic-tech project by the same creator. Open PolicyWatcher App availability: Google Play and App Store. These extensions are PALO-owned or author-maintained and are shown for relationship clarity. 04 / Cite PALO ## Use the preferred citation. Download BibTeX citation | Read citation metadata Preferred citation Degni, Fabrizio. “Il Framework PALO per la Corporate Governance dell'IA: un paradigma per l'orchestrazione del ciclo di vita dell'Intelligenza Artificiale basato su principi in ambito aziendale.” Rivista Corporate Governance, Numero Straordinario 2026, G. Giappichelli Editore, 4 Mar. 2026. ISSN 2724-1068; EISSN 2784-8647. Sources of truth - CITATION.cff - Canonical repository - PALO Framework PDF - Documentation Library - PALO 3.1 and PALO-AI 2.7 release verification record - European Commission AI Act Educational boundary. PALO supports governance and pre-screening. It does not certify compliance or provide legal advice. Review every use against applicable law, sector requirements and deployment context. --- ## Agentic taxonomy and dictionaries Canonical URL: https://paloframework.org/docs/palo-agentic-taxonomy-and-dictionaries.html Editorial date: 2026-10-12 Start and adoption | Public documentation # PALO taxonomy and controlled dictionaries for agentic governance Detailed PALO classifications for lifecycle, authority, delegation, actions, evidence, controls and external policy signals, with exact schema dictionaries. By Fabrizio Degni | 2026-10-12 LevelreferenceAudiencegovernance | technical | builderProductPALO-AIStatusCurrent GuidanceLifecycleCurrentRead25 min Published HTML view | Source: docs/palo-agentic-taxonomy-and-dictionaries.md On this page - Sintesi italiana - Reading the implementation status - Verified inventory - 1.1 What PALO classifies and why - 1.2 Framework layers and their authority - 1.3 The lifecycle taxonomy - 1.4 The five PALO-AM operational objects - 1.5 Action space, autonomy and the exact routing matrix - 1.6 Identity, authority and delegation dictionaries - 1.7 The action and assurance dictionary - 1.8 State vocabularies must remain separate - 1.9 Data and information disclosure taxonomy - 1.10 Controls, indicators and applicability dictionaries - 1.11 Evidence, mappings and versioned meaning - 1.12 A reviewable dictionary entry and maintenance process - 1.13 PolicyWatcher transport and review dictionaries - Sources and accompanying catalogues Subsequent source maintenance: the six-source review of 12 October 2026 updates the live source registry and clarifies two control packs. The catalogue and PDF remain the inspected earlier snapshot. Taxonomy and dictionaries · Ontologies and operational grounding · Searchable technical catalogues · Complete PDF Technical deep dive for the follow-up discussion with the European Commission Fabrizio Degni · PALO Framework · Evidence snapshot 12 October 2026 PALO provides a versioned vocabulary for connecting lifecycle governance, delegated authority, controls, evidence and accountable decisions. Its semantic implementation comprises a released foundation, structured agentic contracts and a draft extension for dependencies and policy impact. These layers have different purposes and maturity. The central contribution is the explicit separation of what a system is, what an agent is authorised to attempt, what actually happened, what evidence supports that account and who accepts the resulting decision. The two sections below explain taxonomy and controlled dictionaries, followed by ontologies and their operational grounding. The accompanying catalogues expose every schema entry and enumeration in the inspected schema set, together with the actual RDF classes, properties and shapes. They make the analysis inspectable beyond the narrative. The scope is semantic design and evidence contracts. PALO-AI remains a developer-preview reference runtime. A coherent vocabulary, a valid record or a passing fixture does not establish legal conformity, deployment admission or operating effectiveness in an adopting organisation. The positive meeting response reported by the author is not used as evidence of institutional endorsement. ### Sintesi italiana# PALO dispone di una base semantica concreta: un registro di concetti e relazioni, definizioni versionate del ciclo di vita, schemi per le evidenze e le decisioni, un’ontologia RDF/OWL e vincoli SHACL. La governance agentica aggiunge contratti operativi per identità, autorità delegata, richieste di azione, approvazioni, capacità esecutive, effetti attesi, ricevute, verifica degli esiti, idoneità dei dati e divulgazione delle informazioni. Il punto da presentare alla Commissione è la continuità tra significato, decisione e prova: una regola di governance è collegata al caso concreto, alla versione applicabile, alle evidenze e all’autorità che decide. Occorre però distinguere ciò che è già rappresentato in OWL da ciò che oggi è formalizzato soprattutto in JSON Schema e nel runtime. L’estensione del grafo dello stack è dichiarata draft e non va presentata come una seconda ontologia già stabilizzata. Le verifiche su questo snapshot hanno confermato 65 schemi leggibili, 61 fixture JSON con esito atteso, 40 corrispondenze su 40 tra file e digest del manifest, una fixture RDF valida e una invalida correttamente respinta. Sono controlli dei contratti acquisiti, non una nuova qualificazione dell’intero runtime. La riconciliazione aggiunge una corrispondenza esplicita fra le cinque attività storiche e le sei fasi canoniche, distingue i due significati precedentemente associati a CECR e uniforma l’esito di routing a “Redesign required”. Tre ulteriori schemi PolicyWatcher completano il corpus. Le proposte di estensione ontologica restano separate dalle modifiche editoriali effettive. ### Reading the implementation status# | Status used here | Meaning | Released foundation | Artifact present in the PALO 3.1 semantic release and, where listed, bound by its manifest. | Executable reference contract | JSON Schema and associated reference code or fixtures exist; deployment effectiveness requires separate evidence. | Draft extension | The artifact explicitly identifies itself as an additive draft or preview. | Documented design | A narrative or UI definition exists, without assuming a corresponding OWL class or runtime guarantee. | Proposed next step | Analysis in this dossier; it has not amended the canonical PALO model. | TBFV | To Be Verified: an assertion requiring additional evidence before stronger use. ### Verified inventory# | Artifact family | Snapshot result | Interpretation | Semantic spine 3.1.0 | 46 nodes, 48 links, 8 node types | A framework and navigation graph, not a count of all domain concepts. | Lifecycle | 6 phase definitions, 6 gate definitions | Frame, Classify, Assess, Control, Measure, Prove. | Control plane | 12 domains, 31 controls, 38 indicators | Tailoring contracts; thresholds and control effectiveness remain contextual. | Mapping registry | 409 atomic mappings | 101 conditional and 308 supporting; no current mapping asserts total coverage. | Core OWL vocabulary | 27 classes, 18 object properties, 18 datatype properties, 163 triples | Lightweight formal vocabulary. | Core SHACL | 12 node shapes, 231 triples | Constraints on selected records and inherited semantic categories. | Stack model 0.1.0 | 25 entity types, 31 relationship types | Draft model reusing 7 foundation entity types. | Stack RDF and SHACL | 18 declared classes, 25 object properties; 4 shapes | New declarations, not 25 additional classes or 31 additional properties. | JSON Schema corpus | 65 schema files; 2,408 schema entries; 204 enum declarations | Entries include objects, branches and definitions; counts are not distinct business concepts. | Verification | 61/61 JSON fixture expectations; 40/40 release item digests | Scoped checks described in Section 2.11. Sources: [P01], [P02], [P03], [P04], [P05], [P06], [P07], [P08], [P09], [P10], [V01]. ### 1.1 What PALO classifies and why# For this deep dive, taxonomy means the organised classification of governance concepts; a controlled dictionary specifies the permitted terms, identifiers, values and intended meanings; an ontology states formal classes and relationships; a schema constrains a record’s structure; and an executable policy evaluates an action against current rules and inputs. These are complementary mechanisms. An allowed value has a defined lexical meaning, but only a valid decision process can give that value authority for a particular action. PALO’s taxonomy is best described as a set of connected facets. The lifecycle answers when governance work occurs. The agentic modality asks who acts, under whose authority, on which resources and with what autonomy. The evidence model asks which assertion is being made, what supports it and how it was evaluated. The stack extension adds technical dependency and policy-change context. No single tree captures all these dimensions without collapsing material distinctions. [P01], [P02], [P10], [P11] The present implementation distributes its dictionaries across JSON registries, JSON Schema enumerations, RDF terms, JSON-LD contexts, source records and UI labels. It does not contain a single reviewed SKOS concept scheme unifying all these terms. A SKOS export is therefore an interoperability proposal, not a description of an existing PALO deliverable. [P01], [P07], [P08], [W01] ### 1.2 Framework layers and their authority# The December 2025 founding document supplies the conceptual roots: fairness/non-discrimination; transparency/explainability; accountability/responsibility; privacy/data governance; safety/robustness; human agency/oversight; and societal/environmental well-being. It evaluates use cases across ethical integrity, technical robustness/safety, business value/feasibility, legal/regulatory conformity and socio-environmental impact. These are normative evaluation dimensions and objectives, not assertions that a system has achieved them. The later semantic spine and agentic contracts turn parts of this conceptual structure into versioned identifiers and evidence requirements. [H01] | Layer | Governance subject | Concrete representation | Boundary | PALO | Lifecycle, ownership, assessment, controls, measurement and proof | Spine, gates, control packs, evidence schemas | Framework definitions do not authorise a deployment. | PALO-AM | Delegated action and human agency | Five operational object cards, authority/action-space matrix, simulator | A routing model is not a legal risk classification. | PALO-AI | Selected checks at the action boundary | Profiles, Action Claims, policy evaluation, approval, capabilities and receipts | Developer preview; deployment admission remains separate. | Stack governance extension | Dependencies from providers and services to systems, controls and cases | Typed dependency graph, RDF vocabulary and impact query | Draft extension; graph impact produces review work. | PolicyWatcher input | Observed changes in external public policies | Source-bound signals and applicability review | A change signal cannot independently decide applicability. This distinction is part of the semantic design, not just product naming. The core ontology explicitly separates RegimeDefinition, GovernanceFrameworkDefinition and EnforcementAdapterDefinition, with pairwise disjointness axioms. However, declaring classes does not automatically classify every UI label or component as an instance of them. [P07], [P10], [P11], [P12] The spine has four evidence/authority classes: canonical-definition, source-backed-context, illustrative-local-preview and human-review-required. The first is authoritative as a PALO definition. None of the four, merely by classification, grants legal authority or changes the state of a case. The authoritative: true flag on canonical definitions must always be read within this scope. [P01], [P02] The public semantic catalog, case workspace and assurance review are three workspaces. “Executive” and “Technical” are presentation lenses, not authenticated identities or access-control roles. Delivery maturity is another axis: the capability matrix distinguishes specified, prototype, implemented and production-ready. These values must not be merged with evidence authority or legal status. [P01], [P02], [P13] ### 1.3 The lifecycle taxonomy# | Canonical phase and gate | Main question | Typical output | Agentic interpretation | Frame | What problem, purpose, population and accountable owner define the case? | Use-case brief | Justify delegated action and identify alternatives with less authority. | Classify | Which route and scrutiny apply? | Risk route | Classify action space, autonomy, data sensitivity and relevant obligations. | Assess | Which impacts and failure modes matter? | Impact assessment | Evaluate authority misuse, tool errors, delegation, human oversight and downstream effects. | Control | Which owned safeguards address the findings? | Control plan | Define allow-lists, policy checks, approval conditions, effect contracts and safe states. | Measure | How will performance and exposure be observed? | KPI/KRI register | Measure errors, interventions, drift, disclosure, unresolved outcomes and control performance. | Prove | What evidence supports the decision and next review? | Evidence bundle and gate decision | Reconstruct authority, execution, observation, exceptions and accountable acceptance. Gate definitions list proceed, proceed-with-conditions, hold, redesign and stop. The Gate Decision Record additionally permits unresolved, preserving the difference between a concluded routing choice and a recorded undecided state. A conditional decision requires conditions; decisions after sequence 1 require the preceding decision identifier and digest. [P03], [P14] The PALO-AM page also retains a five-phase historical presentation: ideation and screening; assessment and planning; development and validation; ethical deployment and monitoring; continuous improvement and decommissioning. This is not the same list as the canonical six-phase lifecycle. The editorial glossary and agentic page publish the following explanatory correspondence: historical phase 1 mainly informs Frame/Classify; phase 2 informs Classify/Assess/Control; phase 3 informs Control/Measure; phase 4 informs Measure/Prove; phase 5 informs Prove and the next cycle. That correspondence is a versioned interpretation for readers, not a one-to-one migration mapping or an executable gate rule. [P35] Canonical identifiers should remain the six current phases. [P03], [P11] ### 1.4 The five PALO-AM operational objects# Agent Identity Profile describes the agent and its provenance, owner and operating context. The narrative includes credential lifecycle, topology, clearance and revocation. The concrete Agent Profile schema represents agentId, profileVersion, role, lineage, base model and systemPromptHash, with optional temperature. Status can be active, suspended or retired. A prompt hash binds bytes; it does not prove that the model followed the prompt or retained all conversational requirements. [P11], [P15] Agent Authority Profile describes permitted activity. The schema supplies tool allow-lists, operation types, read/write scopes, external-network permission, optional host constraints, argument schemas and a Vibe Gate requirement. Identity and authority coexist in the Agent Profile but remain conceptually distinct. A recognised agent is not automatically authorised to use every tool. [P15] Agentic Risk Matrix routes a configuration using action-space impact and autonomy, modified by reversibility, sensitivity and potential impact. Narrative considerations additionally include third-party dependency, speed/volume and multi-agent complexity. Those additional considerations are not independent inputs to the inspected five-field simulator. [P11], [P16] Agentic Control Layer describes the technical and organisational controls surrounding model proposals: policy evaluation, tool schemas, scoped credentials, approval checkpoints, observability, circuit breakers and change management. The presence of a control in this taxonomy is a governance expectation. Whether it is implemented and non-bypassable must be established for the actual connector and deployment. [P11], [P12] Agentic Evidence Layer records proposals, tool calls, structured inputs/outputs, policy decisions, approvals, incidents, measures and retirement evidence. It does not require disclosure of a model’s private chain of thought. The object cards are useful operational domains; they are not five correspondingly named OWL classes in the core vocabulary. [P07], [P11] ### 1.5 Action space, autonomy and the exact routing matrix# | Facet | Controlled values in the simulator | Meaning | Action space | read, internal, cross-system, critical | Read only; internal write; cross-system action; financial, safety, legal or physical action. | Autonomy | supervised, low, medium, high | Human executes; agent proposes and human approves; agent acts within bounded rules; agent selects and executes independently. | Reversibility | reversible, partial, irreversible | Fully reversible; partially reversible; irreversible or hard to remedy. | Data sensitivity | public, internal, sensitive, restricted | Public/synthetic; internal; personal/commercially sensitive; special-category, secret or highly restricted. | Potential impact | low, moderate, high, severe | Localised through consequential rights, safety, livelihood or systemic impact. The implemented base matrix is reproduced below. Lower numbered positive tiers demand stronger controls. 0 means redesign required in the simulator. [P16] | Autonomy | Read | Internal write | Cross-system | Critical | Supervised | 4 | 4 | 3 | 3 | Low | 3 | 3 | 2 | 2 | Medium | 3 | 2 | 1 | 1 | High | 2 | 1 | 1 | 0 Tier 1 is “Maximum controls”; Tier 2 “Controlled”; Tier 3 “Supervised”; Tier 4 “Monitored”. If at least one of irreversible action, restricted data or severe impact is present, a positive base tier is escalated by one tier only, with a floor of Tier 1. The three escalation triggers do not accumulate into three tier changes. High autonomy plus critical action remains 0. Partial reversibility changes recommended controls/evidence but does not itself trigger the tier escalation. These details matter if a third party reimplements the taxonomy. [P16] The reconciled static matrix and simulator both label the high-autonomy/critical combination “Redesign required”. The former static label “PROHIBITED” is retained only as a deprecated display alias in the editorial glossary. This is a PALO design rule and must not be equated with a prohibited practice under the EU AI Act. [P35] A legal classification would require a separate source-specific analysis. “Supervised” also appears both as an autonomy input and a tier label; these are different fields and should be qualified when exported. [P11], [P16] ### 1.6 Identity, authority and delegation dictionaries# The Agent Profile permits six operation values: read, create, update, delete, execute, delegate. Action Claims use the same operation vocabulary, while network intent is separately classified as none, read, write or bidirectional. An operation token is intentionally broad. The exact tool, resource, canonical path and argument schema determine what the action actually means. [P15], [P17] Delegation uses a maximum depth, maximum subagent count, permitted subagent roles and a human-validation requirement. The profile schema allows a depth from 0 to 20 and a maximum subagent count from 0 to 1,000. These are schema bounds, not recommended safe operating settings. An adopting organisation must choose substantially narrower limits where appropriate and test enforcement. [P15] Action Claim authority context distinguishes the human principal, agent identity, workload identity, delegation chain and tenant. Workload proof types include mtls, dpop, http-message-signature and spiffe-svid; the enumeration lists accepted representation categories and does not establish universal interoperability with every implementation of those technologies. ANS integration is upstream identity/status evidence and does not itself establish permission, data fitness or successful effect. [P17], [P18] The swarm mandate extends the scope to a named owner, objective, coordinator, members, tenant/case, validity interval, budget and concurrency limit. Budget rules bind tool, operation, resource and path; the prototype’s narrative requires one unambiguous matching rule, a non-negative integer charge and a per-action maximum. Membership changes carry an expected membership digest and reason. A natural-language objective records an accountable intention; it is not a machine proof of goal alignment. [P19] This yields a useful delegation taxonomy: principal versus agent versus workload; profile versus one-action authority; parent versus descendant; individual limit versus shared exposure; permission revocation versus confirmed interruption. Revoking future authority must not be described as undoing an action already executed or proving cancellation of an in-flight external effect. [P18], [P19] ### 1.7 The action and assurance dictionary# | Term | Concrete meaning and key binding | Common misinterpretation to avoid | Agent Profile | Versioned identity, authority, delegation and evidence configuration | A profile is not a permit for a particular action. | Action Claim | A specific proposed action bound to agent, case, arguments, scopes, time, replay controls and, for newer versions, authority/effect/data contracts | A proposal does not establish permission. | Policy Decision | allowed, denied or pending_approval, with reasons, versions and claim digest | allowed does not mean executed or compliant. | Approval | Human decision concerning the exact claim digest and an expiry | Approval of changed arguments is a different decision. | Execution Capability | Short-lived, single-use reference authority bound to claim, decision, executor, verifier and target | It is distinct from an architectural capability in the stack graph. | Effect Contract | Resource selector, preconditions, expected and forbidden effects, verification and recovery policy | It verifies declared predicates, not every unstated expectation. | Execution Receipt | Signed reference record of execution status and request/result/pre-state digests | succeeded does not prove the intended business outcome. | Outcome Attestation | Verifier result against the effect contract and observed state | verified is scoped to these predicates and evidence. | Assurance Incident | Record connecting an adverse or unresolved assurance result to response/review | It is not automatically a legally reportable serious incident. | Compensating action | A new action proposed to address a previous effect | It needs its own authority cycle and is not a magical rollback. The reference sequence is Propose → Authorize → Approve when required → Capability → Execute → Receipt → Observe → Verify → Escalate when required. This is a governance/assurance sequence, not a replacement for the six lifecycle phases. Approval is conditional; it should not be depicted as necessarily occurring in every action. [P12], [P17], [P20] Action Claim versions 1.1.0 through 1.4.0 are represented in the schema. Version-specific conditions matter: 1.3 introduces the identity-bound authority context; 1.4 additionally binds the Data Fitness Decision and Disclosure Contract by identifier and digest, subject and purpose. An integration must evaluate the actual schema branch rather than treating schemaVersion as decorative metadata. [P17], [P21] ### 1.8 State vocabularies must remain separate# | Record or field | Exact values in the inspected contracts | Profile status | active, suspended, retired | Policy decision status | allowed, denied, pending_approval | Approval status | pending, approved, denied, expired, cancelled | Execution capability status | issued, consumed, expired, revoked | Execution receipt status | succeeded, failed, unknown | Outcome attestation status | verified, mismatch, inconclusive | Predicate check | pass, fail, unknown | Data fitness decision | allowed, denied, review_required | Disclosure contract | active, revoked | Disclosure receipt | verified, mismatch, inconclusive | Evidence claim | asserted, under-review, accepted, rejected, superseded | Evidence evaluation | sufficient, partial, insufficient, unverified | Mapping approval | draft, in-review, approved, rejected, superseded | Mapping coverage | total, partial, conditional, supporting | Gate decision outcome | proceed, proceed-with-conditions, hold, redesign, stop, unresolved These values are not interchangeable booleans. An approved mapping is a publication/review assertion; an approved action is a particular human approval; an accepted evidence claim has still a distinct evaluation record. Likewise, unknown, unverified, inconclusive and unresolved preserve different kinds of missing knowledge. The catalogue keeps each enum attached to its schema and field path instead of deduplicating words that only look similar. [P14], [P17], [P20], [P21], [P22], [P23], [C01] A notable implementation detail is the effect evaluator’s aggregate precedence: a check with unknown makes the aggregate inconclusive before the code considers failing checks. Therefore a record may contain both a failed predicate and an inconclusive aggregate. Consumers must retain and inspect per-predicate results rather than hiding an observed failure behind the aggregate label. This is an observation of the inspected reference code, not a proposed alteration. [P24] ### 1.9 Data and information disclosure taxonomy# The data-assurance contracts classify the governed subject as dataset, data-product, model, ai-system, agent, tool, access-entitlement or other. They connect the subject and tenant to a purpose, source references, quality and lineage assertions, access state, source authority, approval, freshness and incident context. External metadata is evidence to be evaluated; importing it does not independently attest its truth. [P21], [P25] Data fitness means suitability for a stated use under a particular policy and current evidence. The reference evaluator supports quality thresholds, age limits, source authority, ownership/approval, lineage, access, incidents, prohibited classifications and permitted purposes. Missing evidence has explicit deny/review handling. Conflicting current evidence is evaluated conservatively rather than selecting the most favourable assertion. This remains a rule-based fitness decision, not a universal numerical quality score. [P21] Disclosure is separately governed because appropriate access does not imply appropriate transmission. The Disclosure Contract classifies egress as zero-row, aggregated or row-level; trace modes as disabled, metadata-only or redacted-payload; and binds fields, row limits, redactions, destinations, provider/model/region/host, retention, export and output schema. Aggregation does not automatically establish anonymity. [P21], [P25] The lawful-basis field permits consent, contract, legal-obligation, vital-interests, public-task, legitimate-interests, not-applicable and pending-review. These tokens record a classification supplied to the governance process. They do not determine whether a basis is legally available. The documented active-contract rule excludes pending-review and requires an approver; that runtime condition is stronger than simply observing that the string exists in a schema enum. [P21], [P25] An observation records actual fields/rows read and disclosed, sensitive categories, redactions, destination, trace behaviour and digests. The Disclosure Receipt compares that observation with the contract. Missing trustworthy observation remains inconclusive. Because the reference executor and signing material share an in-process boundary, its signed observation is not independent proof that all external network activity was observed. [P21] ### 1.10 Controls, indicators and applicability dictionaries# The 12 governance-control domains are fairness and subgroup testing; system cards and explanations; notice, appeal, review and remedy; Article 50 transparency; data lifecycle; GPAI and systemic risk; serious incidents and decommissioning; accessibility; environmental performance; AI-literacy effectiveness; ISO/IEC 42001 AIMS overlay; and PALO-AI production boundary. Each domain names its objective, applicability questions, controls, indicators, gates, evidence contracts, completion criteria, stop conditions and residual boundary. [P04] The control library classifies controls as directive, preventive, detective or corrective. It includes purpose boundaries, provenance, meaningful review, supplier due diligence, adversarial testing, incident response, material change gates, decision traceability and agentic authority, alongside the domain-specific additions. “Not applicable” must be supported by a reasoned accountable decision; omission is not an applicability outcome. [P04], [P05] The 38 registered KPI/KRI definitions carry formula, cadence, direction, thresholds, linked controls/gates/sources and caveats. Their source explicitly labels thresholds as illustrative. A metric can indicate documentation coverage while saying little about substantive correctness. For example, provenance coverage does not establish permission or fitness, and completed reviews do not establish that reviewers had enough time or independence. [P06] The agentic page adds 11 named indicators: HOR, RTD, ABI, TCER, AISI, MACR, MTTI, CECR, AIRT, TDS and PVR. These are not 11 automatically additional canonical registry entries: some overlap with registry concepts, and others remain narrative definitions. ABI and TDS lack a fully specified numerical protocol in that page. The earlier CECR collision is resolved in the editorial glossary: palo-am:cascading-error-containment-rate retains CECR, while palo-am:simulator-control-effectiveness-coverage names the separate simulator recommendation without that abbreviation. The latter still needs a numerical protocol before it can be treated as an operational metric. The glossary does not add either concept to the canonical KPI/KRI registry. [P35] [P11], [P16] Oversight and bias crosswalks in the briefing are separate research artefacts. Their relationship to the core should be expressed as versioned, source-scoped mappings, retaining draft-source status, clause interpretation and reviewer responsibility. They should not be counted among the 409 core mappings merely because they also use the word crosswalk. Private draft source documents are not required for the public dictionary export. [P26] ### 1.11 Evidence, mappings and versioned meaning# The atomic evidence model distinguishes an artifact, an evidence claim, an evaluation and a bundle manifest. The artifact identifies content and provenance. The claim states a falsifiable assertion about one target in one case scope. The evaluation records the reviewer, assessment-run context, outcome, rationale and quality dimensions. The bundle composes digest-bound records. This prevents a document’s presence from being mistaken for successful evaluation of the proposition it is meant to support. [P22], [P23], [P27] Evidence Evaluation quality values separately cover relevance, integrity, recency and independence, each in the range 0–1. The schema bounds the values but does not supply a universally valid scoring method. A consumer should preserve the method and rationale and avoid treating a mean of four values as proof of assurance. [P23] Each core mapping is atomic: one source version, one target version, mapping type, coverage, conditions, rationale, basis, approval and provenance. The 409 records comprise 101 control-to-gate, 55 control-to-indicator, 72 control-to-source, 11 gate-to-source, 106 indicator-to-gate and 64 indicator-to-source relationships. Every control-to-gate record is conditional; all other current records are supporting. Although the schema permits total and partial, those values do not occur in this inspected registry. [P09] These mapping counts measure authored relationships, not coverage of 409 legal obligations. The mapped source version is a PALO registry reference, not a statement that every clause of an external standard is represented. A mapping’s approved publication state must not be transformed into a conformity assertion. [P09], [P28] ### 1.12 A reviewable dictionary entry and maintenance process# For an interoperable exchange, a dictionary entry should contain a stable concept IRI, preferred label, definition, scope note, aliases/acronyms, broader/related concepts, schema and field paths, allowed values, version, status, owner/reviewer, provenance and change history. Language labels should use explicit tags. Semantic identity should remain stable across translation; an English label and its Italian translation are not different control concepts. PALO already supplies substantial ingredients, especially identifiers, versions, source references, authority boundaries, schemas and mappings. The accompanying extraction preserves these machine-level facts. Additional bilingual definitions, ownership and synonym resolution are a proposed curated layer, not fields assumed to be populated in every existing artifact. [P01], [P02], [C01] The maintenance sequence should be: propose term; identify existing meanings; choose reuse or a new identifier; attach source and scope; review consequences for schemas, policies and user interfaces; test representative and adversarial records; approve a version; publish a digest-bound release; preserve old identifiers or explicit migration. Major meaning or cardinality changes require the existing change-impact and migration process. A wording clarification should not silently change what actions a policy permits. [P28], [P29] ### 1.13 PolicyWatcher transport and review dictionaries# Three additional JSON contracts make external-policy signals more precise. They complement the individual PolicyWatcher signal contract and the draft dependency graph; none grants policy applicability or action authority. [P34] | Contract | Exact controlled vocabulary and bindings | Governance interpretation | Signal Batch | mode = complete-active-snapshot; locale = en or it; count and limit up to 25; hasMore, nullable nextCursor, individual signal schema reference | A page is one part of a snapshot. Completeness cannot be inferred from the first page or a successful HTTP response. | Operational Signal Registry | Transport state: not-synchronized, healthy, degraded, unavailable; complete-traversal and stale flags; last attempted and successful sync; collection and signal digests; active and revoked entries | Transport health, freshness and signal status remain separate. A valid or accepted import is not an accepted governance finding. | Browser-local Review Ledger | localOnly = true; source-registry and signal digests; transport status active or revoked; review state pending-human-review, in-review, routed-to-case-file, reviewed-no-action, rejected | A local review state records triage. Routing to a Case File is not a signed gate decision or a production approval. The registry separately names error codes network-error, http-error, schema-error, response-too-large, pagination-error and capacity-exceeded. Those classifications preserve the reason a snapshot cannot be relied on as complete. Registry statistics count received, accepted, rejected, changed, active and revoked signals; the schema fields must accompany the number, because “accepted” here describes the import process. The review ledger binds an assessment to the imported signal digest and source-registry digest. If the transport later reports revocation or a different digest, the prior local review must remain attributable to the version actually seen. The JSON contract supplies those bindings; an adopting implementation must enforce reconciliation, reviewer identity and persistence. Browser-local data must not be represented as an organisation-wide authoritative review log. The complete schema catalogue now includes the union of the inspected agentic and semantic contracts, these three transport/review schemas, and three explicitly draft or local extension schemas. Equal counts in two repositories do not imply identical memberships. The published field dictionary therefore includes the schema filename, path and constraints for every entry rather than presenting an undifferentiated list of terms. ## Sources and accompanying catalogues# PALO artifact links resolve to public source locations where available. The research snapshot and validation records preserve the inspected bytes. Linked living pages may subsequently change. - [P01] PALO semantic foundation. - [H01] Fabrizio Degni, The PALO Framework A Paradigm for Principled AI Lifecycle Orchestration in Business, December 2025, 67-page local founding document under framework/. Core principles: pp. 13–15; five-phase lifecycle: pp. 18–22; evaluation dimensions: pp. 22–23. Page numbers refer to the PDF page sequence. Extract retained in the research record. - [P02] Semantic spine. - [P03] Lifecycle definitions. - [P04] Governance control packs. - [P05] Control library. - [P06] KPI and KRI registry. - [P07] Core ontology. - [P08] Core SHACL profile. - [P09] Semantic mappings. - [P10] Stack and policy impact graph and stack model. - [P11] PALO-AM operational model. - [P12] Full-cycle assurance. - [P13] Agentic capability matrix. - [P14] Gate Decision Record schema. - [P15] Agent Profile schema. - [P16] PALO-AM simulator source. - [P17] Action Claim schema. - [P18] ANS integration. - [P19] Swarm prototype, distributed extension and mandate schema. - [P20] Effect Contract, Execution Capability, Execution Receipt, Outcome Attestation, Policy Decision, Approval. - [P21] Data assurance control plane. - [P22] Evidence Claim schema. - [P23] Evidence Evaluation schema. - [P24] Inspected local source packages/palo-mcp-server/core.js, preserved with digest in the research snapshot; public project PALOframework. Local working-tree code is not assumed to equal the published Git HEAD. - [P25] Disclosure Contract, Disclosure Observation, Disclosure Receipt, Data Fitness Decision. - [P26] Oversight crosswalk and bias crosswalk. - [P27] Evidence Artifact and Evidence Bundle Manifest. - [P28] Semantic Release Manifest and pinned public release generator. - [P29] Semantic change-impact register. - [P30] Stack ontology, stack SHACL, stack JSON-LD context and core JSON-LD context. - [P31] Pinned public semantic validator. - [P32] Semantic invariants. - [P33] Evidence-envelope schema and pinned assurance foundation implementation. - [P34] PolicyWatcher Signal Batch, Operational Signal Registry and Browser-local Review Ledger. Acquired from Git commit 42d17508ddc836ae37076d9320cbbc672ea268cc. - [P35] Agentic editorial glossary and historical lifecycle correspondence, version 1.0.0. Separate from the canonical ontology and KPI/KRI registry. - [P36] Semantic publication inventory. This records the editorial release; deployment evidence is a separate receipt. - [W01] W3C SKOS vocabulary. - [W02] W3C OWL 2 Primer. - [W03] W3C SHACL Recommendation. - [W04] W3C PROV-O. - [W05] W3C ODRL Information Model. - [W06] Data Privacy Vocabulary. DPV 2.3 identifies itself as a Final Community Group Report and explicitly states that it is not a W3C Standard or on the W3C Standards Track. - [W07] W3C DCAT 3. - [W08] W3C JSON-LD 1.1. - [C01] Schema index, field dictionary JSON, field dictionary CSV and controlled values. - [C02] RDF inventory and searchable catalogue. - [V01] Snapshot verification results and source inventory. The reproducible audit script and complete acquired source snapshot are retained in the local review package. Verification date: 12 October 2026. --- ## Agentic ontologies and verification Canonical URL: https://paloframework.org/docs/palo-agentic-ontologies.html Editorial date: 2026-10-12 Start and adoption | Public documentation # PALO ontologies and their operational grounding for agentic governance PALO RDF and OWL classes, SHACL constraints, draft stack relationships and their connection to reference execution contracts and verification. By Fabrizio Degni | 2026-10-12 LevelreferenceAudiencegovernance | technical | builderProductPALO-AIStatusCurrent GuidanceLifecycleCurrentRead27 min Published HTML view | Source: docs/palo-agentic-ontologies.md On this page - Sintesi italiana - Reading the implementation status - Verified inventory - 2.1 Architecture from concepts to action records - 2.2 The complete core class taxonomy - 2.3 Core relationships and cardinalities - 2.4 What the core SHACL profile actually checks - 2.5 Definition, case, evidence and decision as different objects - 2.6 The draft stack ontology and the 31 typed relations - 2.7 Time, knowledge and policy-impact queries - 2.8 Where agentic semantics are operational today - 2.9 Worked example connecting taxonomy, ontology and execution - 2.10 Competency questions and interoperability - 2.11 Reproducible verification and what it establishes - 2.12 Gaps, ambiguity and a bounded next extension - 2.13 Additional insights from GLM and their evidence review - 2.14 Publication provenance and maintenance - Sources and accompanying catalogues Taxonomy and dictionaries · Ontologies and operational grounding · Searchable technical catalogues · Complete PDF Technical deep dive for the follow-up discussion with the European Commission Fabrizio Degni · PALO Framework · Evidence snapshot 12 October 2026 PALO provides a versioned vocabulary for connecting lifecycle governance, delegated authority, controls, evidence and accountable decisions. Its semantic implementation comprises a released foundation, structured agentic contracts and a draft extension for dependencies and policy impact. These layers have different purposes and maturity. The central contribution is the explicit separation of what a system is, what an agent is authorised to attempt, what actually happened, what evidence supports that account and who accepts the resulting decision. The two sections below explain taxonomy and controlled dictionaries, followed by ontologies and their operational grounding. The accompanying catalogues expose every schema entry and enumeration in the inspected schema set, together with the actual RDF classes, properties and shapes. They make the analysis inspectable beyond the narrative. The scope is semantic design and evidence contracts. PALO-AI remains a developer-preview reference runtime. A coherent vocabulary, a valid record or a passing fixture does not establish legal conformity, deployment admission or operating effectiveness in an adopting organisation. The positive meeting response reported by the author is not used as evidence of institutional endorsement. ### Sintesi italiana# PALO dispone di una base semantica concreta: un registro di concetti e relazioni, definizioni versionate del ciclo di vita, schemi per le evidenze e le decisioni, un’ontologia RDF/OWL e vincoli SHACL. La governance agentica aggiunge contratti operativi per identità, autorità delegata, richieste di azione, approvazioni, capacità esecutive, effetti attesi, ricevute, verifica degli esiti, idoneità dei dati e divulgazione delle informazioni. Il punto da presentare alla Commissione è la continuità tra significato, decisione e prova: una regola di governance è collegata al caso concreto, alla versione applicabile, alle evidenze e all’autorità che decide. Occorre però distinguere ciò che è già rappresentato in OWL da ciò che oggi è formalizzato soprattutto in JSON Schema e nel runtime. L’estensione del grafo dello stack è dichiarata draft e non va presentata come una seconda ontologia già stabilizzata. Le verifiche su questo snapshot hanno confermato 65 schemi leggibili, 61 fixture JSON con esito atteso, 40 corrispondenze su 40 tra file e digest del manifest, una fixture RDF valida e una invalida correttamente respinta. Sono controlli dei contratti acquisiti, non una nuova qualificazione dell’intero runtime. La riconciliazione aggiunge una corrispondenza esplicita fra le cinque attività storiche e le sei fasi canoniche, distingue i due significati precedentemente associati a CECR e uniforma l’esito di routing a “Redesign required”. Tre ulteriori schemi PolicyWatcher completano il corpus. Le proposte di estensione ontologica restano separate dalle modifiche editoriali effettive. ### Reading the implementation status# | Status used here | Meaning | Released foundation | Artifact present in the PALO 3.1 semantic release and, where listed, bound by its manifest. | Executable reference contract | JSON Schema and associated reference code or fixtures exist; deployment effectiveness requires separate evidence. | Draft extension | The artifact explicitly identifies itself as an additive draft or preview. | Documented design | A narrative or UI definition exists, without assuming a corresponding OWL class or runtime guarantee. | Proposed next step | Analysis in this dossier; it has not amended the canonical PALO model. | TBFV | To Be Verified: an assertion requiring additional evidence before stronger use. ### Verified inventory# | Artifact family | Snapshot result | Interpretation | Semantic spine 3.1.0 | 46 nodes, 48 links, 8 node types | A framework and navigation graph, not a count of all domain concepts. | Lifecycle | 6 phase definitions, 6 gate definitions | Frame, Classify, Assess, Control, Measure, Prove. | Control plane | 12 domains, 31 controls, 38 indicators | Tailoring contracts; thresholds and control effectiveness remain contextual. | Mapping registry | 409 atomic mappings | 101 conditional and 308 supporting; no current mapping asserts total coverage. | Core OWL vocabulary | 27 classes, 18 object properties, 18 datatype properties, 163 triples | Lightweight formal vocabulary. | Core SHACL | 12 node shapes, 231 triples | Constraints on selected records and inherited semantic categories. | Stack model 0.1.0 | 25 entity types, 31 relationship types | Draft model reusing 7 foundation entity types. | Stack RDF and SHACL | 18 declared classes, 25 object properties; 4 shapes | New declarations, not 25 additional classes or 31 additional properties. | JSON Schema corpus | 65 schema files; 2,408 schema entries; 204 enum declarations | Entries include objects, branches and definitions; counts are not distinct business concepts. | Verification | 61/61 JSON fixture expectations; 40/40 release item digests | Scoped checks described in Section 2.11. Sources: [P01], [P02], [P03], [P04], [P05], [P06], [P07], [P08], [P09], [P10], [V01]. ### 2.1 Architecture from concepts to action records# PALO’s semantic architecture has four cooperating layers. The semantic spine and lifecycle registries organise framework meaning. The core ontology supplies a vocabulary for definitions, runtime records, immutable records, decisions, evidence, mappings and release identity. JSON Schema supplies richer record contracts, including many agentic objects not declared in the core OWL file. Reference code then evaluates temporal, cryptographic, policy and state-transition conditions that a static ontology alone cannot enforce. [P01], [P07], [P08], [P17], [P24] The draft stack ontology extends the vocabulary to agents, tools, models, providers, services, policy versions and applicability assessments. Its JSON graph model supplies typed edge rules and operational query context. RDF and JSON contracts must therefore be described together. Saying “PALO has an ontology” is supported; saying “all agentic governance is already represented and enforced by OWL reasoning” is not. [P10], [P30] ### 2.2 The complete core class taxonomy# All 27 classes declared in the core file are listed below. The grouping follows actual subclass relations, with three additional canonical-definition subclasses declared near the end of the file. [P07], [C02] | Class or family | Declared classes | Intended role | Root | SemanticEntity | Shared semantic category. | Canonical definitions | CanonicalDefinition; LifecycleDefinition, PhaseDefinition, GateDefinition, AuthorityClass, WorkspaceDefinition, RegimeDefinition, GovernanceFrameworkDefinition, EnforcementAdapterDefinition | Versioned framework meaning and authority separation. | Runtime records | RuntimeRecord; GateInstance, EvidenceArtifact, ControlImplementation, GovernanceCase | Case-scoped occurrences or operational records. | Immutable records | ImmutableRecord; EvidenceClaim, EvidenceEvaluation, EvidenceBundleManifest, EvidenceBundleItem, MappingRecord, SemanticReleaseManifest, SemanticReleaseItem, MetricObservation, AssessmentRun | Records whose historical identity should be preserved. | Decisions | DecisionRecord under ImmutableRecord; GateDecisionRecord under DecisionRecord | Attributable decisions tied to input snapshots. This is intentionally a lightweight hierarchy. For example, EvidenceArtifact is a subclass of RuntimeRecord, not ImmutableRecord, even though its documentation emphasises immutable content identity. The description of immutable evidence and the precise OWL inheritance must not be conflated. Likewise, only the three regime/framework/adapter classes have the explicit pairwise disjointness described above; the file does not make every conceptual separation an OWL disjointness axiom. [P07] ### 2.3 Core relationships and cardinalities# The core declares 18 object properties. The complete set is hasPhaseDefinition, hasGateDefinition, instantiatesGate, gateInstanceCase, decisionForGate, decisionActor, usesArtifact, supportsTarget, claimScope, evaluatesClaim, containsBundleItem, bundleItemReferences, mapsSourceVersion, mapsTargetVersion, pinnedToReleaseManifest, containsReleaseItem, releaseItemReferences and supersedes. [P07] | Relationship | Declared domain and range where present | SHACL or operational qualification | Lifecycle → phase/gate definitions | LifecycleDefinition → PhaseDefinition/GateDefinition | At least one of each in the generic SHACL shape; the released registry has six. | Gate instance → definition and case | GateInstance → GateDefinition/GovernanceCase | Exactly one definition and one case, plus one string caseId. | Gate decision → gate | GateDecisionRecord → GateInstance | Exactly one gate; actor, authority basis, rationale and input snapshot required. | Claim → artifact/target/case | EvidenceClaim → EvidenceArtifact/SemanticEntity/GovernanceCase | Exactly one of each, statement and integrity reference. | Evaluation → claim | EvidenceEvaluation → EvidenceClaim | Exactly one claim and one allowed evaluation outcome. | Bundle → items/release | EvidenceBundleManifest → EvidenceBundleItem; release link range SemanticReleaseManifest | At least one item and exactly one pinned release. | Mapping → source and target versions | MappingRecord → CanonicalDefinition | Exactly one source and one target, coverage, rationale and approval state. | Record → superseded record | ImmutableRecord → ImmutableRecord | Directional historical link; storage immutability is a separate concern. OWL domain and range declarations support logical inference; they are not equivalent to rejecting malformed records. If a triple uses a property whose domain is EvidenceClaim, a reasoner can infer that type. A validation engine must separately check the intended input constraints. This distinction is essential when discussing “enforcement” with ontology specialists. [P07], [W02], [W03] The core’s 18 datatype properties are stableId, definitionVersion, caseId, recordedAt, appendOnly, contentDigest, recordDigest, inputSnapshotHash, authorityBasis, rationale, claimStatement, integrityReference, evaluationOutcome, coverageType, approvalStatus, manifestDigest, bundleDigest and ordinal. Some other terms used in contexts or shapes are not explicitly declared as datatype properties in the ontology. RDF permits vocabulary use without declaration; it still warrants documentation in a curated export. [P07], [P08], [C02] ### 2.4 What the core SHACL profile actually checks# The 12 shapes cover SemanticEntity, CanonicalDefinition, ImmutableRecord, LifecycleDefinition, GateInstance, GateDecisionRecord, EvidenceArtifact, EvidenceClaim, EvidenceEvaluation, EvidenceBundleManifest, MappingRecord and SemanticReleaseManifest. They use property cardinality, datatype, pattern, class, minimum length, fixed value and enumeration constraints. [P08] Every targeted semantic entity needs exactly one non-empty stableId; every canonical definition one dotted three-part version. An immutable record needs a date-time, a SHA-256-shaped record digest and appendOnly true. Digests are checked for lexical format here; a string matching the pattern is not proof that it was computed from the correct payload. The release verifier’s byte-hash comparison is a distinct check. [P08], [P28] Superclass shapes matter. In the supplementary test, a GateDefinition with no stable ID or version produces two violations when the ontology is supplied, even without enabling an additional inference regime. A consumer that omits the class hierarchy or uses a validator with different target handling can obtain weaker results. Validation configuration belongs in the exchange profile. [V01], [W03] The profile does not declare every node closed, does not provide a bespoke shape for every class and does not enforce all operational invariants. For example, naming something ImmutableRecord or requiring appendOnly true cannot stop a database administrator rewriting history. Schema and shape checks need persistence controls, version governance and audit procedures to realise that intention. [P07], [P08] The published JavaScript semantic validator uses N3 parsing and an in-repository implementation of the constraint subset used by the profile. It checks required class presence, namespace agreement, the invariant registry and valid/invalid fixtures. It is not evidence of conformance to the complete SHACL specification. This review adds independent pySHACL checks of the existing fixture pair, with the ontology supplied, no remote imports and meta-SHACL enabled. Those checks strengthen evidence for these fixtures, not for all possible graphs or the whole runtime. [P31], [V01] ### 2.5 Definition, case, evidence and decision as different objects# The distinction between GateDefinition, GateInstance and GateDecisionRecord separates three questions: what the gate means; how it is instantiated for this case; and which decision was made against which evidence at a particular time. Changing a definition should not retroactively rewrite earlier case decisions. A later decision can supersede a prior one while preserving both. [P03], [P07], [P14] Similarly, the evidence chain is artifact → claim → evaluation → decision, not “file uploaded → approved”. A security-test report can support a claim that one connector rejected a particular unauthorised operation. Its scope is that connector, test, version, method and case. It does not automatically support a claim that all connectors are non-bypassable, nor that the deployment is legally compliant. [P22], [P23], [P27] A Semantic Release Manifest binds the exact definition and schema bytes supporting the exchange. A bundle manifest pins the release and constituent records. This makes reconstruction possible: a reviewer can identify the vocabulary and record contracts that applied when a decision was produced. The manifest does not contain the truth of the world; it establishes the identity of the files being used. [P28] ### 2.6 The draft stack ontology and the 31 typed relations# The stack model reuses seven core classes: GovernanceCase, ControlImplementation, EvidenceArtifact, EvidenceClaim, EvidenceEvaluation, GateInstance and GateDecisionRecord. It declares 18 additional classes: Layer, Capability, GovernancePlane, ComponentVersion, AISystemVersion, Agent, ModelVersion, Tool, DataAsset, Provider, Service, PublicPolicy, PolicyVersion, ChangeSignal, ApplicabilityAssessment, RequirementVersion, ControlDefinition and Actor. Together these form the model’s 25 entity types. [P10], [P30] | Relationship family | Exact graph relationship types | Question supported | Architectural capability | PROVIDES_CAPABILITY, BELONGS_TO_LAYER, GOVERNS_LAYER, INFORMS | Which components and governance planes provide or govern capabilities? | Provider and technical dependency | OFFERS, USES_SERVICE, DEPENDS_ON, USES_MODEL, CALLS_TOOL, READS | Which systems depend on a changed service, model, tool or data asset? | Public-policy versioning | HAS_VERSION, FROM_VERSION, TO_VERSION, AFFECTS_SERVICE | Which two policy versions are compared and which service mapping is accepted? | Case and applicability | GOVERNS_VERSION, ASSESSES_SIGNAL, ASSESSES_SYSTEM, IN_CASE, CONSIDERS_REQUIREMENT, REVIEWED_BY | Which case, system, requirement and reviewer contextualise the change? | Control implementation | IMPLEMENTS, ADDRESSES_REQUIREMENT, APPLIES_TO_SYSTEM | Which deployed implementation addresses which control/requirement for which system? | Evidence | USES_ARTIFACT, SUPPORTS_TARGET, EVALUATES_CLAIM | What assertion and evaluation support the review? | Gate and decision history | REVIEWS_SYSTEM, DECISION_FOR_GATE, DECIDED_BY, BASED_ON_ASSESSMENT, SUPERSEDES | What decision was made, by whom, on what assessment, replacing which earlier decision? The JSON model constrains source and target types for each edge. The RDF extension declares 25 new object properties and reuses six from the core. Its new property declarations principally contain explanatory comments; they do not reproduce all JSON endpoint rules as OWL domain/range axioms. Therefore “31 typed relations” describes the graph model, not 31 fully axiomatized new OWL properties. [P10], [P30], [C02] The architecture view has layers L0 infrastructure/deployment, L1 evaluation/observability, L2 models/inference, L3 orchestration/tools, L4 knowledge/storage, L5 representation/retrieval, L6 acquisition/provenance, L7 context/memory and L8 runtime security/controls, plus applications and human interaction. This is a capability map, not a compulsory sequential execution pipeline. Governance and evaluation cross layers; components and capabilities can participate in more than one layer. [P10] The four stack shapes cover policy version, change signal, applicability assessment and requirement. Requirement kind is law, standard, internal-rule or contractual-term. PublicPolicy and RequirementVersion are explicitly disjoint: a provider statement and a legally or organisationally applicable requirement are different objects. The applicability assessment connects the signal to the specific system and case, with rationale and purpose. [P30] ### 2.7 Time, knowledge and policy-impact queries# The graph distinguishes valid time, the period for which an assertion applies, from recorded time, when it became known. validFrom and optional validTo use a half-open interval. Query parameters asOf and knownAt allow a reviewer to ask both “what applied then?” and “what could have been known then?”. Historical analysis should not import later evidence without making that change visible. [P10] The impact query starts from accepted current service mappings and follows reverse dependencies through DEPENDS_ON, USES_SERVICE, USES_MODEL, CALLS_TOOL and READS. It returns witness paths and relevant cases, controls, gates, decisions and evidence. Provisional mappings are excluded from accepted traversal and reported as incomplete coverage. A missing path does not prove that a system is unaffected. [P10] The statuses review-required, unmapped, source-versions-unavailable, signal-unavailable-at-query-time, baseline-established and no-mapped-system-in-scope describe different epistemic conditions. None is a legal approval or a guarantee of no impact. The documented query profile limits graph size and traversal depth; a depth-limit warning is evidence of incomplete traversal, not a safe result. [P10] This graph query must also be distinguished from the reference runtime’s continuous-assurance signal. The latter can invalidate purpose-bound Data Fitness Decisions and revoke unconsumed capabilities for the matching tenant/subject. The public-policy impact query itself does not automatically rewrite controls, reopen gates or revoke capabilities. These are separate mechanisms and authority paths. [P10], [P21] ### 2.8 Where agentic semantics are operational today# The core OWL vocabulary does not declare ActionClaim, ExecutionCapability, EffectContract, ExecutionReceipt, OutcomeAttestation, DataFitnessDecision, DisclosureContract or SwarmMandate as classes. These are nevertheless substantial PALO semantic contracts: their meanings are operationalised through JSON schemas, exact bindings and reference runtime code. Treating absence from OWL as absence from the project would be as inaccurate as claiming complete RDF coverage. [P07], [P17], [P20], [P21], [P24] An Effect Contract groups predicates as preconditions, expected effects and forbidden effects. The schema’s operator set includes exists, notExists, equals, unchanged, changedTo, deltaWithin, numberWithin, containsAll and typeIs, with version-specific legacy restrictions. Resource selectors bind the target and can bind tenant context. Verification specifies timing and inconclusive handling; recovery specifies hold/review or a proposed compensating action. [P20] At the action boundary, the inspected code checks schema semantics, identity and tenant consistency, policy, current data governance, claim digests and approval binding. Capabilities tie together the exact claim, decision, executor, verifier and target. Receipts and attestations preserve separate execution and verification outcomes. These checks support reference demonstrations; they do not establish that external connectors cannot be bypassed in an arbitrary deployed architecture. [P12], [P21], [P24] Several action-assurance contracts use the reference HMAC-SHA256 mechanism; the runtime also contains a separate Ed25519 evidence-envelope path. These mechanisms must not be described as interchangeable. A valid HMAC establishes integrity/authenticity relative to possession of the shared secret; it does not provide public-key non-repudiation between mutually untrusted parties. Neither a signature nor an unkeyed digest proves that an input observation was truthful. Key custody, observer trust, external anchoring and independent validation require explicit deployment evidence. [P15], [P21], [P24] ### 2.9 Worked example connecting taxonomy, ontology and execution# Consider a synthetic refund agent for a support case. A human owner authorises refunds within a defined resource, tenant, per-action limit and shared budget. This example illustrates the contracts and makes no claim about an actual financial deployment. [P12], [P19] - Frame and classify. Record the business purpose, affected customer, accountable owner and whether an agent is necessary. Classify the action as financially consequential; classify autonomy separately. A simulator tier informs scrutiny but does not authorise the refund. - Define authority. Register the agent profile and delegated scopes. If several agents share exposure, bind them to the same mandate and budget. A permission for each agent must not multiply the total approved budget. - Establish data fitness. Identify the order/customer-data subject, purpose and current evidence. A fitness decision for another tenant or purpose cannot be reused. - Bound disclosure. Permit only the needed fields and destinations. A refund may succeed while still violating the disclosure contract, so the two outcomes remain separately observable. - Construct the Action Claim. Bind tool, operation, arguments, target, nonce, sequence, idempotency key, expiry, authority context and effect/data contracts. The proposed amount is part of the content being authorised. - Evaluate and approve. Evaluate current policy and obtain an exact-claim approval when required. Editing the amount or beneficiary after approval changes the claim and requires a new evaluation/approval path. - Issue and consume the capability. Bind executor and verifier, reserve exposure and execute through the governed connector. A lost response must not by itself justify an ungoverned duplicate refund. - Record execution and observe effect. Preserve receipt digests; obtain the authoritative post-state needed to evaluate the contract. A transport success is not enough. - Evaluate outcome and disclosure. Expected predicates might include the intended refund amount and account change; forbidden predicates might include an unintended beneficiary or disallowed data transmission. Missing observation remains inconclusive. - Build the evidence chain. An artifact contains the bounded execution evidence; a claim states exactly what it supports; an evaluation judges it; a gate decision records accountable acceptance, conditions or hold. Pin the semantic release and preserve later supersession. | Adverse variant | Required semantic distinction | Evidence the reviewer should request | Data permission withdrawn after initial approval | Historical permission versus current fitness/capability validity | Signal, invalidation time, revocation and attempted execution record. | Budget available to two agents but insufficient for a third | Individual permit versus aggregate exposure | Reservation/commit history and proof the denied connector did not run. | Refund API reports success but ledger cannot be read | Execution succeeded versus outcome inconclusive | Receipt, failed/missing observation and held incident. | Wrong field disclosed while refund effect is correct | Business effect versus disclosure conformity | Disclosure observation, mismatch checks and response record. | Coordinator revoked while an action is in flight | Future authority revoked versus confirmed external cancellation | Lease/cancellation acknowledgement and eventual effect observation. | New evidence contradicts the previous evaluation | Original decision versus superseding decision | Both records, input hashes, rationale and time/knowledge context. ### 2.10 Competency questions and interoperability# An ontology’s usefulness can be assessed through competency questions: specific questions its representation should answer with evidence. The following questions distinguish existing representation from additional work. | Question | Existing support | Remaining boundary | Which definition/version governed this gate? | Gate Instance, lifecycle definition and release manifest | Consumer must resolve the pinned artifacts. | Which artifact supports this claim and how was it evaluated? | Artifact/claim/evaluation relations and schemas | Truth, method quality and independence require review. | Who decided and what inputs were considered? | Gate Decision Record actor, authority basis, rationale and snapshot hash | Strings do not independently authenticate authority. | Which systems depend on a changed provider service? | Draft graph, accepted mappings and witness-path query | Inventory/mapping completeness and currentness. | Was a proposed action approved exactly as executed? | Claim digest, approval, capability and receipt contracts | End-to-end connector evidence and deployment controls. | Was authority still current at execution? | Runtime revalidation, expiries and revocation mechanisms | Race conditions and distributed boundary qualification. | Which data could leave and which did leave? | Disclosure contract, observation and receipt | Trustworthiness and completeness of the observer. | What was known at an earlier decision time? | Valid/recorded time and snapshot query | Availability of complete historical snapshots. | Can another organisation reconstruct the same graph and validation result? | Public vocabulary and schemas | Complete JSON-to-RDF mapping and conformance profile remain to be established. | Can every agentic contract be queried in RDF? | Partial vocabulary and rich JSON contracts | A complete agentic RDF module and conversion are proposed work. Interoperability should preserve semantic boundaries rather than maximise the number of vocabulary links. The following are candidate alignment directions; no implemented PALO mapping is asserted solely from conceptual similarity. | Vocabulary | Useful alignment target | Required care | SKOS | Concept schemes, preferred/alternative labels, broader/narrower relations, mapping annotations | Distinguish related or close meanings from exact equivalence; preserve local scope. | PROV-O | Entities, activities, agents and derivation/association of evidence | A business “agent” and prov:Agent do not establish authorised delegation by themselves. | ODRL | Permissions, prohibitions, duties, parties and constraints | PALO action approval and effect verification need explicit operational semantics beyond a policy description. | DPV | Data processing purposes, personal-data concepts, actors, risks and measures | Preserve jurisdiction, evidence and reviewer decisions; vocabulary reuse does not establish a lawful basis. | DCAT | External datasets, distributions, data services and catalog metadata | PALO’s evidence reference and AI-system inventory need not become a duplicate data catalog. | JSON-LD | Stable IRIs and typed links for exchange | A context alone is not a complete serializer for an arbitrary graph envelope. | OWL and SHACL | Conceptual axioms and record validation | Keep inference, validation, authorisation and effect observation separate. Primary specifications: [W01], [W02], [W03], [W04], [W05], [W06], [W07], [W08]. These alignments require term-by-term mappings, counterexamples, directionality, versions, scope and round-trip tests. In particular, avoid blanket owl:equivalentClass, owl:sameAs or skos:exactMatch assertions for concepts whose authority, time or case scope differs. ### 2.11 Reproducible verification and what it establishes# The source snapshot combines resident working-tree files, identified Git objects where accessible and exact public artifacts recovered for cloud-only files. Provenance and SHA-256 values are retained in the research manifests. The 40 core release items all match the inspected semantic manifest, establishing integrity of the selected foundation snapshot. Other working-tree and draft-extension material has separate version history; a matching digest does not prove current deployment or current source review. [V01] The reproducible review script parsed all four Turtle files, enumerated classes/properties/shapes, checked 65 JSON schemas structurally, extracted 2,408 schema entries and 204 enum declarations, and validated 61 named valid/invalid JSON fixtures against their matched contracts with format checking enabled. All 61 produced the expected valid/invalid classification. This is not a claim that every schema has a complete negative-test suite. [V01] The independent RDF run used the supplied core ontology and shapes: the valid fixture conformed; the deliberately invalid fixture produced 10 SHACL results. An incomplete GateDefinition probe was rejected for missing stable identity and version. Meta-SHACL validation was enabled. The stack vocabulary and shapes were parsed and inventoried; no stack-instance SHACL conformance suite was run in this review. [V01] The 14 named invariants provide a useful control map: stable identity; canonical versions; preservation of released definitions; definition/instance separation; gate definition/case binding; attributable immutable decisions; atomic claim scope; separate evaluation; manifest-based bundles; version-specific mappings; release pinning; distinct delivery/authority classifications; no creation of legal or deployment authority by framework guidance; and accountable review of non-authoritative signals. Their stated enforcement mechanisms range from schemas and generators to documentation and module contracts. They must not be presented as 14 universally machine-proven properties. [P32] ### 2.12 Gaps, ambiguity and a bounded next extension# | Finding | Current interpretation | Recommended disposition | Five historical activities and six canonical phases | Editorial correspondence 1.0 is now explicit | Retain six-phase canonical IDs; treat the teaching correspondence as many-to-many. | CECR acronym previously had two meanings | Separate editorial concept IDs and simulator wording now distinguish them | Define a numerical protocol for control effectiveness and coverage before operational use. | Routing and legal prohibition | Both UI views now use “Redesign required”; old display alias is deprecated | Preserve independent legal classification. | Agentic objects primarily in JSON | Operational contracts are richer than the OWL vocabulary | Add a focused agentic ontology module tied to existing contract IDs. | JSON-LD contexts do not fully map all envelopes/fields | Vocabulary portability is partial | Define explicit transforms and round-trip loss tests. | Some classes have no dedicated shape; some terms lack declarations | Lightweight profile, not exhaustive closed validation | Publish shape coverage and intended open/closed boundaries. | 14 invariants mix automated and procedural controls | A registry entry does not prove enforcement | Attach each invariant to code/tests/operational evidence and residual limits. | Signatures and append-only flags have limited scope | Integrity and storage assertions are not truth or independent assurance | Add deployment-specific key, observer, persistence and audit evidence. | Bilingual labels and synonym governance are distributed | No unified reviewed dictionary release | Curate a bilingual concept registry and acronym policy. | Draft-source oversight/bias mappings have a separate lifecycle | Research alignment is not adopted-standard conformity | Preserve exact source edition, interpretation, reviewer and revision status. The smallest useful next semantic release would cover one complete chain: Agent → delegated mandate/authority → Action Claim → policy decision → optional approval → execution capability → execution → receipt → outcome attestation → evidence claim/evaluation → gate decision. Data-fitness and disclosure links should be included because Action Claim 1.4 already depends on them. It should reuse existing identifiers and contracts instead of renaming the runtime around a new ontology. This is a proposed extension, not an implementation delivered by this dossier. A bounded acceptance package would include: a bilingual concept register; explicit proposed OWL classes and properties; JSON-to-RDF transformations; SHACL coverage tied to schemas; positive and negative synthetic examples; competency queries; temporal/revocation/case/tenant counterexamples; lossless round-trip checks for the agreed profile; and an immutable release manifest. Test missing observations, expired approvals, changed arguments, stale fitness, conflicting evidence, shared budgets and a revocation during execution. Keep broader legal applicability and production admission outside the semantic pass/fail criterion. The useful question for the Commission is therefore concrete: which minimal vocabulary and evidence-exchange profile would allow independent parties to reconstruct and challenge a delegated-action decision consistently? PALO already supplies a substantial foundation for that exercise. The next step is to agree the bounded profile, evidence and acceptance criteria, then demonstrate interchange and failure behaviour against it. ### 2.13 Additional insights from GLM and their evidence review# A GLM-5.3-Flash consultation on 12 October 2026 challenged the public artifact summary. Its response is an analytical contribution based on that supplied summary, not an independent audit of the repository. The following insights were retained after comparison with PALO artifacts and primary specifications. Authority of statements and authority to act are separate. The four spine classes describe the status of framework information; an agent's authority depends on its principal, profile, delegation, policy and exact action context. A unified dictionary should give these axes different property names and scope notes. It should not infer an execution permit from a canonical-definition label. Verification obligations deserve explicit closure. GLM proposed tracking executions whose required attestation has not arrived by a declared deadline. PALO already implements verification tasks, expiry windows, retries and input_required states; these mechanisms must be recognised before calling the capability missing. A useful extension is a documented completeness query and metric: executions requiring verification with neither a recorded attestation nor an explicitly assigned unresolved incident by the agreed deadline. This proposed measure needs a defined clock, denominator, exclusions, retry semantics and recovery protocol. An inconclusive attestation closes the obligation to record an assessment but does not resolve the underlying business uncertainty. [P24] Evidence disagreement should remain visible. A future conflict record could identify the claims/evaluations in conflict, their scope and time, resolution authority and decision. This should complement the existing conservative data-fitness evaluator, not replace it with a rule that always prefers newer or signed evidence. Integrity, independence, relevance and truth are separate dimensions. PALO's current Evidence Evaluation already keeps four quality dimensions separate. [P21], [P23] Cross-format integrity requires an explicit algorithm profile. The inspected core runtime recursively sorts JSON object keys for one canonicalisation function; arrays retain order. The separate evidence-envelope version 2 explicitly declares RFC8785, and assurance-foundation.js implements a JCS-labelled canonicaliser with finite-number and Unicode-surrogate checks for Ed25519 signing/verification. The release manifest instead hashes exact file bytes. These procedures have different scopes. Independent RFC conformance is not established by this review, and no RDF Dataset Canonicalization claim follows from deterministic JSON output. An exchange profile should name the precise path and test vectors, including number handling, Unicode and graph serialisation. [P24], [P28], [P33] Several GLM suggestions were deliberately not adopted as facts: a linear ladder that places cryptographic anchoring above independent evaluation; an assumption that all 409 mappings are direct regulatory crosswalks; identity binding or temporal handling described as wholly absent; and categorical claims that SHACL cannot express policy-relevant constraints. The precise boundary is that validation constraints can support a policy process, while a shape evaluation alone does not grant operational authority or enforce external effects. GLM's older DPV/DCAT references were replaced with the primary publications checked for this dossier. [P09], [P17], [P24], [W03], [W06], [W07] ### 2.14 Publication provenance and maintenance# The semantic model, the editorial dossier, the runtime source and a hosted website are different release surfaces. This dossier retains the exact source inventory and verification results; the website exposes a separate publication inventory for the two detailed sections, technical catalogue, glossary and PDF. Updating the editorial material does not raise the maturity of the runtime or the draft stack ontology. The source-registry reconciliation marks overdue entries review-due while retaining their original checkedAt and nextReviewAt. Six entries required substantive review at the original snapshot time. The subsequent six-source review addendum records their review and current deadlines; the earlier snapshot and its tests remain historically attributable. The semantic release manifest and Knowledge Reader manifest are updated together so that the metadata transition cannot silently break their integrity pins. This is a review-status transition, not a new validation of the referenced regulations or standards. The publication process records source identity, artifact hashes, target and verification time. GitHub Pages and the separately hosted canonical domain require distinct deployment evidence. A sitemap date comes from the editorial modification record, while component release dates and source verification dates retain their own meaning. A noindex briefing page is deliberately excluded from the search sitemap; that does not exempt its content from release tracking. [P36] ## Sources and accompanying catalogues# PALO artifact links resolve to public source locations where available. The research snapshot and validation records preserve the inspected bytes. Linked living pages may subsequently change. - [P01] PALO semantic foundation. - [H01] Fabrizio Degni, The PALO Framework A Paradigm for Principled AI Lifecycle Orchestration in Business, December 2025, 67-page local founding document under framework/. Core principles: pp. 13–15; five-phase lifecycle: pp. 18–22; evaluation dimensions: pp. 22–23. Page numbers refer to the PDF page sequence. Extract retained in the research record. - [P02] Semantic spine. - [P03] Lifecycle definitions. - [P04] Governance control packs. - [P05] Control library. - [P06] KPI and KRI registry. - [P07] Core ontology. - [P08] Core SHACL profile. - [P09] Semantic mappings. - [P10] Stack and policy impact graph and stack model. - [P11] PALO-AM operational model. - [P12] Full-cycle assurance. - [P13] Agentic capability matrix. - [P14] Gate Decision Record schema. - [P15] Agent Profile schema. - [P16] PALO-AM simulator source. - [P17] Action Claim schema. - [P18] ANS integration. - [P19] Swarm prototype, distributed extension and mandate schema. - [P20] Effect Contract, Execution Capability, Execution Receipt, Outcome Attestation, Policy Decision, Approval. - [P21] Data assurance control plane. - [P22] Evidence Claim schema. - [P23] Evidence Evaluation schema. - [P24] Inspected local source packages/palo-mcp-server/core.js, preserved with digest in the research snapshot; public project PALOframework. Local working-tree code is not assumed to equal the published Git HEAD. - [P25] Disclosure Contract, Disclosure Observation, Disclosure Receipt, Data Fitness Decision. - [P26] Oversight crosswalk and bias crosswalk. - [P27] Evidence Artifact and Evidence Bundle Manifest. - [P28] Semantic Release Manifest and pinned public release generator. - [P29] Semantic change-impact register. - [P30] Stack ontology, stack SHACL, stack JSON-LD context and core JSON-LD context. - [P31] Pinned public semantic validator. - [P32] Semantic invariants. - [P33] Evidence-envelope schema and pinned assurance foundation implementation. - [P34] PolicyWatcher Signal Batch, Operational Signal Registry and Browser-local Review Ledger. Acquired from Git commit 42d17508ddc836ae37076d9320cbbc672ea268cc. - [P35] Agentic editorial glossary and historical lifecycle correspondence, version 1.0.0. Separate from the canonical ontology and KPI/KRI registry. - [P36] Semantic publication inventory. This records the editorial release; deployment evidence is a separate receipt. - [W01] W3C SKOS vocabulary. - [W02] W3C OWL 2 Primer. - [W03] W3C SHACL Recommendation. - [W04] W3C PROV-O. - [W05] W3C ODRL Information Model. - [W06] Data Privacy Vocabulary. DPV 2.3 identifies itself as a Final Community Group Report and explicitly states that it is not a W3C Standard or on the W3C Standards Track. - [W07] W3C DCAT 3. - [W08] W3C JSON-LD 1.1. - [C01] Schema index, field dictionary JSON, field dictionary CSV and controlled values. - [C02] RDF inventory and searchable catalogue. - [V01] Snapshot verification results and source inventory. The reproducible audit script and complete acquired source snapshot are retained in the local review package. Verification date: 12 October 2026. --- ## Semantic technical catalogues Canonical URL: https://paloframework.org/semantic-catalogues/ Editorial date: 2026-10-12 # Technical catalogues Editorial update: 12 October 2026. Exact schema values and source registry content supporting the PALO semantic deep dive. This extraction does not create new canonical definitions. Read the taxonomyField dictionary CSVField dictionary JSONControlled vocabularies JSONRDF inventory JSON 65 schemas · 2,408 schema entries · 204 enum declarations. “Required in parent” describes the local schema branch; conditional and referenced requirements must also be evaluated. ## Canonical registries and draft graph Lifecycle (6) Source: data/lifecycle-core.json · Download full registry [ { "phaseDefinitionId": "phase-frame", "semanticId": "https://paloframework.org/semantic/stage/frame", "definitionVersion": "3.0.0", "ordinal": 1, "label": "Frame", "purpose": "Define the use case, its boundary, owners and affected people before governance choices are made.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/frame?v=3.1.0" }, { "phaseDefinitionId": "phase-classify", "semanticId": "https://paloframework.org/semantic/stage/classify", "definitionVersion": "3.0.0", "ordinal": 2, "label": "Classify", "purpose": "Establish the applicable risk route, obligations and level of scrutiny.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/classify?v=3.1.0" }, { "phaseDefinitionId": "phase-assess", "semanticId": "https://paloframework.org/semantic/stage/assess", "definitionVersion": "3.0.0", "ordinal": 3, "label": "Assess", "purpose": "Evaluate impacts, rights, delegated authority, autonomy and oversight conditions.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/assess?v=3.1.0" }, { "phaseDefinitionId": "phase-control", "semanticId": "https://paloframework.org/semantic/stage/control", "definitionVersion": "3.0.0", "ordinal": 4, "label": "Control", "purpose": "Translate findings into owned, testable engineering, process and assurance controls.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/control?v=3.1.0" }, { "phaseDefinitionId": "phase-measure", "semanticId": "https://paloframework.org/semantic/stage/measure", "definitionVersion": "3.0.0", "ordinal": 5, "label": "Measure", "purpose": "Define how accountability, performance, risk and drift will be observed over time.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/measure?v=3.1.0" }, { "phaseDefinitionId": "phase-prove", "semanticId": "https://paloframework.org/semantic/stage/prove", "definitionVersion": "3.0.0", "ordinal": 6, "label": "Prove & Review", "purpose": "Assemble reconstructable evidence, decide readiness and feed findings into the next cycle.", "gateDefinitionRef": "https://paloframework.org/semantic/gate/prove?v=3.1.0" } ] Gate definitions (6) Source: data/lifecycle-core.json · Download full registry [ { "gateDefinitionId": "https://paloframework.org/semantic/gate/frame?v=3.1.0", "gateId": "frame", "definitionVersion": "3.1.0", "label": "Frame", "purpose": "Agree the problem, affected stakeholders, intended benefit, owner and non-AI alternatives.", "entryCriteria": [ "Named accountable owner", "Problem and affected population described", "Non-AI option considered" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-purpose-boundary" ], "conditionalControlIds": [ "ctrl-system-card-explanations", "ctrl-data-governance-lifecycle", "ctrl-privacy-lifecycle", "ctrl-environmental-performance", "ctrl-ai-literacy-effectiveness", "ctrl-aims-leadership-objectives" ], "indicatorIds": [ "kri-scope-change-rate", "kpi-system-card-coverage", "kpi-data-lifecycle-coverage", "kpi-energy-measurement-coverage", "kpi-ai-literacy-competence-rate", "kpi-aims-objective-coverage" ], "sourceIds": [ "src-oecd-ai-principles", "src-nist-ai-rmf" ], "templateIds": [ "tpl-contribution-starter" ] }, { "gateDefinitionId": "https://paloframework.org/semantic/gate/classify?v=3.1.0", "gateId": "classify", "definitionVersion": "3.1.0", "label": "Classify", "purpose": "Identify system type, authority, affected rights, jurisdictions, suppliers and preliminary risk posture.", "entryCriteria": [ "Purpose boundary recorded", "Material system and supplier dependencies listed" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-purpose-boundary", "ctrl-third-party-due-diligence", "ctrl-change-gate" ], "conditionalControlIds": [ "ctrl-fair-allocation", "ctrl-system-card-explanations", "ctrl-affected-person-notice", "ctrl-article50-transparency", "ctrl-privacy-lifecycle", "ctrl-gpai-provider", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-regulatory-incident-reporting", "ctrl-runtime-production-boundary", "ctrl-aims-leadership-objectives" ], "indicatorIds": [ "kri-scope-change-rate", "kpi-system-card-coverage", "kpi-notice-delivery-coverage", "kpi-gpai-obligation-evidence-coverage", "kpi-production-admission-coverage", "kpi-aims-objective-coverage" ], "sourceIds": [ "src-eu-ai-act", "src-nist-ai-rmf" ], "templateIds": [ "tpl-procurement" ] }, { "gateDefinitionId": "https://paloframework.org/semantic/gate/assess?v=3.1.0", "gateId": "assess", "definitionVersion": "3.1.0", "label": "Assess", "purpose": "Test impacts, data, misuse, limitations, alternatives and residual uncertainty.", "entryCriteria": [ "Classification reviewed", "Data and affected-stakeholder context available", "Test scope agreed" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-data-provenance", "ctrl-third-party-due-diligence", "ctrl-adversarial-testing", "ctrl-change-gate" ], "conditionalControlIds": [ "ctrl-agentic-authority", "ctrl-fairness-quality-of-service", "ctrl-fair-allocation", "ctrl-harmful-representation", "ctrl-system-card-explanations", "ctrl-data-governance-lifecycle", "ctrl-annotation-quality", "ctrl-privacy-lifecycle", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-ai-output-accessibility", "ctrl-environmental-performance" ], "indicatorIds": [ "kpi-provenance-coverage", "kpi-vendor-evidence-coverage", "kri-critical-test-failure-rate", "kpi-subgroup-evaluation-coverage", "kri-residual-disparity-rate", "kpi-explanation-comprehension", "kpi-data-lifecycle-coverage", "kpi-annotation-quality-coverage", "kri-systemic-risk-finding-rate", "kpi-accessibility-test-pass-rate", "kpi-energy-measurement-coverage" ], "sourceIds": [ "src-nist-ai-rmf", "src-nist-genai-profile" ], "templateIds": [ "tpl-red-team-evidence", "tpl-procurement" ] }, { "gateDefinitionId": "https://paloframework.org/semantic/gate/control?v=3.1.0", "gateId": "control", "definitionVersion": "3.1.0", "label": "Control", "purpose": "Assign safeguards, owners, escalation, human authority, technical limits and supplier obligations.", "entryCriteria": [ "Material risks and uncertainty recorded", "Control owners available", "Residual-risk decision route named" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-data-provenance", "ctrl-human-review", "ctrl-third-party-due-diligence", "ctrl-incident-response" ], "conditionalControlIds": [ "ctrl-system-card-explanations", "ctrl-affected-person-notice", "ctrl-appeal-remedy", "ctrl-article50-transparency", "ctrl-data-governance-lifecycle", "ctrl-privacy-lifecycle", "ctrl-gpai-provider", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-regulatory-incident-reporting", "ctrl-decommissioning", "ctrl-ai-output-accessibility", "ctrl-ai-literacy-effectiveness", "ctrl-runtime-production-boundary" ], "indicatorIds": [ "kpi-review-completion", "kpi-vendor-evidence-coverage", "kri-sensitive-data-events", "kri-override-failure-rate", "kpi-notice-delivery-coverage", "kpi-appeal-resolution-sla", "kpi-machine-readable-marking-coverage", "kpi-data-lifecycle-coverage", "kpi-gpai-obligation-evidence-coverage", "kpi-regulatory-reporting-clock-compliance", "kpi-accessibility-test-pass-rate", "kpi-ai-literacy-competence-rate", "kpi-production-admission-coverage" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf" ], "templateIds": [ "tpl-incident-response", "tpl-procurement" ] }, { "gateDefinitionId": "https://paloframework.org/semantic/gate/measure?v=3.1.0", "gateId": "measure", "definitionVersion": "3.1.0", "label": "Measure", "purpose": "Set baselines, indicators, thresholds, monitoring ownership and response timing.", "entryCriteria": [ "Controls and owners assigned", "Data collection feasibility checked", "Threshold decision rights named" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-adversarial-testing", "ctrl-incident-response", "ctrl-decision-trace" ], "conditionalControlIds": [ "ctrl-fairness-quality-of-service", "ctrl-fair-allocation", "ctrl-harmful-representation", "ctrl-system-card-explanations", "ctrl-affected-person-notice", "ctrl-appeal-remedy", "ctrl-article50-transparency", "ctrl-data-governance-lifecycle", "ctrl-annotation-quality", "ctrl-gpai-provider", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-regulatory-incident-reporting", "ctrl-decommissioning", "ctrl-ai-output-accessibility", "ctrl-environmental-performance", "ctrl-ai-literacy-effectiveness", "ctrl-aims-internal-audit", "ctrl-aims-management-review-capa", "ctrl-runtime-production-boundary" ], "indicatorIds": [ "kpi-review-completion", "kpi-incident-triage-time", "kri-sensitive-data-events", "kri-critical-test-failure-rate", "kri-residual-disparity-rate", "kri-harmful-representation-rate", "kpi-explanation-comprehension", "kpi-appeal-resolution-sla", "kri-overdue-remedy-rate", "kri-provenance-verification-failure-rate", "kpi-deletion-verification-coverage", "kri-systemic-risk-finding-rate", "kpi-regulatory-reporting-clock-compliance", "kpi-decommissioning-evidence-coverage", "kri-accessibility-blocker-rate", "kri-environmental-budget-variance", "kri-trained-control-error-rate", "kpi-aims-audit-completion", "kpi-corrective-action-closure", "kri-execution-bypass-rate" ], "sourceIds": [ "src-nist-ai-rmf" ], "templateIds": [ "tpl-incident-response", "tpl-red-team-evidence" ] }, { "gateDefinitionId": "https://paloframework.org/semantic/gate/prove?v=3.1.0", "gateId": "prove", "definitionVersion": "3.1.0", "label": "Prove and Review", "purpose": "Assemble decision evidence, exceptions, source status, approvals and triggers for reopening.", "entryCriteria": [ "Required evidence indexed", "Exceptions and residual risk recorded", "Review and reopening schedule assigned" ], "decisionOptions": [ "proceed", "proceed-with-conditions", "hold", "redesign", "stop" ], "requiredControlIds": [ "ctrl-human-review", "ctrl-adversarial-testing", "ctrl-incident-response", "ctrl-change-gate", "ctrl-decision-trace" ], "conditionalControlIds": [ "ctrl-fairness-quality-of-service", "ctrl-fair-allocation", "ctrl-harmful-representation", "ctrl-system-card-explanations", "ctrl-affected-person-notice", "ctrl-appeal-remedy", "ctrl-article50-transparency", "ctrl-data-governance-lifecycle", "ctrl-annotation-quality", "ctrl-privacy-lifecycle", "ctrl-gpai-provider", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-regulatory-incident-reporting", "ctrl-decommissioning", "ctrl-ai-output-accessibility", "ctrl-environmental-performance", "ctrl-ai-literacy-effectiveness", "ctrl-aims-leadership-objectives", "ctrl-aims-internal-audit", "ctrl-aims-management-review-capa", "ctrl-runtime-production-boundary" ], "indicatorIds": [ "kpi-provenance-coverage", "kpi-review-completion", "kpi-incident-triage-time", "kri-scope-change-rate", "kpi-subgroup-evaluation-coverage", "kri-residual-disparity-rate", "kpi-system-card-coverage", "kpi-explanation-comprehension", "kpi-notice-delivery-coverage", "kpi-appeal-resolution-sla", "kpi-machine-readable-marking-coverage", "kpi-data-lifecycle-coverage", "kpi-annotation-quality-coverage", "kpi-gpai-obligation-evidence-coverage", "kpi-regulatory-reporting-clock-compliance", "kpi-decommissioning-evidence-coverage", "kpi-accessibility-test-pass-rate", "kpi-energy-measurement-coverage", "kpi-ai-literacy-competence-rate", "kpi-aims-objective-coverage", "kpi-aims-audit-completion", "kpi-corrective-action-closure", "kpi-production-admission-coverage" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42001" ], "templateIds": [ "tpl-board-review", "tpl-contribution-starter" ] } ] Twelve governance domains (12) Source: data/governance-control-packs.json · Download full registry [ { "domainId": "domain-fairness-subgroups", "title": "Fairness and subgroup testing", "objective": "Make quality-of-service, allocation and representational-harm evaluation a release and monitoring requirement for affected and intersectional groups.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Can outcomes or service quality differ across affected groups?", "Does the system allocate, rank, recommend or represent people or groups?" ], "controlIds": [ "ctrl-fairness-quality-of-service", "ctrl-fair-allocation", "ctrl-harmful-representation" ], "indicatorIds": [ "kpi-subgroup-evaluation-coverage", "kri-residual-disparity-rate", "kri-harmful-representation-rate" ], "gateIds": [ "classify", "assess", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "subgroup-register", "fairness-test-result", "threshold-approval", "residual-disparity-disclosure" ], "completionCriteria": [ "Applicable groups, intersections, metrics, sample adequacy and thresholds are approved before evaluation.", "Component and whole-system tests pass or a named authority records conditions, mitigation and residual disparities." ], "stopConditions": [ "A material subgroup is omitted or a release threshold is exceeded without accepted mitigation and disclosure." ], "residualBoundary": "PALO validates the governance record, not the scientific validity, legality or social acceptability of a fairness metric or trade-off." }, { "domainId": "domain-system-card-explanations", "title": "System cards and stakeholder explanations", "objective": "Maintain a version-bound system card and verify that affected people, operators, reviewers and customers understand the explanation needed for their decisions.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Do stakeholders need information to understand, rely on, challenge or operate the system?" ], "controlIds": [ "ctrl-system-card-explanations" ], "indicatorIds": [ "kpi-system-card-coverage", "kpi-explanation-comprehension" ], "gateIds": [ "frame", "assess", "control", "prove" ], "evidenceContractRefs": [ "schemas/palo-system-card.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "system-card", "stakeholder-explanation", "comprehension-test", "limitation-disclosure" ], "completionCriteria": [ "The card matches the deployed system and identifies use, components, data, performance, limitations, oversight and monitoring.", "Representative stakeholders meet an approved comprehension rubric in supported languages and accessible formats." ], "stopConditions": [ "A material limitation, decision consequence or human action route is absent or critically misunderstood." ], "residualBoundary": "A system card and comprehension test do not guarantee that every individual understands an outcome or that an explanation is legally sufficient." }, { "domainId": "domain-notice-appeal-remedy", "title": "Affected-person notice, appeal, independent review and remedy", "objective": "Turn contestability into an accessible operational case flow with accountable deadlines, conflict-independent review, reasoned outcomes and verified remedies.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Can an AI-assisted interaction or outcome materially affect an identifiable person?", "Could a person reasonably need explanation, correction or review?" ], "controlIds": [ "ctrl-affected-person-notice", "ctrl-appeal-remedy" ], "indicatorIds": [ "kpi-notice-delivery-coverage", "kpi-appeal-resolution-sla", "kri-overdue-remedy-rate" ], "gateIds": [ "classify", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-affected-person-case.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "notice-template", "delivery-log", "appeal-case", "independence-check", "review-outcome", "remedy-record" ], "completionCriteria": [ "Notice and intake routes are accessible, timely and connected to the correct case and system version.", "Appeals receive conflict-independent review and accepted remedies are verified before closure." ], "stopConditions": [ "A high-impact system lacks a reachable human challenge route or an urgent remedy is overdue." ], "residualBoundary": "The adopting organization must determine legal rights, deadlines, reviewer independence and available remedies for each jurisdiction and context." }, { "domainId": "domain-article50-transparency", "title": "Article 50 marking, labelling and provenance", "objective": "Separate provider and deployer obligations and preserve evidence for AI-interaction notices, machine-readable marks, labels, provenance and exceptions.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Does the system interact directly with people?", "Does it generate or manipulate image, audio, video or text content covered by Article 50?", "Is the organization acting as provider, deployer or both?" ], "controlIds": [ "ctrl-article50-transparency" ], "indicatorIds": [ "kpi-machine-readable-marking-coverage", "kri-provenance-verification-failure-rate" ], "gateIds": [ "classify", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-article50-transparency-record.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "article50-applicability-record", "interaction-notice-test", "machine-readable-marking-test", "deployer-label-record", "content-provenance-record" ], "completionCriteria": [ "A reviewed actor, content-type, obligation and exception assessment exists for every supported modality.", "Independent samples verify notices, detectable marks, labels and provenance across the expected content transformation path." ], "stopConditions": [ "Required notices or markings are systematically absent, undetectable or not bound to the produced content." ], "residualBoundary": "PALO records implementation claims but does not prescribe one technical marking standard or determine equivalent legal adequacy." }, { "domainId": "domain-data-lifecycle", "title": "Dataset, annotation, privacy, retention and deletion lifecycle", "objective": "Trace material training, evaluation, prompt, retrieval, embedding and operational data through origin, transformation, quality, permission, lawful use, retention and verified disposition.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Does the system train, evaluate, retrieve, infer from or retain material data or knowledge sources?", "Is personal, sensitive, licensed or annotated data involved?" ], "controlIds": [ "ctrl-data-provenance", "ctrl-data-governance-lifecycle", "ctrl-annotation-quality", "ctrl-privacy-lifecycle" ], "indicatorIds": [ "kpi-provenance-coverage", "kpi-data-lifecycle-coverage", "kpi-annotation-quality-coverage", "kpi-deletion-verification-coverage", "kri-sensitive-data-events" ], "gateIds": [ "frame", "classify", "assess", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-data-lineage-record.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "dataset-lineage-record", "permission-record", "quality-test", "annotation-protocol", "lawful-basis-record", "retention-schedule", "deletion-verification" ], "completionCriteria": [ "Every material data asset has a versioned lineage, purpose, permission, quality, sensitivity and owner record.", "Retention and deletion decisions cover replicas, derived data, embeddings, caches and approved legal holds." ], "stopConditions": [ "A material dataset has unknown origin or permission, or sensitive data lacks an approved lifecycle and disposition route." ], "residualBoundary": "Schema-valid records cannot establish lawful basis, ownership, representativeness or actual deletion without accountable and technical verification." }, { "domainId": "domain-gpai-systemic-risk", "title": "GPAI provider, deployer and systemic-risk workflows", "objective": "Determine value-chain role, assemble applicable provider or deployer evidence and operate systemic-risk evaluation, mitigation, incident and downstream-information workflows.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Is the organization providing, modifying, integrating or deploying a general-purpose AI model?", "Could the model meet systemic-risk classification or create material cascading impacts?" ], "controlIds": [ "ctrl-gpai-provider", "ctrl-gpai-deployer", "ctrl-systemic-risk", "ctrl-third-party-due-diligence" ], "indicatorIds": [ "kpi-gpai-obligation-evidence-coverage", "kri-systemic-risk-finding-rate", "kpi-vendor-evidence-coverage" ], "gateIds": [ "classify", "assess", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-gpai-systemic-risk-record.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "gpai-role-assessment", "model-component-inventory", "provider-evidence-review", "systemic-risk-assessment", "model-evaluation", "risk-mitigation-record" ], "completionCriteria": [ "Actor role, model identity, modifications, applicable obligations and downstream dependencies receive accountable review.", "Systemic-risk scenarios, evaluations, mitigations, residual findings and incident routes are current for the released model." ], "stopConditions": [ "The GPAI role is undetermined, mandatory provider evidence is missing or a critical systemic-risk scenario is untested." ], "residualBoundary": "PALO does not designate a model as systemic-risk GPAI, verify model-provider disclosures or establish compliance with the voluntary Code." }, { "domainId": "domain-serious-incident-decommissioning", "title": "Serious-incident reporting and decommissioning", "objective": "Bind detection to jurisdiction-specific reporting clocks and ensure withdrawal or retirement completes stakeholder transition, revocation, data disposition and residual monitoring.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Can a system failure meet a serious-incident or other mandatory reporting threshold?", "Is the system, model, provider or material feature being withdrawn or retired?" ], "controlIds": [ "ctrl-incident-response", "ctrl-regulatory-incident-reporting", "ctrl-decommissioning" ], "indicatorIds": [ "kpi-incident-triage-time", "kpi-regulatory-reporting-clock-compliance", "kpi-decommissioning-evidence-coverage" ], "gateIds": [ "classify", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-serious-incident-record.schema.json", "schemas/palo-decommission-record.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "serious-incident-record", "reportability-decision", "notification-receipt", "decommission-plan", "data-disposition-record", "retirement-verification" ], "completionCriteria": [ "Clock starts, applicable deadlines, reportability decisions, notifications and corrective actions are timestamped and evidence-bound.", "Decommissioning closes only after access revocation, stakeholder transition, data disposition and residual-risk verification." ], "stopConditions": [ "A potentially reportable incident has no active accountable clock or a retirement would strand unsafe access, data or affected users." ], "residualBoundary": "Legal reportability, authority routing and deadlines require current jurisdiction-specific review; retirement evidence needs operational verification." }, { "domainId": "domain-accessibility", "title": "Accessibility of AI interactions and outcomes", "objective": "Test interfaces, notices, explanations, generated content, human review and remedy routes with assistive technologies and representative disabled users.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Can disabled people interact with, receive, understand or challenge system outputs?" ], "controlIds": [ "ctrl-ai-output-accessibility", "ctrl-affected-person-notice", "ctrl-system-card-explanations" ], "indicatorIds": [ "kpi-accessibility-test-pass-rate", "kri-accessibility-blocker-rate", "kpi-explanation-comprehension" ], "gateIds": [ "assess", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "accessibility-test-plan", "assistive-technology-result", "user-evaluation", "conformance-report", "remediation-record" ], "completionCriteria": [ "Critical journeys and supported output modalities pass automated and manual accessibility evaluation.", "Representative disabled users can complete notice, explanation, review and remedy journeys through equivalent routes." ], "stopConditions": [ "A high-impact notice, decision, review or remedy journey has an unresolved accessibility blocker." ], "residualBoundary": "PALO does not certify WCAG conformance or replace sector, product and jurisdiction-specific accessibility assessment." }, { "domainId": "domain-environment", "title": "Environmental performance", "objective": "Make energy, emissions, water and hardware impacts visible through explicit boundaries, measurement or estimation, alternatives and accountable budgets.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Are training, evaluation, inference or hardware impacts material under the organization environmental boundary?" ], "controlIds": [ "ctrl-environmental-performance" ], "indicatorIds": [ "kpi-energy-measurement-coverage", "kri-environmental-budget-variance" ], "gateIds": [ "frame", "assess", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "environmental-boundary-record", "energy-measurement", "emissions-calculation", "alternative-analysis", "budget-decision" ], "completionCriteria": [ "Material workloads have declared boundaries, reproducible measurement or estimation and current baselines.", "Material regressions and alternative architectures receive an accountable budget and trade-off decision." ], "stopConditions": [ "A material workload has no baseline or exceeds an approved budget without a reviewed exception." ], "residualBoundary": "PALO does not prescribe lifecycle-accounting methodology, verify supplier data or make environmental claims independently." }, { "domainId": "domain-ai-literacy", "title": "AI literacy and competence effectiveness", "objective": "Move beyond attendance records by testing role-specific knowledge, practical control behavior and refresh needs after system or obligation changes.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Does a role develop, deploy, operate, review, procure, oversee or use AI on the organization behalf?" ], "controlIds": [ "ctrl-ai-literacy-effectiveness" ], "indicatorIds": [ "kpi-ai-literacy-competence-rate", "kri-trained-control-error-rate" ], "gateIds": [ "frame", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "role-competence-matrix", "learning-record", "competence-assessment", "observed-practice-test", "refresh-record" ], "completionCriteria": [ "Every in-scope role has approved competencies and current role-specific learning.", "People demonstrate competence in practical assessments and observed control behavior, with failures routed to refresh and redesign." ], "stopConditions": [ "A high-authority role lacks current demonstrated competence for the system and decisions in scope." ], "residualBoundary": "PALO cannot establish competence from attendance, self-attestation or a generic quiz and does not define an organization curriculum." }, { "domainId": "domain-iso42001-aims", "title": "ISO/IEC 42001 management-system overlay", "objective": "Connect system-level PALO cases to organizational context, leadership, policy, objectives, support, operations, performance evaluation, internal audit, management review and corrective action.", "completionLevel": "governance-control-plane", "applicabilityQuestions": [ "Is the organization establishing, operating or assessing an AI management system?" ], "controlIds": [ "ctrl-aims-leadership-objectives", "ctrl-aims-internal-audit", "ctrl-aims-management-review-capa" ], "indicatorIds": [ "kpi-aims-objective-coverage", "kpi-aims-audit-completion", "kpi-corrective-action-closure" ], "gateIds": [ "frame", "classify", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-aims-overlay-record.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "aims-scope", "ai-policy", "aims-objectives", "audit-programme", "management-review-record", "corrective-action", "effectiveness-check" ], "completionCriteria": [ "The AIMS scope, policy, objectives, roles, resources and documented-information controls are approved and connected to applicable PALO cases.", "Internal audit, management review, nonconformity and corrective-action cycles operate with independence and effectiveness evidence." ], "stopConditions": [ "Material AI activities fall outside the declared AIMS scope without review or a critical nonconformity is overdue." ], "residualBoundary": "This is an implementation overlay, not the licensed ISO/IEC 42001 text, a clause-by-clause legal interpretation or certification." }, { "domainId": "domain-palo-ai-production", "title": "PALO-AI production identity, persistence, tenancy, keys and execution", "objective": "Fail closed unless the deployed runtime demonstrates workload identity, tenant isolation, durable recovery, external key custody, non-bypassable policy enforcement, trusted connectors and verified effects.", "completionLevel": "reference-runtime-only", "applicabilityQuestions": [ "Will PALO-AI authorize or execute consequential actions in a production environment?", "Will multiple tenants, external connectors or regulated evidence use the runtime?" ], "controlIds": [ "ctrl-agentic-authority", "ctrl-runtime-production-boundary" ], "indicatorIds": [ "kpi-production-admission-coverage", "kri-execution-bypass-rate", "kri-tool-call-error-rate", "kri-override-failure-rate" ], "gateIds": [ "classify", "control", "measure", "prove" ], "evidenceContractRefs": [ "schemas/palo-production-profile.schema.json", "schemas/palo-governance-assurance-record.schema.json" ], "minimumEvidenceKinds": [ "production-profile", "identity-test", "tenant-isolation-test", "persistence-recovery-test", "key-custody-attestation", "bypass-resistance-test", "connector-attestation" ], "completionCriteria": [ "The production admission validator passes only against deployment-specific, current and independently challengeable evidence.", "Every protected external effect is observed through a claim, decision, one-time capability, trusted receipt and authoritative outcome-verification chain." ], "stopConditions": [ "Shared tokens, process-local keys, SQLite-only state, unscoped tenant data or an in-process bypass route remain in the production path." ], "residualBoundary": "PALO 3.1 supplies a fail-closed admission contract and reference tests; it does not claim production completion until external infrastructure and independent deployment evidence satisfy that contract." } ] All 31 controls (31) Source: data/control-library.json · Download full registry [ { "controlId": "ctrl-purpose-boundary", "title": "Document purpose and prohibited uses", "objective": "Keep intended outcomes, affected people, authority and prohibited uses explicit and reviewable.", "controlType": "directive", "lifecycleGates": [ "frame", "classify" ], "evidenceKinds": [ "approved-purpose-record", "stakeholder-map" ], "indicatorIds": [ "kri-scope-change-rate" ], "sourceIds": [ "src-nist-ai-rmf", "src-oecd-ai-principles" ], "templateIds": [ "tpl-board-review", "tpl-procurement" ] }, { "controlId": "ctrl-data-provenance", "title": "Record data provenance and permitted use", "objective": "Trace material data sources, permissions, quality limits and sensitivity decisions.", "controlType": "preventive", "lifecycleGates": [ "assess", "control" ], "evidenceKinds": [ "data-inventory", "provenance-record", "quality-test" ], "indicatorIds": [ "kpi-provenance-coverage", "kri-sensitive-data-events" ], "sourceIds": [ "src-nist-ai-rmf", "src-eu-ai-act" ], "templateIds": [ "tpl-procurement", "tpl-red-team-evidence" ] }, { "controlId": "ctrl-human-review", "title": "Define meaningful human review", "objective": "Give named reviewers sufficient information, authority, time and escalation paths to change outcomes.", "controlType": "preventive", "lifecycleGates": [ "control", "prove" ], "evidenceKinds": [ "review-procedure", "override-log", "training-record" ], "indicatorIds": [ "kpi-review-completion", "kri-override-failure-rate" ], "sourceIds": [ "src-nist-ai-rmf", "src-oecd-ai-principles", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review", "tpl-incident-response" ] }, { "controlId": "ctrl-third-party-due-diligence", "title": "Perform risk-based third-party due diligence", "objective": "Record supplier capabilities, limitations, dependencies, change notices, audit rights and exit options.", "controlType": "preventive", "lifecycleGates": [ "classify", "assess", "control" ], "evidenceKinds": [ "supplier-questionnaire", "contract-control-matrix", "exit-plan" ], "indicatorIds": [ "kpi-vendor-evidence-coverage" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf" ], "templateIds": [ "tpl-procurement" ] }, { "controlId": "ctrl-adversarial-testing", "title": "Test misuse and failure scenarios", "objective": "Exercise credible abuse, unsafe-output, security and recovery scenarios before and after material change.", "controlType": "detective", "lifecycleGates": [ "assess", "measure", "prove" ], "evidenceKinds": [ "test-plan", "test-result", "residual-risk-record" ], "indicatorIds": [ "kri-critical-test-failure-rate" ], "sourceIds": [ "src-nist-genai-profile", "src-owasp-llm-top10" ], "templateIds": [ "tpl-red-team-evidence" ] }, { "controlId": "ctrl-incident-response", "title": "Operate incident and escalation response", "objective": "Detect, contain, document, communicate and learn from material failures and near misses.", "controlType": "corrective", "lifecycleGates": [ "control", "measure", "prove" ], "evidenceKinds": [ "incident-record", "containment-log", "post-incident-review" ], "indicatorIds": [ "kpi-incident-triage-time", "kri-sensitive-data-events" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42001" ], "templateIds": [ "tpl-incident-response", "tpl-board-review" ] }, { "controlId": "ctrl-change-gate", "title": "Gate material model and workflow changes", "objective": "Reassess purpose, authority, data, controls and evidence before material changes enter use.", "controlType": "preventive", "lifecycleGates": [ "classify", "assess", "prove" ], "evidenceKinds": [ "change-record", "impact-delta", "approval-record" ], "indicatorIds": [ "kri-scope-change-rate", "kpi-review-completion" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-decision-trace", "title": "Maintain decision and evidence traceability", "objective": "Connect accountable decisions to inputs, controls, exceptions, evidence and source status.", "controlType": "detective", "lifecycleGates": [ "measure", "prove" ], "evidenceKinds": [ "decision-log", "evidence-index", "exception-record" ], "indicatorIds": [ "kpi-review-completion", "kpi-provenance-coverage" ], "sourceIds": [ "src-nist-ai-rmf", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review", "tpl-contribution-starter" ] }, { "controlId": "ctrl-agentic-authority", "title": "Enforce agentic authority and delegation constraints", "objective": "Limit tool access, define subagent boundaries, and intercept high-risk action claims in autonomous AI workflows.", "controlType": "preventive", "lifecycleGates": [ "assess", "control" ], "evidenceKinds": [ "agentic-interface-config", "signed-execution-log", "human-override-record" ], "indicatorIds": [ "kpi-review-completion", "kri-scope-change-rate" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-fairness-quality-of-service", "title": "Test quality of service across affected groups", "objective": "Define relevant demographic and intersectional groups, approved metrics and release thresholds, then test component and whole-system performance before release and after material change.", "controlType": "preventive", "lifecycleGates": [ "assess", "measure", "prove" ], "evidenceKinds": [ "subgroup-register", "evaluation-dataset-record", "fairness-test-result", "threshold-approval" ], "indicatorIds": [ "kpi-subgroup-evaluation-coverage", "kri-residual-disparity-rate" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005", "src-eu-ai-act" ], "templateIds": [ "tpl-red-team-evidence", "tpl-board-review" ] }, { "controlId": "ctrl-fair-allocation", "title": "Test allocation effects and disparities", "objective": "Evaluate whether decisions, rankings or allocations create unjustified differences in resources or opportunities and record mitigation and residual disparity decisions.", "controlType": "preventive", "lifecycleGates": [ "classify", "assess", "prove" ], "evidenceKinds": [ "allocation-impact-assessment", "group-outcome-test", "trade-off-decision", "residual-disparity-disclosure" ], "indicatorIds": [ "kpi-subgroup-evaluation-coverage", "kri-residual-disparity-rate" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-harmful-representation", "title": "Detect stereotyping, demeaning and erasing outputs", "objective": "Test representational harms across languages, cultures and intersecting groups, including refusal, omission and generated-content failure modes.", "controlType": "detective", "lifecycleGates": [ "assess", "measure", "prove" ], "evidenceKinds": [ "representation-test-set", "harmful-output-evaluation", "mitigation-result", "residual-harm-record" ], "indicatorIds": [ "kri-harmful-representation-rate" ], "sourceIds": [ "src-nist-genai-profile", "src-iso-42005" ], "templateIds": [ "tpl-red-team-evidence" ] }, { "controlId": "ctrl-system-card-explanations", "title": "Maintain a system card and test stakeholder explanations", "objective": "Keep intended use, components, data, performance, limitations, human authority and monitoring current, and test whether each stakeholder group can understand and act on the explanation provided.", "controlType": "directive", "lifecycleGates": [ "frame", "assess", "control", "prove" ], "evidenceKinds": [ "system-card", "stakeholder-explanation", "comprehension-test", "limitation-disclosure" ], "indicatorIds": [ "kpi-system-card-coverage", "kpi-explanation-comprehension" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review", "tpl-contribution-starter" ] }, { "controlId": "ctrl-affected-person-notice", "title": "Provide timely notice to affected people", "objective": "Inform affected people about material AI involvement, decision significance, available human contact, explanation and challenge routes in an accessible form.", "controlType": "directive", "lifecycleGates": [ "classify", "control", "measure" ], "evidenceKinds": [ "notice-template", "delivery-log", "accessibility-review", "channel-coverage-test" ], "indicatorIds": [ "kpi-notice-delivery-coverage" ], "sourceIds": [ "src-eu-ai-act", "src-eu-article50-guidelines", "src-wcag-22" ], "templateIds": [ "tpl-incident-response" ] }, { "controlId": "ctrl-appeal-remedy", "title": "Operate appeal, independent review and remedy", "objective": "Provide an accessible intake route, conflict-independent reviewer, decision deadline, reasoned outcome and tracked correction, restoration or compensation route where applicable.", "controlType": "corrective", "lifecycleGates": [ "control", "measure", "prove" ], "evidenceKinds": [ "appeal-case", "independence-check", "review-outcome", "remedy-record" ], "indicatorIds": [ "kpi-appeal-resolution-sla", "kri-overdue-remedy-rate" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42005" ], "templateIds": [ "tpl-incident-response", "tpl-board-review" ] }, { "controlId": "ctrl-article50-transparency", "title": "Enforce Article 50 notices, marking, labelling and provenance", "objective": "Determine provider and deployer duties, disclose direct AI interaction, apply detectable machine-readable marks to in-scope synthetic content, preserve provenance and test required labels and exceptions.", "controlType": "preventive", "lifecycleGates": [ "classify", "control", "measure", "prove" ], "evidenceKinds": [ "article50-applicability-record", "interaction-notice-test", "machine-readable-marking-test", "deployer-label-record", "content-provenance-record" ], "indicatorIds": [ "kpi-machine-readable-marking-coverage", "kri-provenance-verification-failure-rate" ], "sourceIds": [ "src-eu-ai-act", "src-eu-article50-guidelines" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-data-governance-lifecycle", "title": "Govern complete data and knowledge-source lifecycles", "objective": "Trace datasets, prompts, retrieval corpora, embeddings and derived data through origin, transformation, permission, quality, use, retention, deletion and change impact.", "controlType": "preventive", "lifecycleGates": [ "frame", "assess", "control", "measure", "prove" ], "evidenceKinds": [ "dataset-lineage-record", "transformation-log", "permission-record", "retention-schedule", "deletion-verification" ], "indicatorIds": [ "kpi-data-lifecycle-coverage", "kpi-deletion-verification-coverage", "kpi-provenance-coverage" ], "sourceIds": [ "src-eu-gdpr", "src-eu-ai-act", "src-nist-ai-rmf" ], "templateIds": [ "tpl-procurement", "tpl-board-review" ] }, { "controlId": "ctrl-annotation-quality", "title": "Assure annotation and ground-truth quality", "objective": "Define annotation instructions, annotator competence, sampling, agreement, dispute resolution, drift review and known ground-truth limitations.", "controlType": "detective", "lifecycleGates": [ "assess", "measure", "prove" ], "evidenceKinds": [ "annotation-protocol", "annotator-competence-record", "inter-annotator-test", "quality-sample", "dispute-log" ], "indicatorIds": [ "kpi-annotation-quality-coverage" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005" ], "templateIds": [ "tpl-red-team-evidence" ] }, { "controlId": "ctrl-privacy-lifecycle", "title": "Apply privacy obligations across the AI lifecycle", "objective": "Record actor roles, purposes, lawful basis, necessity, minimisation, data-subject rights, retention, deletion and privacy-risk decisions for personal data used by or exposed to AI.", "controlType": "preventive", "lifecycleGates": [ "frame", "classify", "assess", "control", "prove" ], "evidenceKinds": [ "privacy-role-record", "lawful-basis-record", "necessity-test", "rights-procedure", "retention-schedule", "deletion-verification" ], "indicatorIds": [ "kpi-data-lifecycle-coverage", "kpi-deletion-verification-coverage", "kri-sensitive-data-events" ], "sourceIds": [ "src-eu-gdpr", "src-nist-ai-rmf" ], "templateIds": [ "tpl-procurement", "tpl-board-review" ] }, { "controlId": "ctrl-gpai-provider", "title": "Operate the GPAI provider obligation pack", "objective": "For in-scope providers, maintain technical documentation, downstream information, copyright policy, training-content summary and Code-of-Practice or equivalent compliance evidence.", "controlType": "directive", "lifecycleGates": [ "classify", "control", "measure", "prove" ], "evidenceKinds": [ "gpai-role-assessment", "technical-documentation", "downstream-information-pack", "copyright-policy", "training-content-summary", "code-conformity-record" ], "indicatorIds": [ "kpi-gpai-obligation-evidence-coverage" ], "sourceIds": [ "src-eu-ai-act", "src-eu-gpai-code" ], "templateIds": [ "tpl-procurement", "tpl-board-review" ] }, { "controlId": "ctrl-gpai-deployer", "title": "Operate the GPAI deployer and integrator control pack", "objective": "Record model selection, contractual rights, provider documentation, configuration, downstream context, evaluation, monitoring and material modifications for GPAI use.", "controlType": "preventive", "lifecycleGates": [ "classify", "assess", "control", "measure", "prove" ], "evidenceKinds": [ "gpai-role-assessment", "model-component-inventory", "provider-evidence-review", "deployment-evaluation", "material-modification-record" ], "indicatorIds": [ "kpi-gpai-obligation-evidence-coverage", "kpi-vendor-evidence-coverage" ], "sourceIds": [ "src-eu-ai-act", "src-eu-gpai-code", "src-nist-genai-profile" ], "templateIds": [ "tpl-procurement", "tpl-red-team-evidence" ] }, { "controlId": "ctrl-systemic-risk", "title": "Evaluate and mitigate GPAI systemic risk", "objective": "Identify model-capability, misuse, cyber, autonomy, societal and cascading risks; run proportionate evaluations and adversarial tests; document mitigations and unresolved systemic-risk findings.", "controlType": "preventive", "lifecycleGates": [ "classify", "assess", "control", "measure", "prove" ], "evidenceKinds": [ "systemic-risk-assessment", "model-evaluation", "adversarial-test-result", "risk-mitigation-record", "systemic-incident-record" ], "indicatorIds": [ "kri-systemic-risk-finding-rate", "kri-critical-test-failure-rate" ], "sourceIds": [ "src-eu-ai-act", "src-eu-gpai-code", "src-nist-genai-profile", "src-owasp-llm-top10" ], "templateIds": [ "tpl-red-team-evidence", "tpl-incident-response" ] }, { "controlId": "ctrl-regulatory-incident-reporting", "title": "Classify and report serious incidents within applicable clocks", "objective": "Start a jurisdiction-specific clock at detection, preserve evidence, determine reportability, notify competent authorities and affected parties, and document updates and closure without delaying containment.", "controlType": "corrective", "lifecycleGates": [ "control", "measure", "prove" ], "evidenceKinds": [ "serious-incident-record", "reportability-decision", "regulatory-clock-log", "notification-receipt", "corrective-action-record" ], "indicatorIds": [ "kpi-regulatory-reporting-clock-compliance", "kpi-incident-triage-time" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42001" ], "templateIds": [ "tpl-incident-response", "tpl-board-review" ] }, { "controlId": "ctrl-decommissioning", "title": "Gate withdrawal, retirement and decommissioning", "objective": "Plan service withdrawal, customer transition, model and data disposition, capability revocation, residual monitoring and accountable closure before operation ends.", "controlType": "corrective", "lifecycleGates": [ "control", "measure", "prove" ], "evidenceKinds": [ "decommission-plan", "stakeholder-notice", "data-disposition-record", "access-revocation-log", "retirement-verification" ], "indicatorIds": [ "kpi-decommissioning-evidence-coverage" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review", "tpl-incident-response" ] }, { "controlId": "ctrl-ai-output-accessibility", "title": "Test accessible AI interactions and generated outcomes", "objective": "Test interfaces, notices, explanations, generated content, review and appeal routes with assistive technologies and representative disabled users across supported modalities.", "controlType": "preventive", "lifecycleGates": [ "assess", "control", "measure", "prove" ], "evidenceKinds": [ "accessibility-test-plan", "assistive-technology-result", "user-evaluation", "conformance-report", "remediation-record" ], "indicatorIds": [ "kpi-accessibility-test-pass-rate", "kri-accessibility-blocker-rate" ], "sourceIds": [ "src-wcag-22", "src-iso-42005", "src-eu-ai-act" ], "templateIds": [ "tpl-red-team-evidence", "tpl-board-review" ] }, { "controlId": "ctrl-environmental-performance", "title": "Measure and govern AI environmental performance", "objective": "Define material energy, carbon, water and hardware indicators, establish baselines and budgets, compare alternatives and gate material environmental regressions.", "controlType": "preventive", "lifecycleGates": [ "frame", "assess", "measure", "prove" ], "evidenceKinds": [ "environmental-boundary-record", "energy-measurement", "emissions-calculation", "alternative-analysis", "budget-decision" ], "indicatorIds": [ "kpi-energy-measurement-coverage", "kri-environmental-budget-variance" ], "sourceIds": [ "src-iso-42001", "src-iso-42005", "src-eu-ai-act" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-ai-literacy-effectiveness", "title": "Measure role-based AI literacy effectiveness", "objective": "Map role competencies, deliver contextual learning, assess demonstrated ability, refresh after material change and track whether trained people apply required controls.", "controlType": "directive", "lifecycleGates": [ "frame", "control", "measure", "prove" ], "evidenceKinds": [ "role-competence-matrix", "learning-record", "competence-assessment", "observed-practice-test", "refresh-record" ], "indicatorIds": [ "kpi-ai-literacy-competence-rate", "kri-trained-control-error-rate" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-aims-leadership-objectives", "title": "Establish AIMS context, leadership, policy and objectives", "objective": "Define organizational scope, interested parties, accountable leadership, AI policy, measurable objectives, roles, resources and controlled documented information.", "controlType": "directive", "lifecycleGates": [ "frame", "classify", "prove" ], "evidenceKinds": [ "aims-scope", "ai-policy", "leadership-commitment", "roles-and-authorities", "aims-objectives", "document-control-record" ], "indicatorIds": [ "kpi-aims-objective-coverage" ], "sourceIds": [ "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-aims-internal-audit", "title": "Operate risk-based AIMS internal audits", "objective": "Maintain an independent audit programme covering system and organizational controls, evidence quality, nonconformities and follow-up verification.", "controlType": "detective", "lifecycleGates": [ "measure", "prove" ], "evidenceKinds": [ "audit-programme", "auditor-independence-record", "audit-plan", "audit-report", "nonconformity-record" ], "indicatorIds": [ "kpi-aims-audit-completion", "kpi-corrective-action-closure" ], "sourceIds": [ "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-aims-management-review-capa", "title": "Perform management review and corrective action", "objective": "Review AIMS performance, source and context changes, incidents, audit results, resources and objectives; assign corrective actions and verify effectiveness before closure.", "controlType": "corrective", "lifecycleGates": [ "measure", "prove" ], "evidenceKinds": [ "management-review-record", "performance-evaluation", "corrective-action", "effectiveness-check", "continual-improvement-record" ], "indicatorIds": [ "kpi-corrective-action-closure", "kpi-aims-objective-coverage" ], "sourceIds": [ "src-iso-42001" ], "templateIds": [ "tpl-board-review" ] }, { "controlId": "ctrl-runtime-production-boundary", "title": "Enforce PALO-AI production admission and non-bypassable execution", "objective": "Refuse production claims unless workload identity, tenant isolation, durable state, external key custody, policy enforcement, trusted connectors, outcome verification and recovery controls are configured and tested.", "controlType": "preventive", "lifecycleGates": [ "classify", "control", "measure", "prove" ], "evidenceKinds": [ "production-profile", "identity-test", "tenant-isolation-test", "persistence-recovery-test", "key-custody-attestation", "bypass-resistance-test", "connector-attestation" ], "indicatorIds": [ "kpi-production-admission-coverage", "kri-execution-bypass-rate" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf", "src-owasp-llm-top10" ], "templateIds": [ "tpl-red-team-evidence", "tpl-board-review" ] } ] All 38 indicators with formulas (38) Source: data/kpi-kri-registry.json · Download full registry [ { "indicatorId": "kpi-provenance-coverage", "type": "KPI", "name": "Material data provenance coverage", "purpose": "Track whether material data inputs have reviewed provenance records.", "formula": "reviewed material data sources / identified material data sources * 100", "cadence": "monthly and before material change", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85%" }, "controlIds": [ "ctrl-data-provenance", "ctrl-decision-trace" ], "gateIds": [ "assess", "prove" ], "sourceIds": [ "src-nist-ai-rmf" ], "caveat": "Coverage measures documentation presence, not correctness, permission, or fitness for use." }, { "indicatorId": "kpi-review-completion", "type": "KPI", "name": "Required review completion", "purpose": "Track whether decisions requiring human review received a recorded review before execution.", "formula": "eligible decisions with timely recorded review / eligible decisions * 100", "cadence": "weekly", "direction": "higher-is-better", "thresholds": { "amber": "below 98%", "red": "below 95%" }, "controlIds": [ "ctrl-human-review", "ctrl-change-gate", "ctrl-decision-trace" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-oecd-ai-principles", "src-nist-ai-rmf" ], "caveat": "Completion alone does not show that review was informed, independent, or able to alter the outcome." }, { "indicatorId": "kpi-vendor-evidence-coverage", "type": "KPI", "name": "Supplier evidence coverage", "purpose": "Track completion of required supplier evidence items for in-scope services.", "formula": "accepted required supplier evidence items / required supplier evidence items * 100", "cadence": "quarterly and at renewal", "direction": "higher-is-better", "thresholds": { "amber": "below 90%", "red": "below 75%" }, "controlIds": [ "ctrl-third-party-due-diligence" ], "gateIds": [ "assess", "control" ], "sourceIds": [ "src-iso-42001" ], "caveat": "Accepted evidence must still be tested for relevance, recency, scope and independent support." }, { "indicatorId": "kpi-incident-triage-time", "type": "KPI", "name": "Median incident triage time", "purpose": "Track elapsed time from detection to accountable initial classification and containment assignment.", "formula": "median minutes from detectedAt to triagedAt for in-scope incidents", "cadence": "monthly", "direction": "lower-is-better", "thresholds": { "amber": "over 240 minutes", "red": "over 480 minutes" }, "controlIds": [ "ctrl-incident-response" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-nist-ai-rmf" ], "caveat": "Fast triage is not equivalent to correct severity, containment quality, or regulatory reporting." }, { "indicatorId": "kri-scope-change-rate", "type": "KRI", "name": "Ungated material scope changes", "purpose": "Detect purpose, population, authority or workflow changes that bypassed the change gate.", "formula": "ungated material changes / identified material changes * 100", "cadence": "monthly", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "above 5%" }, "controlIds": [ "ctrl-purpose-boundary", "ctrl-change-gate" ], "gateIds": [ "frame", "classify", "prove" ], "sourceIds": [ "src-nist-ai-rmf" ], "caveat": "A useful denominator depends on reliable change detection and an agreed definition of material change." }, { "indicatorId": "kri-sensitive-data-events", "type": "KRI", "name": "Sensitive-data control events", "purpose": "Surface unauthorized access, disclosure, retention or use involving sensitive data.", "formula": "count of confirmed in-scope sensitive-data control events", "cadence": "continuous with monthly review", "direction": "lower-is-better", "thresholds": { "amber": "1 event", "red": "2 or more events or any severe event" }, "controlIds": [ "ctrl-data-provenance", "ctrl-incident-response" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-nist-ai-rmf" ], "caveat": "Counts depend on detection quality and do not by themselves determine legal incident materiality." }, { "indicatorId": "kri-override-failure-rate", "type": "KRI", "name": "Human override failure rate", "purpose": "Detect cases where a required reviewer could not pause, alter or reverse a system action.", "formula": "failed override attempts / recorded override attempts * 100", "cadence": "weekly", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "above 2% or any severe consequence" }, "controlIds": [ "ctrl-human-review" ], "gateIds": [ "control", "measure" ], "sourceIds": [ "src-oecd-ai-principles", "src-eu-ai-act" ], "caveat": "Low rates can hide low usage, poor logging or reviewers avoiding an ineffective mechanism." }, { "indicatorId": "kri-critical-test-failure-rate", "type": "KRI", "name": "Critical adversarial test failure rate", "purpose": "Track unresolved critical failures in approved misuse and failure scenarios.", "formula": "unresolved critical failed tests / executed critical tests * 100", "cadence": "per release and monthly for adaptive systems", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any failure without an approved containment decision" }, "controlIds": [ "ctrl-adversarial-testing" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-nist-genai-profile", "src-owasp-llm-top10" ], "caveat": "The metric is only as useful as scenario coverage, test independence and severity calibration." }, { "indicatorId": "kri-tool-call-error-rate", "type": "KRI", "name": "Tool call error rate", "purpose": "Track the rate of malformed, hallucinated, or unauthorized tool calls made by autonomous agents.", "formula": "unauthorized or failed tool calls / total tool calls * 100", "cadence": "weekly and per release", "direction": "lower-is-better", "thresholds": { "amber": "above 1%", "red": "above 5% or any unauthorized write attempt" }, "controlIds": [ "ctrl-human-review" ], "gateIds": [ "control", "measure" ], "sourceIds": [ "src-nist-ai-rmf" ], "caveat": "High error rates indicate semantic drift, poor schema alignment, or attempt to bypass controls." }, { "indicatorId": "kri-multi-agent-conflict-rate", "type": "KRI", "name": "Multi-agent conflict rate", "purpose": "Track deadlocked, conflicting, or terminated multi-agent workflows.", "formula": "deadlocked or failed workflow runs / total multi-agent runs * 100", "cadence": "weekly", "direction": "lower-is-better", "thresholds": { "amber": "above 2%", "red": "above 10%" }, "controlIds": [ "ctrl-human-review" ], "gateIds": [ "control", "measure" ], "sourceIds": [ "src-nist-ai-rmf" ], "caveat": "Signals goal conflicts, prompt mismatches, or infinite message loop issues." }, { "indicatorId": "kpi-subgroup-evaluation-coverage", "type": "KPI", "name": "Applicable subgroup evaluation coverage", "purpose": "Track whether approved demographic and intersectional groups are represented in release and monitoring evaluations.", "formula": "applicable approved subgroups with accepted evaluation evidence / applicable approved subgroups * 100", "cadence": "per release, after material change and quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "below 95% or any omitted high-impact group" }, "controlIds": [ "ctrl-fairness-quality-of-service", "ctrl-fair-allocation" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005" ], "caveat": "Coverage does not show that group definitions, sample sizes, metrics or thresholds are appropriate." }, { "indicatorId": "kri-residual-disparity-rate", "type": "KRI", "name": "Unaccepted residual disparity rate", "purpose": "Surface subgroup metric comparisons that exceed an approved maximum difference without an accountable residual-risk decision.", "formula": "subgroup comparisons above approved difference threshold without accepted decision / applicable subgroup comparisons * 100", "cadence": "per release and monthly for adaptive systems", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any unresolved material disparity" }, "controlIds": [ "ctrl-fairness-quality-of-service", "ctrl-fair-allocation" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-nist-ai-rmf", "src-eu-ai-act" ], "caveat": "A numerical threshold cannot by itself determine whether a difference is lawful, fair or acceptable." }, { "indicatorId": "kri-harmful-representation-rate", "type": "KRI", "name": "Material harmful-representation rate", "purpose": "Track unresolved stereotyping, demeaning, erasing or culturally harmful outputs in approved test scenarios.", "formula": "unresolved material harmful outputs / executed representation scenarios * 100", "cadence": "per release and monthly", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any severe output or repeated group-specific pattern" }, "controlIds": [ "ctrl-harmful-representation" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-nist-genai-profile", "src-iso-42005" ], "caveat": "Results depend on culturally competent scenario design, reviewers and supported languages." }, { "indicatorId": "kpi-system-card-coverage", "type": "KPI", "name": "Current system-card coverage", "purpose": "Track whether in-scope systems have an approved card reflecting the deployed version, use, limitations, data, performance and controls.", "formula": "in-scope deployed systems with current approved system cards / in-scope deployed systems * 100", "cadence": "per release and quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any high-impact system without a current card" }, "controlIds": [ "ctrl-system-card-explanations" ], "gateIds": [ "frame", "assess", "prove" ], "sourceIds": [ "src-nist-ai-rmf", "src-eu-ai-act" ], "caveat": "A current card is documentation evidence, not proof that its claims are accurate or understood." }, { "indicatorId": "kpi-explanation-comprehension", "type": "KPI", "name": "Stakeholder explanation comprehension", "purpose": "Measure whether representative stakeholders can correctly understand limitations, significance, human authority and available actions.", "formula": "participants meeting the approved comprehension rubric / tested representative participants * 100", "cadence": "before release, after material explanation change and annually", "direction": "higher-is-better", "thresholds": { "amber": "below 85%", "red": "below 70% or any critical misunderstanding" }, "controlIds": [ "ctrl-system-card-explanations" ], "gateIds": [ "assess", "control", "prove" ], "sourceIds": [ "src-iso-42005", "src-wcag-22" ], "caveat": "The organization must justify participant selection, language, accessibility and the comprehension rubric." }, { "indicatorId": "kpi-notice-delivery-coverage", "type": "KPI", "name": "Affected-person notice delivery coverage", "purpose": "Track whether people receive an accessible notice before or at the point of material AI interaction or effect.", "formula": "eligible interactions or decisions with verified notice delivery / eligible interactions or decisions * 100", "cadence": "continuous with monthly review", "direction": "higher-is-better", "thresholds": { "amber": "below 99%", "red": "below 95% or any systematic channel failure" }, "controlIds": [ "ctrl-affected-person-notice" ], "gateIds": [ "control", "measure" ], "sourceIds": [ "src-eu-ai-act", "src-eu-article50-guidelines", "src-wcag-22" ], "caveat": "Delivery does not establish comprehension, legal adequacy or that all eligible events were detected." }, { "indicatorId": "kpi-appeal-resolution-sla", "type": "KPI", "name": "Appeals resolved within approved service level", "purpose": "Track timely, reasoned and conflict-independent review of affected-person appeals.", "formula": "eligible appeals resolved within approved deadline / eligible resolved appeals * 100", "cadence": "monthly", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85% or any urgent case overdue" }, "controlIds": [ "ctrl-appeal-remedy" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42005" ], "caveat": "Speed does not establish reviewer independence, procedural fairness or remedy effectiveness." }, { "indicatorId": "kri-overdue-remedy-rate", "type": "KRI", "name": "Overdue remedy rate", "purpose": "Surface accepted corrections, restoration or other remedies that remain incomplete beyond their accountable deadline.", "formula": "open remedies past due / open and completed remedies in period * 100", "cadence": "weekly", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "above 5% or any severe-harm remedy overdue" }, "controlIds": [ "ctrl-appeal-remedy" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-iso-42005" ], "caveat": "A closed remedy still requires evidence that the affected outcome was actually corrected." }, { "indicatorId": "kpi-machine-readable-marking-coverage", "type": "KPI", "name": "Machine-readable synthetic-content marking coverage", "purpose": "Track successful application and independent detection of configured marks on in-scope generated or manipulated content.", "formula": "in-scope content samples with independently detected valid marks / tested in-scope content samples * 100", "cadence": "per release and daily production sample", "direction": "higher-is-better", "thresholds": { "amber": "below 99%", "red": "below 95% or any systematically unmarked modality" }, "controlIds": [ "ctrl-article50-transparency" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-eu-article50-guidelines" ], "caveat": "Mark detection in a test set does not prove robustness after downstream transformation or legal sufficiency." }, { "indicatorId": "kri-provenance-verification-failure-rate", "type": "KRI", "name": "Content provenance verification failure rate", "purpose": "Detect missing, invalid or broken content-provenance assertions in in-scope outputs.", "formula": "content samples with missing or invalid expected provenance / tested content samples * 100", "cadence": "daily with release review", "direction": "lower-is-better", "thresholds": { "amber": "above 1%", "red": "above 5% or any unexplained signing-key failure" }, "controlIds": [ "ctrl-article50-transparency" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-eu-article50-guidelines" ], "caveat": "Provenance assertions indicate origin and processing claims; they do not establish that content is truthful." }, { "indicatorId": "kpi-data-lifecycle-coverage", "type": "KPI", "name": "Material data lifecycle coverage", "purpose": "Track complete records for origin, transformations, permissions, quality, purpose, retention and disposition of material data assets.", "formula": "material data assets with accepted lifecycle records / identified material data assets * 100", "cadence": "monthly and before material change", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85% or any unrecorded sensitive dataset" }, "controlIds": [ "ctrl-data-governance-lifecycle", "ctrl-privacy-lifecycle" ], "gateIds": [ "frame", "assess", "control", "prove" ], "sourceIds": [ "src-eu-gdpr", "src-eu-ai-act", "src-nist-ai-rmf" ], "caveat": "Record completeness does not prove that permissions, lawful basis, quality or retention decisions are correct." }, { "indicatorId": "kpi-annotation-quality-coverage", "type": "KPI", "name": "Annotation quality assurance coverage", "purpose": "Track whether material annotated datasets have current protocols, competence evidence, sampling and agreement results.", "formula": "material annotated datasets with accepted QA evidence / material annotated datasets * 100", "cadence": "per dataset release and quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any production dataset without an accepted QA sample" }, "controlIds": [ "ctrl-annotation-quality" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-nist-ai-rmf", "src-iso-42005" ], "caveat": "Agreement can be high while instructions or ground truth remain biased or conceptually invalid." }, { "indicatorId": "kpi-deletion-verification-coverage", "type": "KPI", "name": "Due data deletion verification coverage", "purpose": "Track verified deletion or approved legal hold across primary data, replicas, embeddings, caches and derived artifacts.", "formula": "due deletion items with verified disposition or approved hold / due deletion items * 100", "cadence": "weekly", "direction": "higher-is-better", "thresholds": { "amber": "below 99%", "red": "below 95% or any sensitive-data deadline missed" }, "controlIds": [ "ctrl-data-governance-lifecycle", "ctrl-privacy-lifecycle" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-eu-gdpr" ], "caveat": "Verification scope must explicitly cover backups, immutable records and technically non-deletable derived artifacts." }, { "indicatorId": "kpi-gpai-obligation-evidence-coverage", "type": "KPI", "name": "Applicable GPAI obligation evidence coverage", "purpose": "Track accepted evidence for each provider, deployer or integrator obligation activated by the role assessment.", "formula": "applicable GPAI obligations with accepted evidence / applicable GPAI obligations * 100", "cadence": "monthly and before release or material modification", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any overdue mandatory evidence item" }, "controlIds": [ "ctrl-gpai-provider", "ctrl-gpai-deployer" ], "gateIds": [ "classify", "control", "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-eu-gpai-code" ], "caveat": "The denominator depends on a legally reviewed role and applicability assessment." }, { "indicatorId": "kri-systemic-risk-finding-rate", "type": "KRI", "name": "Unresolved material systemic-risk finding rate", "purpose": "Track material model-capability, misuse, cyber, autonomy, societal or cascading-risk findings without accepted mitigation.", "formula": "unresolved material systemic-risk findings / executed systemic-risk scenarios * 100", "cadence": "per model release and monthly", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any critical finding or untested critical scenario" }, "controlIds": [ "ctrl-systemic-risk" ], "gateIds": [ "assess", "control", "measure", "prove" ], "sourceIds": [ "src-eu-gpai-code", "src-nist-genai-profile" ], "caveat": "Scenario selection and model-access constraints can materially understate systemic risk." }, { "indicatorId": "kpi-regulatory-reporting-clock-compliance", "type": "KPI", "name": "Applicable regulatory reporting clock compliance", "purpose": "Track on-time initial and follow-up notifications for incidents determined reportable in each jurisdiction.", "formula": "required notifications submitted within applicable clock / required notifications * 100", "cadence": "continuous with monthly review", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any missed mandatory reporting deadline" }, "controlIds": [ "ctrl-regulatory-incident-reporting" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-eu-ai-act" ], "caveat": "Timeliness depends on correct detection, jurisdiction mapping, reportability analysis and clock-start evidence." }, { "indicatorId": "kpi-decommissioning-evidence-coverage", "type": "KPI", "name": "Decommissioning evidence coverage", "purpose": "Track completion of customer transition, capability revocation, data disposition, residual monitoring and closure evidence.", "formula": "accepted due decommissioning evidence items / due decommissioning evidence items * 100", "cadence": "weekly during retirement and at closure", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any unresolved safety, access or sensitive-data item at closure" }, "controlIds": [ "ctrl-decommissioning" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf" ], "caveat": "An evidence item can be present while downstream copies, user dependencies or residual harms remain." }, { "indicatorId": "kpi-accessibility-test-pass-rate", "type": "KPI", "name": "Applicable accessibility test pass rate", "purpose": "Measure supported interface, notice, explanation, generated-output and remedy scenarios that meet approved accessibility criteria.", "formula": "passed applicable accessibility scenarios / executed applicable accessibility scenarios * 100", "cadence": "per release and quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 98%", "red": "below 95% or any critical journey blocked" }, "controlIds": [ "ctrl-ai-output-accessibility" ], "gateIds": [ "assess", "control", "measure", "prove" ], "sourceIds": [ "src-wcag-22" ], "caveat": "Automated conformance checks must be supplemented by manual assistive-technology and representative-user evaluation." }, { "indicatorId": "kri-accessibility-blocker-rate", "type": "KRI", "name": "Unresolved accessibility blocker rate", "purpose": "Surface critical user journeys that disabled users cannot complete independently or through an equivalent route.", "formula": "unresolved blocked critical journeys / tested critical journeys * 100", "cadence": "per release and weekly while blockers are open", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any high-impact notice, review or remedy journey blocked" }, "controlIds": [ "ctrl-ai-output-accessibility" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-wcag-22", "src-iso-42005" ], "caveat": "The tested journey inventory must include supported modalities, languages and assistive technologies." }, { "indicatorId": "kpi-energy-measurement-coverage", "type": "KPI", "name": "Material AI energy measurement coverage", "purpose": "Track energy measurements or documented estimation methods for material training, evaluation and inference workloads.", "formula": "material AI workloads with accepted energy measurement or estimate / material AI workloads * 100", "cadence": "monthly and per release", "direction": "higher-is-better", "thresholds": { "amber": "below 90%", "red": "below 75% or no baseline for a material workload" }, "controlIds": [ "ctrl-environmental-performance" ], "gateIds": [ "assess", "measure", "prove" ], "sourceIds": [ "src-iso-42001", "src-iso-42005" ], "caveat": "Estimates must state boundaries, allocation assumptions, location and temporal electricity factors." }, { "indicatorId": "kri-environmental-budget-variance", "type": "KRI", "name": "Environmental budget variance", "purpose": "Detect material energy, emissions, water or hardware impacts above approved lifecycle budgets.", "formula": "actual or estimated impact minus approved budget, divided by approved budget * 100", "cadence": "monthly and per release", "direction": "within-range", "thresholds": { "amber": "more than 10% above budget", "red": "more than 25% above budget or any unapproved material regression" }, "controlIds": [ "ctrl-environmental-performance" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-iso-42001", "src-iso-42005" ], "caveat": "Budgets and calculations require organization-specific boundaries and should not hide absolute impacts behind efficiency ratios." }, { "indicatorId": "kpi-ai-literacy-competence-rate", "type": "KPI", "name": "Role-based AI competence demonstration rate", "purpose": "Measure whether people in AI roles demonstrate the required knowledge and practical control behavior for their responsibilities.", "formula": "in-scope people passing current role-based competence assessment / in-scope people * 100", "cadence": "quarterly and after material role or system change", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85% or any unqualified high-authority role" }, "controlIds": [ "ctrl-ai-literacy-effectiveness" ], "gateIds": [ "frame", "control", "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42001" ], "caveat": "Attendance or quiz completion alone is insufficient; assessment must test role-relevant judgment and control use." }, { "indicatorId": "kri-trained-control-error-rate", "type": "KRI", "name": "Post-training control error rate", "purpose": "Detect repeated governance or operational errors by trained roles that indicate ineffective learning or unclear procedures.", "formula": "confirmed role-relevant control errors by currently trained people / reviewed role-relevant actions * 100", "cadence": "monthly", "direction": "lower-is-better", "thresholds": { "amber": "above 2%", "red": "above 5% or any severe preventable error" }, "controlIds": [ "ctrl-ai-literacy-effectiveness" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-eu-ai-act", "src-iso-42001" ], "caveat": "Error attribution must account for system, procedure, workload and authority-design failures rather than blaming individuals by default." }, { "indicatorId": "kpi-aims-objective-coverage", "type": "KPI", "name": "AIMS objective measurement coverage", "purpose": "Track measurable, owned and reviewed objectives for material AI management risks and opportunities within the declared AIMS scope.", "formula": "applicable AIMS objectives with owner, measure, target and review evidence / applicable AIMS objectives * 100", "cadence": "quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any material risk without an owned measurable objective" }, "controlIds": [ "ctrl-aims-leadership-objectives", "ctrl-aims-management-review-capa" ], "gateIds": [ "frame", "classify", "measure", "prove" ], "sourceIds": [ "src-iso-42001" ], "caveat": "Coverage does not establish ISO/IEC 42001 conformity or the adequacy of selected objectives." }, { "indicatorId": "kpi-aims-audit-completion", "type": "KPI", "name": "Risk-based AIMS audit completion", "purpose": "Track completion and accountable reporting of planned internal audits within the approved programme.", "formula": "completed planned audits with accepted report / audits due in period * 100", "cadence": "quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85% or any critical scope repeatedly unaudited" }, "controlIds": [ "ctrl-aims-internal-audit" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-iso-42001" ], "caveat": "Completion does not establish auditor competence, independence, audit depth or certification." }, { "indicatorId": "kpi-corrective-action-closure", "type": "KPI", "name": "Corrective action effective closure", "purpose": "Track timely closure of nonconformities only after root-cause and effectiveness evidence is accepted.", "formula": "corrective actions closed on time with accepted effectiveness check / corrective actions due * 100", "cadence": "monthly", "direction": "higher-is-better", "thresholds": { "amber": "below 95%", "red": "below 85% or any critical nonconformity overdue" }, "controlIds": [ "ctrl-aims-internal-audit", "ctrl-aims-management-review-capa" ], "gateIds": [ "measure", "prove" ], "sourceIds": [ "src-iso-42001" ], "caveat": "Administrative closure without effectiveness verification must not count as completed." }, { "indicatorId": "kpi-production-admission-coverage", "type": "KPI", "name": "PALO-AI production admission evidence coverage", "purpose": "Track accepted identity, tenancy, persistence, key-custody, connector, recovery and bypass-resistance evidence before production admission.", "formula": "accepted mandatory production admission checks / applicable mandatory production admission checks * 100", "cadence": "per release and quarterly", "direction": "higher-is-better", "thresholds": { "amber": "below 100%", "red": "any mandatory check absent, failed or expired" }, "controlIds": [ "ctrl-runtime-production-boundary" ], "gateIds": [ "classify", "control", "measure", "prove" ], "sourceIds": [ "src-iso-42001", "src-nist-ai-rmf" ], "caveat": "Passing repository checks is not production admission; operational and independent evidence must match the deployed environment." }, { "indicatorId": "kri-execution-bypass-rate", "type": "KRI", "name": "Protected action bypass rate", "purpose": "Detect consequential actions reaching external systems without a current claim, decision, capability, receipt and outcome-verification chain.", "formula": "protected external effects without a valid complete governance chain / protected external effects * 100", "cadence": "continuous with daily review", "direction": "lower-is-better", "thresholds": { "amber": "above 0%", "red": "any consequential bypass or unverifiable external effect" }, "controlIds": [ "ctrl-runtime-production-boundary" ], "gateIds": [ "control", "measure", "prove" ], "sourceIds": [ "src-nist-ai-rmf", "src-owasp-llm-top10" ], "caveat": "The metric requires independent observation of external effects; runtime self-report alone cannot prove non-bypassability." } ] Semantic spine nodes (46) Source: data/semantic-spine.json · Download full registry [ { "id": "frame", "label": "Frame", "number": "01", "type": "stage", "phaseId": "frame", "role": "Define the use case, its boundary, owners and affected people before governance choices are made.", "status": "Operational phase", "properties": { "Core question": "What are we building, for whom, and why?", "Lifecycle": "Phase 1 Ideation", "Decision gate": "Is the use case sufficiently defined to classify?" }, "outputs": [ "Use-case brief" ], "action": "Describe purpose, scope, owners, affected people and the decision boundary.", "intents": [ "what should I do first", "start governance", "define use case", "assign owner" ], "stakeholders": [ "accountable owner", "product", "governance" ], "href": "#frame", "semanticId": "https://paloframework.org/semantic/stage/frame", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "classify", "label": "Classify", "number": "02", "type": "stage", "phaseId": "classify", "role": "Establish the applicable risk route, obligations and level of scrutiny.", "status": "Operational phase", "properties": { "Core question": "What route, obligations, and level of scrutiny apply?", "Lifecycle": "Phases 1-2 Screening and Assessment", "Decision gate": "Is the initial risk route justified and current?" }, "outputs": [ "Risk route" ], "action": "Run the initial risk route and verify current obligations against official sources.", "intents": [ "classify risk", "risk tier", "applicable obligations", "high risk" ], "stakeholders": [ "legal", "risk", "governance" ], "href": "#classify", "semanticId": "https://paloframework.org/semantic/stage/classify", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "assess", "label": "Assess", "number": "03", "type": "stage", "phaseId": "assess", "role": "Evaluate impacts, rights, delegated authority, autonomy and oversight conditions.", "status": "Operational phase", "properties": { "Core question": "What impacts, rights, authority, and oversight conditions exist?", "Lifecycle": "Phase 2 Assessment and Planning", "Decision gate": "Are impacts and delegated authority understood well enough to control?" }, "outputs": [ "Impact assessment record" ], "action": "Evaluate impacts, fundamental rights, authority, autonomy and human oversight.", "intents": [ "fundamental rights", "agent autonomy", "assess impact", "human oversight" ], "stakeholders": [ "legal", "risk", "product", "public sector" ], "href": "#assess", "semanticId": "https://paloframework.org/semantic/stage/assess", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "control", "label": "Control", "number": "04", "type": "stage", "phaseId": "control", "role": "Translate findings into owned, testable engineering, process and assurance controls.", "status": "Operational phase", "properties": { "Core question": "Which controls make the identified risks governable?", "Lifecycle": "Phases 2-3 Planning, Development, and Validation", "Decision gate": "Are controls implemented, testable, and owned?" }, "outputs": [ "Control plan" ], "action": "Convert findings into owned controls with tests, evidence and decision gates.", "intents": [ "select controls", "implement controls", "assurance test", "development governance" ], "stakeholders": [ "engineering", "product", "assurance" ], "href": "#control", "semanticId": "https://paloframework.org/semantic/stage/control", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "measure", "label": "Measure", "number": "05", "type": "stage", "phaseId": "measure", "role": "Define how accountability, performance, risk and drift will be observed over time.", "status": "Operational phase", "properties": { "Core question": "How will accountability, performance, risk, and drift be observed?", "Lifecycle": "Phase 2 definition and Phase 4 monitoring", "Decision gate": "Can the team detect deterioration and act?" }, "outputs": [ "KPI/KRI register" ], "action": "Define indicators, thresholds, owners and cadence, then monitor material change.", "intents": [ "KPI", "KRI", "monitor change", "drift", "threshold" ], "stakeholders": [ "operations", "assurance", "board" ], "href": "#measure", "semanticId": "https://paloframework.org/semantic/stage/measure", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "prove", "label": "Prove & Review", "number": "06", "type": "stage", "phaseId": "prove", "role": "Assemble reconstructable evidence, decide readiness and feed findings into the next cycle.", "status": "Operational phase", "properties": { "Core question": "Can the decision be reconstructed, reviewed, and improved?", "Lifecycle": "Phases 4-5 Deployment, Review, and Decommissioning", "Decision gate": "Is the evidence complete enough for an accountable decision?" }, "outputs": [ "Versioned evidence bundle", "Next-cycle update" ], "action": "Assemble versioned evidence, review readiness and record the accountable decision.", "intents": [ "board evidence", "evidence bundle", "prove decision", "review readiness" ], "stakeholders": [ "board", "executive", "audit", "assurance" ], "href": "#prove", "semanticId": "https://paloframework.org/semantic/stage/prove", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "model-canvas", "label": "AI Model Canvas", "type": "module", "phaseId": "frame", "role": "Structures purpose, scope, ownership and assumptions.", "status": "Available", "href": "../../PALO_ModelCanvasAI.html", "properties": { "When to use": "At initiation and after material scope change", "Key properties": "purpose, scope, owners, stakeholders, lifecycle, assumptions", "Weight": "W5 Core" }, "outputs": [ "Structured Canvas", "JSON/Markdown record" ], "weight": "W5", "action": "At initiation and after material scope change", "intents": [ "what should I do first", "start governance", "define use case", "assign owner" ], "stakeholders": [ "accountable owner", "product", "governance" ], "semanticId": "https://paloframework.org/semantic/module/model-canvas", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-ai-rmf" ], "lastReviewed": "2026-08-12" }, { "id": "agency-map", "label": "Human Agency Risk Map", "type": "module", "phaseId": "frame", "role": "Maps delegated activity and potential effects on human agency.", "status": "Available", "href": "../../PALO_HumanAgencyRiskMap.html", "properties": { "When to use": "When systems influence or replace human decisions", "Key properties": "delegated activity, affected agency, oversight need", "Weight": "W3 Contextual" }, "outputs": [ "Agency-risk context" ], "weight": "W3", "action": "When systems influence or replace human decisions", "intents": [ "what should I do first", "start governance", "define use case", "assign owner" ], "stakeholders": [ "accountable owner", "product", "governance" ], "semanticId": "https://paloframework.org/semantic/module/agency-map", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-oecd-ai-principles" ], "lastReviewed": "2026-08-12" }, { "id": "tech-trends", "label": "Tech Trends Observatory", "type": "module", "phaseId": "frame", "role": "Adds technology and horizon signals to the use-case context.", "status": "Reference", "href": "../../PALO_TechTrends2026.html", "properties": { "When to use": "For emerging capabilities or uncertain technical trajectories", "Key properties": "technology signal, horizon, governance impact", "Weight": "W2 Supporting" }, "outputs": [ "Horizon context" ], "weight": "W2", "action": "For emerging capabilities or uncertain technical trajectories", "intents": [ "what should I do first", "start governance", "define use case", "assign owner" ], "stakeholders": [ "accountable owner", "product", "governance" ], "semanticId": "https://paloframework.org/semantic/module/tech-trends", "definitionVersion": "3.0.0", "evidenceClass": "source-backed-context", "authorityBoundary": "Source-backed context informs governance work but does not independently determine legal applicability, compliance, or deployment authorization.", "sourceRefs": [ "src-nist-ai-rmf" ], "lastReviewed": "2026-08-12" }, { "id": "risk-tiering", "label": "Risk Tiering Calculator", "type": "module", "phaseId": "classify", "role": "Routes the use case through an initial EU AI Act risk screen.", "status": "Available", "href": "../../PALO_RiskTiering.html", "properties": { "When to use": "For every use case before detailed assessment", "Key properties": "tier, prohibited-practice signals, high-risk context", "Weight": "W5 Core" }, "outputs": [ "Markdown risk report" ], "weight": "W5", "action": "For every use case before detailed assessment", "intents": [ "classify risk", "risk tier", "applicable obligations", "high risk" ], "stakeholders": [ "legal", "risk", "governance" ], "semanticId": "https://paloframework.org/semantic/module/risk-tiering", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-eu-ai-act" ], "lastReviewed": "2026-08-12" }, { "id": "comparison", "label": "Framework Comparison", "type": "module", "phaseId": "classify", "role": "Cross-checks overlapping governance frameworks and gaps.", "status": "Available", "href": "../../PALO_ComparisonTool.html", "properties": { "When to use": "When multiple standards or frameworks apply", "Key properties": "applicable framework, overlap, gaps", "Weight": "W3 Contextual" }, "outputs": [ "Comparison record" ], "weight": "W3", "action": "When multiple standards or frameworks apply", "intents": [ "classify risk", "risk tier", "applicable obligations", "high risk" ], "stakeholders": [ "legal", "risk", "governance" ], "semanticId": "https://paloframework.org/semantic/module/comparison", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-ai-rmf", "src-iso-42001" ], "lastReviewed": "2026-08-12" }, { "id": "reg-watch", "label": "Regulatory Watch 2026", "type": "module", "phaseId": "classify", "role": "Keeps the route anchored to current official sources.", "status": "Reviewed source", "href": "../../PALO_RegulatoryWatch.html", "properties": { "When to use": "At classification and each formal review", "Key properties": "article, date, status, source", "Weight": "W4 Strong" }, "outputs": [ "Current obligation context" ], "weight": "W4", "action": "At classification and each formal review", "intents": [ "classify risk", "risk tier", "applicable obligations", "high risk" ], "stakeholders": [ "legal", "risk", "governance" ], "semanticId": "https://paloframework.org/semantic/module/reg-watch", "definitionVersion": "3.0.0", "evidenceClass": "source-backed-context", "authorityBoundary": "Source-backed context informs governance work but does not independently determine legal applicability, compliance, or deployment authorization.", "sourceRefs": [ "src-eu-ai-act" ], "lastReviewed": "2026-08-12" }, { "id": "fria", "label": "FRIA Assessment", "type": "module", "phaseId": "assess", "role": "Evaluates fundamental-rights impact scenarios and mitigations.", "status": "Available", "href": "../../PALO_FRIA.html", "properties": { "When to use": "When deployment may affect people or protected rights", "Key properties": "affected right, scenario, likelihood, gravity, reversibility, mitigation", "Weight": "W4 Strong" }, "outputs": [ "FRIA JSON/Markdown/template" ], "weight": "W4", "action": "When deployment may affect people or protected rights", "intents": [ "fundamental rights", "agent autonomy", "assess impact", "human oversight" ], "stakeholders": [ "legal", "risk", "product", "public sector" ], "semanticId": "https://paloframework.org/semantic/module/fria", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-eu-ai-act" ], "lastReviewed": "2026-08-12" }, { "id": "palo-am", "label": "PALO-AM", "type": "module", "phaseId": "assess", "role": "Examines identity, authority and action space in agentic systems.", "status": "Available", "href": "../../PALO_AgenticGovernance.html", "properties": { "When to use": "For agents, tools and delegated action", "Key properties": "identity, authority, tools, action space, autonomy, oversight", "Weight": "W4 Strong" }, "outputs": [ "Agentic governance record" ], "weight": "W4", "action": "For agents, tools and delegated action", "intents": [ "fundamental rights", "agent autonomy", "assess impact", "human oversight" ], "stakeholders": [ "legal", "risk", "product", "public sector" ], "semanticId": "https://paloframework.org/semantic/module/palo-am", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-ai-rmf", "src-iso-42001" ], "lastReviewed": "2026-08-12" }, { "id": "assessment-path", "label": "Assessment Path", "type": "module", "phaseId": "assess", "role": "Connects context, risk route, readiness and sources.", "status": "Available", "href": "../../PALO_AssessmentPath.html", "properties": { "When to use": "As the backbone of the contextual assessment", "Key properties": "context, route, readiness, sources", "Weight": "W5 Core" }, "outputs": [ "Contextual assessment record", "Evidence bundle" ], "weight": "W5", "action": "As the backbone of the contextual assessment", "intents": [ "fundamental rights", "agent autonomy", "assess impact", "human oversight" ], "stakeholders": [ "legal", "risk", "product", "public sector" ], "semanticId": "https://paloframework.org/semantic/module/assessment-path", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-ai-rmf" ], "lastReviewed": "2026-08-12" }, { "id": "vibe", "label": "Vibe Coding Governance", "type": "module", "phaseId": "control", "role": "Governs AI-assisted development through explicit delivery gates.", "status": "Available", "href": "../../PALO_VibeCoding.html", "properties": { "When to use": "When AI assists software development", "Key properties": "functional intent, controlled environment, evidence, delivery gates", "Weight": "W3 Contextual" }, "outputs": [ "AI-assisted development controls" ], "weight": "W3", "action": "When AI assists software development", "intents": [ "select controls", "implement controls", "assurance test", "development governance" ], "stakeholders": [ "engineering", "product", "assurance" ], "semanticId": "https://paloframework.org/semantic/module/vibe", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-genai-profile", "src-owasp-llm-top10" ], "lastReviewed": "2026-08-12" }, { "id": "auditbench", "label": "AuditBench Explorer", "type": "module", "phaseId": "control", "role": "Tests hidden behavior and alignment evidence.", "status": "Available", "href": "../../PALO_AuditBench.html", "properties": { "When to use": "During validation and assurance", "Key properties": "hidden behavior, audit technique, test status", "Weight": "W3 Contextual" }, "outputs": [ "Alignment audit assessment/report" ], "weight": "W3", "action": "During validation and assurance", "intents": [ "select controls", "implement controls", "assurance test", "development governance" ], "stakeholders": [ "engineering", "product", "assurance" ], "semanticId": "https://paloframework.org/semantic/module/auditbench", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-genai-profile" ], "lastReviewed": "2026-08-12" }, { "id": "poisoning", "label": "Poisoning Boomerang", "type": "module", "phaseId": "control", "role": "Frames data and model integrity threats across the lifecycle.", "status": "Reference", "href": "../../PALO_PoisoningStudy.html", "properties": { "When to use": "Where provenance or integrity risks are material", "Key properties": "threat, provenance, detection, integrity control", "Weight": "W3 Contextual" }, "outputs": [ "Data/model integrity controls" ], "weight": "W3", "action": "Where provenance or integrity risks are material", "intents": [ "select controls", "implement controls", "assurance test", "development governance" ], "stakeholders": [ "engineering", "product", "assurance" ], "semanticId": "https://paloframework.org/semantic/module/poisoning", "definitionVersion": "3.0.0", "evidenceClass": "source-backed-context", "authorityBoundary": "Source-backed context informs governance work but does not independently determine legal applicability, compliance, or deployment authorization.", "sourceRefs": [ "src-nist-ai-rmf" ], "lastReviewed": "2026-08-12" }, { "id": "kpi", "label": "KPI and KRI Generator", "type": "module", "phaseId": "measure", "role": "Creates the measurable indicator set for governance monitoring.", "status": "Available", "href": "../../PALO_KPIGenerator.html", "properties": { "When to use": "When controls need observable performance and risk signals", "Current properties": "category, indicator, definition, formula", "Required downstream": "threshold, owner, cadence, current value, status", "Weight": "W5 Core" }, "outputs": [ "CSV/Markdown indicator set" ], "weight": "W5", "action": "When controls need observable performance and risk signals", "intents": [ "KPI", "KRI", "monitor change", "drift", "threshold" ], "stakeholders": [ "operations", "assurance", "board" ], "semanticId": "https://paloframework.org/semantic/module/kpi", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [ "src-nist-ai-rmf", "src-iso-42001" ], "lastReviewed": "2026-08-12" }, { "id": "toolbox", "label": "P.A.L.O. Toolbox", "type": "module", "phaseId": "measure", "role": "Captures portable operational evidence locally.", "status": "Android and iOS", "href": "../../PALO_CompanionApp.html", "properties": { "When to use": "During field work and ongoing evidence capture", "Key properties": "local record, Evidence Vault, portable report", "Weight": "W3 Contextual" }, "outputs": [ "Local operational evidence", "Portable evidence package" ], "weight": "W3", "action": "During field work and ongoing evidence capture", "intents": [ "KPI", "KRI", "monitor change", "drift", "threshold" ], "stakeholders": [ "operations", "assurance", "board" ], "semanticId": "https://paloframework.org/semantic/module/toolbox", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "docs", "label": "Documentation Library", "type": "module", "phaseId": "prove", "role": "Connects evidence to lifecycle guidance and source artifacts.", "status": "Available", "href": "../../PALO_DocumentationLibrary.html", "properties": { "When to use": "When reconstructing decisions or preparing review", "Key properties": "lifecycle guidance, source artifact, version", "Weight": "W4 Strong" }, "outputs": [ "Source and guidance context" ], "weight": "W4", "action": "When reconstructing decisions or preparing review", "intents": [ "board evidence", "evidence bundle", "prove decision", "review readiness" ], "stakeholders": [ "board", "executive", "audit", "assurance" ], "semanticId": "https://paloframework.org/semantic/module/docs", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "brief", "label": "Use-case brief", "type": "artifact", "phaseId": "frame", "role": "Versioned operational output transferred to the next governance decision.", "status": "Produced output", "properties": { "Owner": "Assigned by the operating team", "Versioning": "Required", "Review state": "Tracked in the evidence path" }, "outputs": [ "Use-case brief" ], "action": "Create, version and hand this artifact to the next accountable decision.", "intents": [ "what should I do first", "start governance", "define use case", "assign owner", "Use-case brief" ], "stakeholders": [ "accountable owner", "product", "governance" ], "semanticId": "https://paloframework.org/semantic/artifact/brief", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "route", "label": "Risk route", "type": "artifact", "phaseId": "classify", "role": "Versioned operational output transferred to the next governance decision.", "status": "Produced output", "properties": { "Owner": "Assigned by the operating team", "Versioning": "Required", "Review state": "Tracked in the evidence path" }, "outputs": [ "Risk route" ], "action": "Create, version and hand this artifact to the next accountable decision.", "intents": [ "classify risk", "risk tier", "applicable obligations", "high risk", "Risk route" ], "stakeholders": [ "legal", "risk", "governance" ], "semanticId": "https://paloframework.org/semantic/artifact/route", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "impact-record", "label": "Impact assessment record", "type": "artifact", "phaseId": "assess", "role": "Versioned operational output transferred to the next governance decision.", "status": "Produced output", "properties": { "Owner": "Assigned by the operating team", "Versioning": "Required", "Review state": "Tracked in the evidence path" }, "outputs": [ "Impact assessment record" ], "action": "Create, version and hand this artifact to the next accountable decision.", "intents": [ "fundamental rights", "agent autonomy", "assess impact", "human oversight", "Impact assessment record" ], "stakeholders": [ "legal", "risk", "product", "public sector" ], "semanticId": "https://paloframework.org/semantic/artifact/impact-record", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "control-plan", "label": "Control plan", "type": "artifact", "phaseId": "control", "role": "Versioned operational output transferred to the next governance decision.", "status": "Produced output", "properties": { "Owner": "Assigned by the operating team", "Versioning": "Required", "Review state": "Tracked in the evidence path" }, "outputs": [ "Control plan" ], "action": "Create, version and hand this artifact to the next accountable decision.", "intents": [ "select controls", "implement controls", "assurance test", "development governance", "Control plan" ], "stakeholders": [ "engineering", "product", "assurance" ], "semanticId": "https://paloframework.org/semantic/artifact/control-plan", "definitionVersion": "3.0.0", "evidenceClass": "canonical-definition", "authorityBoundary": "Canonical PALO framework definition; it structures governance but does not create legal obligations or authorize deployment.", "sourceRefs": [], "lastReviewed": "2026-08-12" }, { "id": "indicator-register", "label": "KPI/KRI register", "type": "artifact", "phaseId": "measure", 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data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-sensitive-data-events/src-eu-ai-act", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-sensitive-data-events", "semanticId": "https://paloframework.org/semantic/indicator/kri-sensitive-data-events?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-eu-ai-act", "semanticId": 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"entityType": "indicator", "entityId": "kri-sensitive-data-events", "semanticId": "https://paloframework.org/semantic/indicator/kri-sensitive-data-events?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-nist-ai-rmf", "semanticId": "https://paloframework.org/semantic/source/src-nist-ai-rmf?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-systemic-risk-finding-rate/src-eu-gpai-code", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-systemic-risk-finding-rate", "semanticId": "https://paloframework.org/semantic/indicator/kri-systemic-risk-finding-rate?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-eu-gpai-code", "semanticId": "https://paloframework.org/semantic/source/src-eu-gpai-code?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-systemic-risk-finding-rate/src-nist-genai-profile", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-systemic-risk-finding-rate", "semanticId": "https://paloframework.org/semantic/indicator/kri-systemic-risk-finding-rate?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-nist-genai-profile", "semanticId": "https://paloframework.org/semantic/source/src-nist-genai-profile?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-tool-call-error-rate/src-nist-ai-rmf", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-tool-call-error-rate", "semanticId": "https://paloframework.org/semantic/indicator/kri-tool-call-error-rate?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-nist-ai-rmf", "semanticId": "https://paloframework.org/semantic/source/src-nist-ai-rmf?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-trained-control-error-rate/src-eu-ai-act", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-trained-control-error-rate", "semanticId": "https://paloframework.org/semantic/indicator/kri-trained-control-error-rate?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-eu-ai-act", "semanticId": "https://paloframework.org/semantic/source/src-eu-ai-act?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } }, { "mappingId": "https://paloframework.org/semantic/mapping/indicator-to-source/kri-trained-control-error-rate/src-iso-42001", "mappingVersion": "1.0.0", "mappingType": "indicator-to-source", "source": { "entityType": "indicator", "entityId": "kri-trained-control-error-rate", "semanticId": "https://paloframework.org/semantic/indicator/kri-trained-control-error-rate?v=3.1.0", "version": "3.1.0" }, "target": { "entityType": "source", "entityId": "src-iso-42001", "semanticId": "https://paloframework.org/semantic/source/src-iso-42001?v=1.0.0", "version": "1.0.0" }, "coverageType": "supporting", "conditions": [], "rationale": "The source informs the indicator definition; the published threshold remains illustrative.", "basis": "Declared relationship in data/kpi-kri-registry.json; no legal-equivalence or compliance claim is created.", "approval": { "status": "approved", "scope": "PALO framework publication only; not a legal applicability or certification decision.", "decidedAt": "2026-08-23T08:00:00Z", "decidedBy": "PALO framework release process" }, "validFrom": "2026-08-23T00:00:00Z", "provenance": { "generatedFrom": "data/kpi-kri-registry.json", "generationRule": "indicator-to-source: one immutable source-target pair per declared ID reference." } } ] Fourteen declared invariants (14) Source: data/semantic-invariants.json · Download full registry [ { "invariantId": "SEM-01", "statement": "Every semantic entity has exactly one stable identifier.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-02", "statement": "Every canonical definition has exactly one semantic version.", "enforcedBy": [ "SHACL", "generator" ] }, { "invariantId": "SEM-03", "statement": "Released definitions are superseded, never overwritten.", "enforcedBy": [ "release validation", "documentation" ] }, { "invariantId": "SEM-04", "statement": "Lifecycle definitions, phase definitions and gate definitions are distinct from runtime instances.", "enforcedBy": [ "OWL", "JSON Schema" ] }, { "invariantId": "SEM-05", "statement": "Every gate instance references exactly one versioned gate definition and one case.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-06", "statement": "Every consequential gate decision is append-only, digest-bound and attributable.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-07", "statement": "An evidence claim references exactly one artifact, one target and one case scope.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-08", "statement": "Evidence evaluation is separate from evidence assertion.", "enforcedBy": [ "OWL", "SHACL" ] }, { "invariantId": "SEM-09", "statement": "Evidence bundles are manifests of digest-bound records, not duplicate evidence stores.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-10", "statement": "Each cross-framework mapping represents one source version and one target version.", "enforcedBy": [ "SHACL", "JSON Schema" ] }, { "invariantId": "SEM-11", "statement": "Every assessment and evidence manifest is pinned to an immutable semantic release manifest.", "enforcedBy": [ "SHACL", "release validation" ] }, { "invariantId": "SEM-12", "statement": "Delivery status and evidence authority class remain separate properties.", "enforcedBy": [ "semantic spine schema", "browser tests" ] }, { "invariantId": "SEM-13", "statement": "Framework guidance does not create legal obligations or deployment authorization.", "enforcedBy": [ "authority boundary", "documentation" ] }, { "invariantId": "SEM-14", "statement": "Non-authoritative monitoring signals require accountable human review before changing case state.", "enforcedBy": [ "semantic spine schema", "module contract" ] } ] Draft stack entity types (25) Source: data/stack-governance-model.json · Download full registry [ { "id": "Layer", "semanticId": "https://paloframework.org/semantic/Layer", "origin": "stack-extension-0.1" }, { "id": "Capability", "semanticId": "https://paloframework.org/semantic/Capability", "origin": "stack-extension-0.1" }, { "id": "GovernancePlane", "semanticId": "https://paloframework.org/semantic/GovernancePlane", "origin": "stack-extension-0.1" }, { "id": "ComponentVersion", "semanticId": "https://paloframework.org/semantic/ComponentVersion", "origin": "stack-extension-0.1" }, { "id": "AISystemVersion", "semanticId": "https://paloframework.org/semantic/AISystemVersion", "origin": "stack-extension-0.1" }, { "id": "Agent", "semanticId": "https://paloframework.org/semantic/Agent", "origin": "stack-extension-0.1" }, { "id": "ModelVersion", "semanticId": "https://paloframework.org/semantic/ModelVersion", "origin": "stack-extension-0.1" }, { "id": "Tool", "semanticId": "https://paloframework.org/semantic/Tool", "origin": "stack-extension-0.1" }, { "id": "DataAsset", "semanticId": "https://paloframework.org/semantic/DataAsset", "origin": "stack-extension-0.1" }, { "id": "Provider", "semanticId": "https://paloframework.org/semantic/Provider", "origin": "stack-extension-0.1" }, { "id": "Service", "semanticId": "https://paloframework.org/semantic/Service", "origin": "stack-extension-0.1" }, { "id": "PublicPolicy", "semanticId": "https://paloframework.org/semantic/PublicPolicy", "origin": "stack-extension-0.1" }, { "id": "PolicyVersion", "semanticId": "https://paloframework.org/semantic/PolicyVersion", "origin": "stack-extension-0.1" }, { "id": "ChangeSignal", "semanticId": "https://paloframework.org/semantic/ChangeSignal", "origin": "stack-extension-0.1" }, { "id": "GovernanceCase", "semanticId": "https://paloframework.org/semantic/GovernanceCase", "origin": "palo-3.1" }, { "id": "ApplicabilityAssessment", "semanticId": "https://paloframework.org/semantic/ApplicabilityAssessment", "origin": "stack-extension-0.1" }, { "id": "RequirementVersion", "semanticId": "https://paloframework.org/semantic/RequirementVersion", "origin": "stack-extension-0.1" }, { "id": "ControlDefinition", "semanticId": "https://paloframework.org/semantic/ControlDefinition", "origin": "stack-extension-0.1" }, { "id": "ControlImplementation", "semanticId": "https://paloframework.org/semantic/ControlImplementation", "origin": "palo-3.1" }, { "id": "EvidenceArtifact", "semanticId": "https://paloframework.org/semantic/EvidenceArtifact", "origin": "palo-3.1" }, { "id": "EvidenceClaim", "semanticId": "https://paloframework.org/semantic/EvidenceClaim", "origin": "palo-3.1" }, { "id": "EvidenceEvaluation", "semanticId": "https://paloframework.org/semantic/EvidenceEvaluation", "origin": "palo-3.1" }, { "id": "GateInstance", "semanticId": "https://paloframework.org/semantic/GateInstance", "origin": "palo-3.1" }, { "id": "GateDecisionRecord", "semanticId": "https://paloframework.org/semantic/GateDecisionRecord", "origin": "palo-3.1" }, { "id": "Actor", "semanticId": "https://paloframework.org/semantic/Actor", "origin": "stack-extension-0.1" } ] Draft stack relationship types (31) Source: data/stack-governance-model.json · Download full registry [ { "id": "PROVIDES_CAPABILITY", "sourceTypes": [ "ComponentVersion", "GovernancePlane" ], "targetTypes": [ "Capability" ], "meaning": "Provides capability within the recorded source, time and case scope." }, { "id": "BELONGS_TO_LAYER", "sourceTypes": [ "Capability" ], "targetTypes": [ "Layer" ], "meaning": "Belongs to layer within the recorded source, time and case scope." }, { "id": "GOVERNS_LAYER", "sourceTypes": [ "GovernancePlane" ], "targetTypes": [ "Layer" ], "meaning": "Governs layer within the recorded source, time and case scope." }, { "id": "INFORMS", "sourceTypes": [ "ComponentVersion" ], "targetTypes": [ "GovernancePlane" ], "meaning": "Informs within the recorded source, time and case scope." }, { "id": "OFFERS", "sourceTypes": [ "Provider" ], "targetTypes": [ "Service" ], "meaning": "Offers within the recorded source, time and case scope." }, { "id": "USES_SERVICE", "sourceTypes": [ "AISystemVersion", "Agent", "ComponentVersion", "Tool", "ModelVersion" ], "targetTypes": [ "Service" ], "meaning": "Uses service within the recorded source, time and case scope." }, { "id": "DEPENDS_ON", "sourceTypes": [ "AISystemVersion", "Agent", "ComponentVersion", "Tool", "ModelVersion" ], "targetTypes": [ "AISystemVersion", "Agent", "ComponentVersion", "Tool", "ModelVersion", "Service", "DataAsset" ], "meaning": "Depends on within the recorded source, time and case scope." }, { "id": "USES_MODEL", "sourceTypes": [ "AISystemVersion", "Agent" ], "targetTypes": [ "ModelVersion" ], "meaning": "Uses model within the recorded source, time and case scope." }, { "id": "CALLS_TOOL", "sourceTypes": [ "AISystemVersion", "Agent" ], "targetTypes": [ "Tool" ], "meaning": "Calls tool within the recorded source, time and case scope." }, { "id": "READS", "sourceTypes": [ "AISystemVersion", "Agent", "Tool" ], "targetTypes": [ "DataAsset" ], "meaning": "Reads within the recorded source, time and case scope." }, { "id": "HAS_VERSION", "sourceTypes": [ "PublicPolicy" ], "targetTypes": [ "PolicyVersion" ], "meaning": "Has version within the recorded source, time and case scope." }, { "id": "FROM_VERSION", "sourceTypes": [ "ChangeSignal" ], "targetTypes": [ "PolicyVersion" ], "meaning": "From version within the recorded source, time and case scope.", "maxPerSource": 1 }, { "id": "TO_VERSION", "sourceTypes": [ "ChangeSignal" ], "targetTypes": [ "PolicyVersion" ], "meaning": "To version within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "AFFECTS_SERVICE", "sourceTypes": [ "ChangeSignal" ], "targetTypes": [ "Service" ], "meaning": "Affects service within the recorded source, time and case scope." }, { "id": "GOVERNS_VERSION", "sourceTypes": [ "GovernanceCase" ], "targetTypes": [ "AISystemVersion" ], "meaning": "Governs version within the recorded source, time and case scope." }, { "id": "ASSESSES_SIGNAL", "sourceTypes": [ "ApplicabilityAssessment" ], "targetTypes": [ "ChangeSignal" ], "meaning": "Assesses signal within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "ASSESSES_SYSTEM", "sourceTypes": [ "ApplicabilityAssessment" ], "targetTypes": [ "AISystemVersion" ], "meaning": "Assesses system within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "IN_CASE", "sourceTypes": [ "ApplicabilityAssessment", "GateInstance", "ControlImplementation" ], "targetTypes": [ "GovernanceCase" ], "meaning": "In case within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "CONSIDERS_REQUIREMENT", "sourceTypes": [ "ApplicabilityAssessment" ], "targetTypes": [ "RequirementVersion" ], "meaning": "Considers requirement within the recorded source, time and case scope." }, { "id": "REVIEWED_BY", "sourceTypes": [ "ApplicabilityAssessment" ], "targetTypes": [ "Actor" ], "meaning": "Reviewed by within the recorded source, time and case scope.", "maxPerSource": 1 }, { "id": "IMPLEMENTS", "sourceTypes": [ "ControlImplementation" ], "targetTypes": [ "ControlDefinition" ], "meaning": "Implements within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "ADDRESSES_REQUIREMENT", "sourceTypes": [ "ControlDefinition" ], "targetTypes": [ "RequirementVersion" ], "meaning": "Addresses requirement within the recorded source, time and case scope." }, { "id": "APPLIES_TO_SYSTEM", "sourceTypes": [ "ControlImplementation" ], "targetTypes": [ "AISystemVersion" ], "meaning": "Applies to system within the recorded source, time and case scope.", "minPerSource": 1 }, { "id": "USES_ARTIFACT", "sourceTypes": [ "EvidenceClaim" ], "targetTypes": [ "EvidenceArtifact" ], "meaning": "Uses artifact within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "SUPPORTS_TARGET", "sourceTypes": [ "EvidenceClaim" ], "targetTypes": [ "ControlImplementation", "ApplicabilityAssessment" ], "meaning": "Supports target within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "EVALUATES_CLAIM", "sourceTypes": [ "EvidenceEvaluation" ], "targetTypes": [ "EvidenceClaim" ], "meaning": "Evaluates claim within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "REVIEWS_SYSTEM", "sourceTypes": [ "GateInstance" ], "targetTypes": [ "AISystemVersion" ], "meaning": "Reviews system within the recorded source, time and case scope.", "minPerSource": 1 }, { "id": "DECISION_FOR_GATE", "sourceTypes": [ "GateDecisionRecord" ], "targetTypes": [ "GateInstance" ], "meaning": "Decision for gate within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "DECIDED_BY", "sourceTypes": [ "GateDecisionRecord" ], "targetTypes": [ "Actor" ], "meaning": "Decided by within the recorded source, time and case scope.", "maxPerSource": 1, "minPerSource": 1 }, { "id": "BASED_ON_ASSESSMENT", "sourceTypes": [ "GateDecisionRecord" ], "targetTypes": [ "ApplicabilityAssessment" ], "meaning": "Based on assessment within the recorded source, time and case scope." }, { "id": "SUPERSEDES", "sourceTypes": [ "GateDecisionRecord" ], "targetTypes": [ "GateDecisionRecord" ], "meaning": "Supersedes within the recorded source, time and case scope.", "maxPerSource": 1 } ] ## RDF classes properties and shapes ### palo-ontology-v3.shacl.ttl 231 triples. Exact declarations follow; absence of a domain/range is preserved. | Shape | Target | Property constraints | palo:SemanticEntityShape | palo:SemanticEntity | 1 | palo:CanonicalDefinitionShape | palo:CanonicalDefinition | 1 | palo:ImmutableRecordShape | palo:ImmutableRecord | 3 | palo:LifecycleDefinitionShape | palo:LifecycleDefinition | 2 | palo:GateInstanceShape | palo:GateInstance | 3 | palo:GateDecisionRecordShape | palo:GateDecisionRecord | 5 | palo:EvidenceArtifactShape | palo:EvidenceArtifact | 2 | palo:EvidenceClaimShape | palo:EvidenceClaim | 5 | palo:EvidenceEvaluationShape | palo:EvidenceEvaluation | 2 | palo:EvidenceBundleManifestShape | palo:EvidenceBundleManifest | 3 | palo:MappingRecordShape | palo:MappingRecord | 5 | palo:SemanticReleaseManifestShape | palo:SemanticReleaseManifest | 2 ### palo-ontology-v3.ttl 163 triples. Exact declarations follow; absence of a domain/range is preserved. | Term | Superclass | Domain | Range | palo:AssessmentRun | palo:ImmutableRecord | | | palo:AuthorityClass | palo:CanonicalDefinition | | | palo:CanonicalDefinition | palo:SemanticEntity | | | palo:ControlImplementation | palo:RuntimeRecord | | | palo:DecisionRecord | palo:ImmutableRecord | | | palo:EnforcementAdapterDefinition | palo:CanonicalDefinition | | | palo:EvidenceArtifact | palo:RuntimeRecord | | | palo:EvidenceBundleItem | palo:ImmutableRecord | | | palo:EvidenceBundleManifest | palo:ImmutableRecord | | | palo:EvidenceClaim | palo:ImmutableRecord | | | palo:EvidenceEvaluation | palo:ImmutableRecord | | | palo:GateDecisionRecord | palo:DecisionRecord | | | palo:GateDefinition | palo:CanonicalDefinition | | | palo:GateInstance | palo:RuntimeRecord | | | palo:GovernanceCase | palo:RuntimeRecord | | | palo:GovernanceFrameworkDefinition | palo:CanonicalDefinition | | | palo:ImmutableRecord | palo:SemanticEntity | | | palo:LifecycleDefinition | palo:CanonicalDefinition | | | palo:MappingRecord | palo:ImmutableRecord | | | palo:MetricObservation | palo:ImmutableRecord | | | palo:PhaseDefinition | palo:CanonicalDefinition | | | palo:RegimeDefinition | palo:CanonicalDefinition | | | palo:RuntimeRecord | palo:SemanticEntity | | | palo:SemanticEntity | | | | palo:SemanticReleaseItem | palo:ImmutableRecord | | | palo:SemanticReleaseManifest | palo:ImmutableRecord | | | palo:WorkspaceDefinition | palo:CanonicalDefinition | | | Term | Superclass | Domain | Range | palo:bundleItemReferences | | palo:EvidenceBundleItem | palo:ImmutableRecord | palo:claimScope | | palo:EvidenceClaim | palo:GovernanceCase | palo:containsBundleItem | | palo:EvidenceBundleManifest | palo:EvidenceBundleItem | palo:containsReleaseItem | | palo:SemanticReleaseManifest | palo:SemanticReleaseItem | palo:decisionActor | | palo:DecisionRecord | | palo:decisionForGate | | palo:GateDecisionRecord | palo:GateInstance | palo:evaluatesClaim | | palo:EvidenceEvaluation | palo:EvidenceClaim | palo:gateInstanceCase | | palo:GateInstance | palo:GovernanceCase | palo:hasGateDefinition | | palo:LifecycleDefinition | palo:GateDefinition | palo:hasPhaseDefinition | | palo:LifecycleDefinition | palo:PhaseDefinition | palo:instantiatesGate | | palo:GateInstance | palo:GateDefinition | palo:mapsSourceVersion | | palo:MappingRecord | palo:CanonicalDefinition | palo:mapsTargetVersion | | palo:MappingRecord | palo:CanonicalDefinition | palo:pinnedToReleaseManifest | | | palo:SemanticReleaseManifest | palo:releaseItemReferences | | palo:SemanticReleaseItem | palo:CanonicalDefinition | palo:supersedes | | palo:ImmutableRecord | palo:ImmutableRecord | palo:supportsTarget | | palo:EvidenceClaim | palo:SemanticEntity | palo:usesArtifact | | palo:EvidenceClaim | palo:EvidenceArtifact | Term | Superclass | Domain | Range | palo:appendOnly | | palo:ImmutableRecord | http://www.w3.org/2001/XMLSchema#boolean | palo:approvalStatus | | palo:MappingRecord | http://www.w3.org/2001/XMLSchema#string | palo:authorityBasis | | palo:DecisionRecord | http://www.w3.org/2001/XMLSchema#string | palo:bundleDigest | | palo:EvidenceBundleManifest | http://www.w3.org/2001/XMLSchema#string | palo:caseId | | | http://www.w3.org/2001/XMLSchema#string | palo:claimStatement | | palo:EvidenceClaim | http://www.w3.org/2001/XMLSchema#string | palo:contentDigest | | | http://www.w3.org/2001/XMLSchema#string | palo:coverageType | | palo:MappingRecord | http://www.w3.org/2001/XMLSchema#string | palo:definitionVersion | | palo:CanonicalDefinition | http://www.w3.org/2001/XMLSchema#string | palo:evaluationOutcome | | palo:EvidenceEvaluation | http://www.w3.org/2001/XMLSchema#string | palo:inputSnapshotHash | | palo:DecisionRecord | http://www.w3.org/2001/XMLSchema#string | palo:integrityReference | | palo:EvidenceClaim | http://www.w3.org/2001/XMLSchema#string | palo:manifestDigest | | palo:SemanticReleaseManifest | http://www.w3.org/2001/XMLSchema#string | palo:ordinal | | palo:PhaseDefinition | http://www.w3.org/2001/XMLSchema#integer | palo:rationale | | | http://www.w3.org/2001/XMLSchema#string | palo:recordDigest | | palo:ImmutableRecord | http://www.w3.org/2001/XMLSchema#string | palo:recordedAt | | palo:ImmutableRecord | http://www.w3.org/2001/XMLSchema#dateTime | palo:stableId | | palo:SemanticEntity | http://www.w3.org/2001/XMLSchema#string ### palo-stack-governance.shacl.ttl 58 triples. Exact declarations follow; absence of a domain/range is preserved. | Shape | Target | Property constraints | palo:StackPolicyVersionShape | palo:PolicyVersion | 1 | palo:StackSignalShape | palo:ChangeSignal | 2 | palo:StackApplicabilityShape | palo:ApplicabilityAssessment | 5 | palo:StackRequirementShape | palo:RequirementVersion | 1 ### palo-stack-governance.ttl 90 triples. Exact declarations follow; absence of a domain/range is preserved. | Term | Superclass | Domain | Range | palo:AISystemVersion | palo:SemanticEntity | | | palo:Actor | palo:SemanticEntity | | | palo:Agent | palo:SemanticEntity | | | palo:ApplicabilityAssessment | palo:SemanticEntity | | | palo:Capability | palo:SemanticEntity | | | palo:ChangeSignal | palo:SemanticEntity | | | palo:ComponentVersion | palo:SemanticEntity | | | palo:ControlDefinition | palo:SemanticEntity | | | palo:DataAsset | palo:SemanticEntity | | | palo:GovernancePlane | palo:SemanticEntity | | | palo:Layer | palo:SemanticEntity | | | palo:ModelVersion | palo:SemanticEntity | | | palo:PolicyVersion | palo:SemanticEntity | | | palo:Provider | palo:SemanticEntity | | | palo:PublicPolicy | palo:SemanticEntity | | | palo:RequirementVersion | palo:SemanticEntity | | | palo:Service | palo:SemanticEntity | | | palo:Tool | palo:SemanticEntity | | | Term | Superclass | Domain | Range | palo:addressesRequirement | | | | palo:affectsService | | | | palo:appliesToSystem | | | | palo:assessesSignal | | | | palo:assessesSystem | | | | palo:basedOnAssessment | | | | palo:belongsToLayer | | | | palo:callsTool | | | | palo:considersRequirement | | | | palo:dependsOn | | | | palo:fromVersion | | | | palo:governsLayer | | | | palo:governsVersion | | | | palo:hasVersion | | | | palo:implements | | | | palo:inCase | | | | palo:informs | | | | palo:offers | | | | palo:providesCapability | | | | palo:reads | | | | palo:reviewedBy | | | | palo:reviewsSystem | | | | palo:toVersion | | | | palo:usesModel | | | | palo:usesService | | | ## Field and controlled value dictionary Filter by schema name, field path or value 65 schemas shown PALO Affected-Person Notice, Appeal and Remedy Case palo-affected-person-case.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","caseId","systemCaseId","systemVersion","notice","intake","review","outcome","remedy","privacyBoundary","audit"],"additionalProperties":false} | | $.format | true | | {"const":"palo-affected-person-case"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.caseId | true | string | {"minLength":1} | | $.systemCaseId | true | string | {"minLength":1} | | $.systemVersion | true | string | {"minLength":1} | | $.notice | true | object | {"required":["noticeId","deliveredAt","channel","accessibleFormats","aiRole","significance","humanContact","appealRoute"],"additionalProperties":false} | | $.notice.noticeId | true | string | {} | | $.notice.deliveredAt | true | string | {"format":"date-time"} | | $.notice.channel | true | string | {} | | $.notice.accessibleFormats | true | array | {"minItems":1,"uniqueItems":true} | | $.notice.accessibleFormats[] | false | string | {} | | $.notice.aiRole | true | string | {"minLength":10} | | $.notice.significance | true | string | {"minLength":10} | | $.notice.humanContact | true | string | {"minLength":3} | | $.notice.appealRoute | true | string | {"minLength":3} | | $.intake | true | object | {"required":["receivedAt","acknowledgedAt","requestType","urgency","deadlineAt"],"additionalProperties":false} | | $.intake.receivedAt | true | string | {"format":"date-time"} | | $.intake.acknowledgedAt | true | string | {"format":"date-time"} | | $.intake.requestType | true | | {"enum":["explanation","correction","appeal","human-review","remedy","other"]} | | $.intake.urgency | true | | {"enum":["standard","urgent","immediate-harm"]} | | $.intake.deadlineAt | true | string | {"format":"date-time"} | | $.review | true | object | {"required":["reviewerId","reviewerRole","independentFromOriginalDecision","conflictCheck","evidenceReviewed","completedAt"],"additionalProperties":false} | | $.review.reviewerId | true | string | {} | | $.review.reviewerRole | true | string | {} | | $.review.independentFromOriginalDecision | true | | {"const":true} | | $.review.conflictCheck | true | string | {"minLength":10} | | $.review.evidenceReviewed | true | array | {"minItems":1} | | $.review.evidenceReviewed[] | false | string | {} | | $.review.completedAt | true | string | {"format":"date-time"} | | $.outcome | true | object | {"required":["decision","reasons","communicatedAt"],"additionalProperties":false} | | $.outcome.decision | true | | {"enum":["upheld","varied","overturned","withdrawn","inconclusive"]} | | $.outcome.reasons | true | string | {"minLength":20} | | $.outcome.communicatedAt | true | string | {"format":"date-time"} | | $.remedy | true | object | {"required":["required","actions","owner","dueAt","status","verified"],"additionalProperties":false} | | $.remedy.required | true | boolean | {} | | $.remedy.actions | true | array | {} | | $.remedy.actions[] | false | string | {} | | $.remedy.owner | true | string | {} | | $.remedy.dueAt | true | string | {"format":"date-time"} | | $.remedy.status | true | | {"enum":["not-required","planned","in-progress","completed","overdue"]} | | $.remedy.verified | true | boolean | {} | | $.privacyBoundary | true | string | {"minLength":20} | | $.audit | true | object | {"required":["createdAt","updatedAt","recordDigest"],"additionalProperties":false} | | $.audit.createdAt | true | string | {"format":"date-time"} | | $.audit.updatedAt | true | string | {"format":"date-time"} | | $.audit.recordDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO Agentic Action Claim palo-agentic-action-claim.schema.json Developer-preview interoperability contract for a proposed agent action. Schema validity is not authorization, safety evidence, legal approval, or proof of execution. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","claimId","agentId","caseId","action","requestedScopes","externalNetwork","delegation","requestedAt","expiresAt","nonce","idempotencyKey","sequenceNumber"],"additionalProperties":false} | Developer-preview interoperability contract for a proposed agent action. Schema validity is not authorization, safety evidence, legal approval, or proof of execution. | $.format | true | | {"const":"palo-agentic-action-claim"} | | $.schemaVersion | true | | {"enum":["1.1.0","1.2.0","1.3.0","1.4.0"]} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.action | true | object | {"required":["tool","operation","resource","path","networkIntent","arguments","argumentsDigest","argumentSchemaDigest"],"additionalProperties":false} | | $.action.tool | true | string | {"minLength":1,"maxLength":200} | | $.action.operation | true | | {"enum":["read","create","update","delete","execute","delegate"]} | | $.action.resource | true | string | {"minLength":1,"maxLength":1000} | | $.action.path | true | string | {"minLength":1,"maxLength":1000,"pattern":"^/"} | | $.action.networkIntent | true | | {"enum":["none","read","write","bidirectional"]} | | $.action.networkHost | false | string | {"minLength":1,"maxLength":253,"pattern":"^[a-z0-9.-]+$"} | | $.action.arguments | true | object | {"maxProperties":100,"additionalProperties":true} | | $.action.argumentsDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.action.argumentSchemaDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.requestedScopes | true | object | {"required":["read","write"],"additionalProperties":false} | | $.requestedScopes.read | true | array | {"uniqueItems":true} | | $.requestedScopes.read[] | false | string | {"minLength":1} | | $.requestedScopes.write | true | array | {"uniqueItems":true} | | $.requestedScopes.write[] | false | string | {"minLength":1} | | $.externalNetwork | true | boolean | {} | | $.delegation | true | object | {"required":["depth","subagentCount"],"additionalProperties":false} | | $.delegation.depth | true | integer | {"minimum":0} | | $.delegation.subagentCount | true | integer | {"minimum":0} | | $.delegation.parentAgentId | false | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.delegation.requestedSubagentRole | false | string | {"minLength":1} | | $.authorityContext | false | object | {"required":["authorityContextId","humanPrincipal","workloadIdentity","agentIdentity","delegationChain"],"additionalProperties":false} | | $.authorityContext.authorityContextId | true | string | {"pattern":"^authority-[a-f0-9-]{36}$"} | | $.authorityContext.humanPrincipal | true | object | {"required":["subject","issuer","authenticatedAt","credentialDigest"],"additionalProperties":false} | | $.authorityContext.humanPrincipal.subject | true | string | {"minLength":1,"maxLength":512} | | $.authorityContext.humanPrincipal.issuer | true | string | {"format":"uri","maxLength":1000} | | $.authorityContext.humanPrincipal.authenticatedAt | true | string | {"format":"date-time"} | | $.authorityContext.humanPrincipal.credentialDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.authorityContext.humanPrincipal.proofReference | false | string | {"format":"uri","maxLength":2000} | | $.authorityContext.workloadIdentity | true | object | {"required":["subject","issuer","audience","proofType","credentialDigest"],"additionalProperties":false} | | $.authorityContext.workloadIdentity.subject | true | string | {"minLength":1,"maxLength":1000} | | $.authorityContext.workloadIdentity.issuer | true | string | {"format":"uri","maxLength":1000} | | $.authorityContext.workloadIdentity.audience | true | string | {"minLength":1,"maxLength":1000} | | $.authorityContext.workloadIdentity.proofType | true | | {"enum":["mtls","dpop","http-message-signature","spiffe-svid"]} | | $.authorityContext.workloadIdentity.credentialDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.authorityContext.workloadIdentity.proofReference | false | string | {"format":"uri","maxLength":2000} | | $.authorityContext.agentIdentity | true | object | {"required":["agentId","instanceId"],"additionalProperties":false} | | $.authorityContext.agentIdentity.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.authorityContext.agentIdentity.instanceId | true | string | {"minLength":1,"maxLength":256} | | $.authorityContext.tenantId | false | string | {"minLength":1,"maxLength":128} | | $.authorityContext.delegationChain | true | array | {"maxItems":16} | | $.authorityContext.delegationChain[] | false | object | {"required":["delegationId","from","to","scopes","issuedAt","expiresAt"],"additionalProperties":false} | | $.authorityContext.delegationChain[].delegationId | true | string | {"pattern":"^delegation-[a-f0-9-]{36}$"} | | $.authorityContext.delegationChain[].from | true | string | {"minLength":1,"maxLength":1000} | | $.authorityContext.delegationChain[].to | true | string | {"minLength":1,"maxLength":1000} | | $.authorityContext.delegationChain[].scopes | true | object | {"required":["read","write"],"additionalProperties":false} | | $.authorityContext.delegationChain[].scopes.read | true | array | {"uniqueItems":true} | | $.authorityContext.delegationChain[].scopes.read[] | false | string | {"minLength":1} | | $.authorityContext.delegationChain[].scopes.write | true | array | {"uniqueItems":true} | | $.authorityContext.delegationChain[].scopes.write[] | false | string | {"minLength":1} | | $.authorityContext.delegationChain[].issuedAt | true | string | {"format":"date-time"} | | $.authorityContext.delegationChain[].expiresAt | true | string | {"format":"date-time"} | | $.requestedAt | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | | $.nonce | true | string | {"pattern":"^[a-zA-Z0-9_-]{16,128}$"} | | $.idempotencyKey | true | string | {"pattern":"^[a-zA-Z0-9._:-]{16,200}$"} | | $.sequenceNumber | true | integer | {"minimum":1,"maximum":9007199254740991} | | $.effectContract | false | / palo-agentic-effect-contract.schema.json | {} | | $.dataGovernance | false | object | {"required":["subject","purpose","fitnessDecisionId","fitnessDecisionDigest","disclosureContractId","disclosureContractDigest"],"additionalProperties":false} | | $.dataGovernance.subject | true | object | {"required":["type","id"],"additionalProperties":false} | | $.dataGovernance.subject.type | true | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.dataGovernance.subject.id | true | string | {"minLength":1,"maxLength":1000} | | $.dataGovernance.purpose | true | string | {"minLength":1,"maxLength":300} | | $.dataGovernance.fitnessDecisionId | true | string | {"pattern":"^fitness-decision-[a-f0-9-]{36}$"} | | $.dataGovernance.fitnessDecisionDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.dataGovernance.disclosureContractId | true | string | {"pattern":"^disclosure-[a-f0-9-]{36}$"} | | $.dataGovernance.disclosureContractDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.metadata | false | object | {"additionalProperties":true} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["schemaVersion"]} | | $.allOf[0].if.schemaVersion | true | | {"enum":["1.1.0","1.2.0"]} | | $.allOf[0].then | false | | {} | | $.allOf[1] | false | | {} | | $.allOf[1].if | false | | {"required":["schemaVersion"]} | | $.allOf[1].if.schemaVersion | true | | {"const":"1.2.0"} | | $.allOf[1].then | false | | {"required":["effectContract"]} | | $.allOf[1].then.effectContract | true | / palo-agentic-effect-contract.schema.json | {} | | $.allOf[2] | false | | {} | | $.allOf[2].if | false | | {"required":["schemaVersion"]} | | $.allOf[2].if.schemaVersion | true | | {"const":"1.3.0"} | | $.allOf[2].then | false | | {"required":["effectContract","authorityContext"]} | | $.allOf[2].then.effectContract | true | / palo-agentic-effect-contract.schema.json | {} | | $.allOf[2].then.authorityContext | true | object | {} | | $.allOf[3] | false | | {} | | $.allOf[3].if | false | | {"required":["schemaVersion"]} | | $.allOf[3].if.schemaVersion | true | | {"const":"1.4.0"} | | $.allOf[3].then | false | | {"required":["effectContract","authorityContext","dataGovernance"]} | | $.allOf[3].then.effectContract | true | / palo-agentic-effect-contract.schema.json | {} | | $.allOf[3].then.authorityContext | true | object | {} | | $.allOf[3].then.dataGovernance | true | object | {} | PALO Human Approval palo-agentic-approval.schema.json Developer-preview approval-state contract. The reference clients do not yet provide production reviewer identity, device attestation or all context required for a consequential human decision. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","approvalId","claimId","claimDigest","caseId","agentId","status","requestedBy","requestedAt","expiresAt"],"additionalProperties":false} | Developer-preview approval-state contract. The reference clients do not yet provide production reviewer identity, device attestation or all context required for a consequential human decision. | $.format | true | | {"const":"palo-agentic-approval"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.approvalId | true | string | {"pattern":"^approval-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.claimDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.status | true | | {"enum":["pending","approved","denied","expired","cancelled"]} | | $.requestedBy | true | string | {"minLength":1} | | $.requestedAt | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | | $.resolvedBy | false | string | {"minLength":1} | | $.resolvedAt | false | string | {"format":"date-time"} | | $.rationale | false | string | {"maxLength":4000} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["status"]} | | $.allOf[0].if.status | true | | {"enum":["approved","denied","cancelled"]} | | $.allOf[0].then | false | | {"required":["resolvedBy","resolvedAt","rationale"]} | | $.allOf[0].then.resolvedBy | true | | {} | | $.allOf[0].then.resolvedAt | true | | {} | | $.allOf[0].then.rationale | true | | {} | PALO Assurance Incident palo-agentic-assurance-incident.schema.json Developer-preview human-resolution record for a mismatched or inconclusive governed action. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","incidentId","executionId","claimId","caseId","status","severity","reason","resourceHold","createdAt","updatedAt"],"additionalProperties":false} | Developer-preview human-resolution record for a mismatched or inconclusive governed action. | $.format | true | | {"const":"palo-agentic-assurance-incident"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.incidentId | true | string | {"pattern":"^incident-[a-f0-9-]{36}$"} | | $.executionId | true | string | {"pattern":"^execution-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.status | true | | {"enum":["open","acknowledged","resolved"]} | | $.severity | true | | {"enum":["low","medium","high","critical"]} | | $.reason | true | string | {"minLength":1,"maxLength":4000} | | $.resourceHold | true | boolean | {} | | $.createdAt | true | string | {"format":"date-time"} | | $.updatedAt | true | string | {"format":"date-time"} | | $.resolvedBy | false | string | {"minLength":1,"maxLength":320} | | $.resolution | false | string | {"minLength":1,"maxLength":4000} | | $.resolvedAt | false | string | {"format":"date-time"} | | $.recommendedCompensation | false | object | {"required":["requiresNewActionClaim","action"],"additionalProperties":false} | | $.recommendedCompensation.requiresNewActionClaim | true | | {"const":true} | | $.recommendedCompensation.action | true | object | {"required":["tool","operation","resource","path"],"additionalProperties":false} | | $.recommendedCompensation.action.tool | true | string | {"minLength":1,"maxLength":200} | | $.recommendedCompensation.action.operation | true | | {"enum":["create","update","delete","execute"]} | | $.recommendedCompensation.action.resource | true | string | {"minLength":1,"maxLength":1000} | | $.recommendedCompensation.action.path | true | string | {"minLength":1,"maxLength":1000,"pattern":"^/"} | PALO Agentic Capability Governance Crosswalk palo-agentic-capability-crosswalk.schema.json PALO-owned governance responses and reviewed mappings from optional external capability taxonomies. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","crosswalkVersion","releasedAt","status","authorityBoundary","capabilities","providerMappings"],"additionalProperties":false} | PALO-owned governance responses and reviewed mappings from optional external capability taxonomies. | $.format | true | | {"const":"palo-agentic-capability-crosswalk"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.crosswalkVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.releasedAt | true | string | {"format":"date"} | | $.status | true | | {"enum":["draft","in-review","approved-for-release","superseded"]} | | $.authorityBoundary | true | string | {"minLength":80} | | $.capabilities | true | array | {"minItems":1} | | $.capabilities[] | false | / #/$defs/capability | {} | | $.providerMappings | true | array | {} | | $.providerMappings[] | false | / #/$defs/providerMapping | {} | | $.$defs.capability | false | object | {"required":["capabilityId","title","definition","primaryConcern","controlIds","evidenceKinds","indicatorIds","gateIds","assessmentQuestions","whatEvidenceWouldChangeThis","limitations"],"additionalProperties":false} | | $.$defs.capability.capabilityId | true | string | {"pattern":"^palo-cap-[a-z0-9-]+$"} | | $.$defs.capability.title | true | string | {"minLength":1,"maxLength":160} | | $.$defs.capability.definition | true | string | {"minLength":40,"maxLength":600} | | $.$defs.capability.primaryConcern | true | | {"enum":["purpose","authority","oversight","identity","delegation","change","observability","resilience","physical-effect"]} | | $.$defs.capability.controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.capability.controlIds[] | false | string | {"pattern":"^ctrl-[a-z0-9-]+$"} | | $.$defs.capability.evidenceKinds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.capability.evidenceKinds[] | false | string | {"minLength":1} | | $.$defs.capability.indicatorIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.capability.indicatorIds[] | false | string | {"pattern":"^(kpi|kri)-[a-z0-9-]+$"} | | $.$defs.capability.gateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.capability.gateIds[] | false | string | {"minLength":1} | | $.$defs.capability.assessmentQuestions | true | array | {"minItems":2,"uniqueItems":true} | | $.$defs.capability.assessmentQuestions[] | false | string | {"minLength":20} | | $.$defs.capability.whatEvidenceWouldChangeThis | true | array | {"minItems":2,"uniqueItems":true} | | $.$defs.capability.whatEvidenceWouldChangeThis[] | false | string | {"minLength":20} | | $.$defs.capability.limitations | true | string | {"minLength":40} | | $.$defs.providerMapping | false | object | {"required":["providerId","providerCapabilityId","providerLabel","providerRubricVersion","paloCapabilityIds","coverage","mappingVersion","reviewState","rationale","notUseCaseRiskScore"],"additionalProperties":false} | | $.$defs.providerMapping.providerId | true | string | {"pattern":"^[a-z][a-z0-9-]{2,63}$"} | | $.$defs.providerMapping.providerCapabilityId | true | string | {"minLength":1,"maxLength":120} | | $.$defs.providerMapping.providerLabel | true | string | {"minLength":1,"maxLength":160} | | $.$defs.providerMapping.providerRubricVersion | true | string | {"minLength":1,"maxLength":100} | | $.$defs.providerMapping.paloCapabilityIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.providerMapping.paloCapabilityIds[] | false | string | {"pattern":"^palo-cap-[a-z0-9-]+$"} | | $.$defs.providerMapping.coverage | true | | {"enum":["partial","supporting"]} | | $.$defs.providerMapping.mappingVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.providerMapping.reviewState | true | | {"enum":["draft","in-review","approved","rejected","superseded"]} | | $.$defs.providerMapping.rationale | true | string | {"minLength":40} | | $.$defs.providerMapping.notUseCaseRiskScore | true | | {"const":true} | PALO Agentic Effect Contract palo-agentic-effect-contract.schema.json Developer-preview contract describing observable preconditions, intended effects and forbidden effects for a governed action. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","effectContractId","resourceSelector","preconditions","expectedEffects","forbiddenEffects","verification"],"additionalProperties":false} | Developer-preview contract describing observable preconditions, intended effects and forbidden effects for a governed action. | $.format | true | | {"const":"palo-agentic-effect-contract"} | | $.schemaVersion | true | | {"enum":["1.0.0","1.1.0"]} | | $.effectContractId | true | string | {"pattern":"^effect-[a-f0-9-]{36}$"} | | $.resourceSelector | true | object | {"required":["resource","path"],"additionalProperties":false} | | $.resourceSelector.resource | true | string | {"minLength":1,"maxLength":1000} | | $.resourceSelector.path | true | string | {"minLength":1,"maxLength":1000,"pattern":"^/"} | | $.resourceSelector.tenantId | false | string | {"minLength":1,"maxLength":128} | | $.preconditions | true | / #/$defs/predicateList | {} | | $.expectedEffects | true | / #/$defs/predicateList | {} | | $.forbiddenEffects | true | / #/$defs/predicateList | {} | | $.verification | true | object | {"required":["windowSeconds","onInconclusive"],"additionalProperties":false} | | $.verification.windowSeconds | true | integer | {"minimum":1,"maximum":86400} | | $.verification.onInconclusive | true | | {"enum":["hold_and_review","retry_then_review"]} | | $.verification.maxAttempts | false | integer | {"minimum":1,"maximum":10} | | $.verification.initialDelaySeconds | false | integer | {"minimum":0,"maximum":86400} | | $.verification.retryBackoffSeconds | false | integer | {"minimum":1,"maximum":86400} | | $.recovery | false | object | {"required":["onMismatch"],"additionalProperties":false} | | $.recovery.onMismatch | true | | {"enum":["hold_and_review","propose_compensation"]} | | $.recovery.compensationAction | false | object | {"required":["tool","operation","resource","path"],"additionalProperties":false} | | $.recovery.compensationAction.tool | true | string | {"minLength":1,"maxLength":200} | | $.recovery.compensationAction.operation | true | | {"enum":["create","update","delete","execute"]} | | $.recovery.compensationAction.resource | true | string | {"minLength":1,"maxLength":1000} | | $.recovery.compensationAction.path | true | string | {"minLength":1,"maxLength":1000,"pattern":"^/"} | | $.recovery.allOf[0] | false | | {} | | $.recovery.allOf[0].if | false | | {"required":["onMismatch"]} | | $.recovery.allOf[0].if.onMismatch | true | | {"const":"propose_compensation"} | | $.recovery.allOf[0].then | false | | {"required":["compensationAction"]} | | $.recovery.allOf[0].then.compensationAction | true | object | {} | | $.$defs.legacyPredicateList | false | array | {} | | $.$defs.legacyPredicateList[] | false | | {} | | $.$defs.legacyPredicateList[].allOf[0] | false | / #/$defs/predicate | {} | | $.$defs.legacyPredicateList[].allOf[1] | false | object | {} | | $.$defs.legacyPredicateList[].allOf[1].operator | false | | {"enum":["exists","equals","unchanged","changedTo","deltaWithin"]} | | $.$defs.predicateList | false | array | {"maxItems":100} | | $.$defs.predicateList[] | false | / #/$defs/predicate | {} | | $.$defs.predicate | false | object | {"required":["predicateId","path","operator"],"additionalProperties":false} | | $.$defs.predicate.predicateId | true | string | {"pattern":"^predicate-[a-zA-Z0-9._-]{1,100}$"} | | $.$defs.predicate.path | true | string | {"pattern":"^(|/(?:[^~/]|~0|~1)*)$","maxLength":1000} | | $.$defs.predicate.operator | true | | {"enum":["exists","notExists","equals","unchanged","changedTo","deltaWithin","numberWithin","containsAll","typeIs"]} | | $.$defs.predicate.minimumDelta | false | number | {} | | $.$defs.predicate.maximumDelta | false | number | {} | | $.$defs.predicate.minimum | false | number | {} | | $.$defs.predicate.maximum | false | number | {} | | $.$defs.predicate.values | false | array | {"uniqueItems":true,"maxItems":100} | | $.$defs.predicate.expectedType | false | | {"enum":["array","boolean","null","number","object","string"]} | | $.$defs.predicate.description | false | string | {"maxLength":500} | | $.$defs.predicate.allOf[0] | false | | {} | | $.$defs.predicate.allOf[0].if | false | | {"required":["operator"]} | | $.$defs.predicate.allOf[0].if.operator | true | | {"enum":["equals","changedTo"]} | | $.$defs.predicate.allOf[0].then | false | | {"required":["value"]} | | $.$defs.predicate.allOf[1] | false | | {} | | $.$defs.predicate.allOf[1].if | false | | {"required":["operator"]} | | $.$defs.predicate.allOf[1].if.operator | true | | {"const":"deltaWithin"} | | $.$defs.predicate.allOf[1].then | false | | {"required":["minimumDelta","maximumDelta"]} | | $.$defs.predicate.allOf[1].then.minimumDelta | true | number | {} | | $.$defs.predicate.allOf[1].then.maximumDelta | true | number | {} | | $.$defs.predicate.allOf[2] | false | | {} | | $.$defs.predicate.allOf[2].if | false | | {"required":["operator"]} | | $.$defs.predicate.allOf[2].if.operator | true | | {"const":"numberWithin"} | | $.$defs.predicate.allOf[2].then | false | | {"required":["minimum","maximum"]} | | $.$defs.predicate.allOf[2].then.minimum | true | number | {} | | $.$defs.predicate.allOf[2].then.maximum | true | number | {} | | $.$defs.predicate.allOf[3] | false | | {} | | $.$defs.predicate.allOf[3].if | false | | {"required":["operator"]} | | $.$defs.predicate.allOf[3].if.operator | true | | {"const":"containsAll"} | | $.$defs.predicate.allOf[3].then | false | | {"required":["values"]} | | $.$defs.predicate.allOf[3].then.values | true | array | {} | | $.$defs.predicate.allOf[4] | false | | {} | | $.$defs.predicate.allOf[4].if | false | | {"required":["operator"]} | | $.$defs.predicate.allOf[4].if.operator | true | | {"const":"typeIs"} | | $.$defs.predicate.allOf[4].then | false | | {"required":["expectedType"]} | | $.$defs.predicate.allOf[4].then.expectedType | true | string | {} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["schemaVersion"]} | | $.allOf[0].if.schemaVersion | true | | {"const":"1.0.0"} | | $.allOf[0].then | false | | {} | | $.allOf[0].then.preconditions | false | / #/$defs/legacyPredicateList | {} | | $.allOf[0].then.expectedEffects | false | / #/$defs/legacyPredicateList | {} | | $.allOf[0].then.forbiddenEffects | false | / #/$defs/legacyPredicateList | {} | | $.allOf[0].then.verification | false | object | {} | PALO Agentic Enforcement Provider palo-agentic-enforcement-provider.schema.json Vendor-neutral manifest for a policy runtime that returns fail-closed pre-action decisions to PALO. Provider registration does not make an external runtime trusted, production-ready, or endorsed by its vendor. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","providerId","providerVersion","displayName","providerType","capabilities","policyReference"],"additionalProperties":false} | Vendor-neutral manifest for a policy runtime that returns fail-closed pre-action decisions to PALO. Provider registration does not make an external runtime trusted, production-ready, or endorsed by its vendor. | $.format | true | | {"const":"palo-agentic-enforcement-provider"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.providerId | true | string | {"pattern":"^provider-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.providerVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+(?:-[0-9A-Za-z.-]+)?$"} | | $.displayName | true | string | {"minLength":1,"maxLength":200} | | $.providerType | true | string | {"pattern":"^[a-z][a-z0-9._-]{2,100}$"} | | $.capabilities | true | array | {"minItems":1,"uniqueItems":true} | | $.capabilities[] | false | | {"enum":["pre_action_decision","human_escalation","decision_evidence","argument_transformation","post_action_mediation"]} | | $.capabilities.contains | false | | {"const":"pre_action_decision"} | | $.policyReference | true | string | {"minLength":1,"maxLength":500} | | $.vendor | false | string | {"minLength":1,"maxLength":200} | | $.metadata | false | object | {"additionalProperties":{"anyOf":[{"type":"string"},{"type":"number"},{"type":"boolean"},{"type":"null"}]}} | | $.metadata.additionalProperties | false | | {} | | $.metadata.additionalProperties.anyOf[0] | false | string | {} | | $.metadata.additionalProperties.anyOf[1] | false | number | {} | | $.metadata.additionalProperties.anyOf[2] | false | boolean | {} | | $.metadata.additionalProperties.anyOf[3] | false | null | {} | PALO Signed Agentic Evidence Envelope palo-agentic-evidence-envelope.schema.json Developer-preview evidence-envelope contract. Version 1 uses a shared HMAC secret; version 2 supports RFC 8785 canonicalization and externally verifiable Ed25519 signatures. Neither version is external timestamping, legal evidence, or certification of the claimed execution. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","eventId","caseId","agentId","claimId","decisionId","outcome","recordedAt","payloadDigest","previousEventDigest","keyId","algorithm","signature"],"additionalProperties":false} | Developer-preview evidence-envelope contract. Version 1 uses a shared HMAC secret; version 2 supports RFC 8785 canonicalization and externally verifiable Ed25519 signatures. Neither version is external timestamping, legal evidence, or certification of the claimed execution. | $.format | true | | {"const":"palo-agentic-evidence-envelope"} | | $.schemaVersion | true | | {"enum":["1.0.0","2.0.0"]} | | $.eventId | true | string | {"pattern":"^event-[a-f0-9-]{36}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.decisionId | true | string | {"pattern":"^decision-[a-f0-9-]{36}$"} | | $.approvalId | false | string | {"pattern":"^approval-[a-f0-9-]{36}$"} | | $.executionId | false | string | {"pattern":"^execution-[a-f0-9-]{36}$"} | | $.attestationId | false | string | {"pattern":"^attestation-[a-f0-9-]{36}$"} | | $.incidentId | false | string | {"pattern":"^incident-[a-f0-9-]{36}$"} | | $.taskId | false | string | {"pattern":"^task-[a-f0-9-]{36}$"} | | $.traceId | false | string | {"pattern":"^[a-f0-9]{32}$"} | | $.outcome | true | | {"enum":["allowed","denied","pending_approval","executed","failed","execution_started","execution_succeeded","execution_failed","execution_unknown","outcome_verified","outcome_mismatch","outcome_inconclusive","incident_opened","incident_resolved"]} | | $.recordedAt | true | string | {"format":"date-time"} | | $.redactedPayload | false | object | {"additionalProperties":true} | | $.payloadDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.previousEventDigest | true | ["string","null"] | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"enum":["HMAC-SHA256","Ed25519"]} | | $.canonicalization | false | | {"const":"RFC8785"} | | $.verificationMethod | false | string | {"minLength":1,"maxLength":1000} | | $.signature | true | | {} | | $.signature.oneOf[0] | false | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.signature.oneOf[1] | false | string | {"pattern":"^ed25519:[A-Za-z0-9_-]{86}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["schemaVersion"]} | | $.allOf[0].if.schemaVersion | true | | {"const":"1.0.0"} | | $.allOf[0].then | false | | {} | | $.allOf[0].then.algorithm | false | | {"const":"HMAC-SHA256"} | | $.allOf[0].then.signature | false | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.allOf[1] | false | | {} | | $.allOf[1].if | false | | {"required":["schemaVersion"]} | | $.allOf[1].if.schemaVersion | true | | {"const":"2.0.0"} | | $.allOf[1].then | false | | {"required":["canonicalization","verificationMethod"]} | | $.allOf[1].then.algorithm | false | | {"const":"Ed25519"} | | $.allOf[1].then.canonicalization | true | | {"const":"RFC8785"} | | $.allOf[1].then.verificationMethod | true | string | {} | | $.allOf[1].then.signature | false | string | {"pattern":"^ed25519:[A-Za-z0-9_-]{86}$"} | PALO One-Time Execution Capability palo-agentic-execution-capability.schema.json Server-side developer-preview capability binding one authorized claim to one executor and verifier. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","capabilityId","claimId","claimDigest","decisionId","caseId","agentId","executorId","verifierId","resource","path","issuedAt","expiresAt","singleUse","status","keyId","algorithm","signature"],"additionalProperties":false} | Server-side developer-preview capability binding one authorized claim to one executor and verifier. | $.format | true | | {"const":"palo-agentic-execution-capability"} | | $.schemaVersion | true | | {"enum":["1.0.0","1.1.0"]} | | $.capabilityId | true | string | {"pattern":"^capability-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.claimDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.decisionId | true | string | {"pattern":"^decision-[a-f0-9-]{36}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.executorId | true | string | {"pattern":"^executor-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.verifierId | true | string | {"pattern":"^verifier-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.resource | true | string | {"minLength":1,"maxLength":1000} | | $.path | true | string | {"pattern":"^/","maxLength":1000} | | $.tenantId | false | string | {"minLength":1,"maxLength":128} | | $.fitnessDecisionId | false | string | {"pattern":"^fitness-decision-[a-f0-9-]{36}$"} | | $.fitnessDecisionDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.disclosureContractId | false | string | {"pattern":"^disclosure-[a-f0-9-]{36}$"} | | $.disclosureContractDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.issuedAt | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | | $.singleUse | true | | {"const":true} | | $.status | true | | {"enum":["issued","consumed","expired","revoked"]} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"const":"HMAC-SHA256"} | | $.signature | true | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["schemaVersion"]} | | $.allOf[0].if.schemaVersion | true | | {"const":"1.1.0"} | | $.allOf[0].then | false | | {"required":["fitnessDecisionId","fitnessDecisionDigest","disclosureContractId","disclosureContractDigest"]} | | $.allOf[0].then.fitnessDecisionId | true | | {} | | $.allOf[0].then.fitnessDecisionDigest | true | | {} | | $.allOf[0].then.disclosureContractId | true | | {} | | $.allOf[0].then.disclosureContractDigest | true | | {} | PALO Trusted Execution Receipt palo-agentic-execution-receipt.schema.json Developer-preview signed receipt generated by the trusted executor rather than by the calling agent. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","executionId","capabilityId","claimId","claimDigest","executorId","status","startedAt","completedAt","preStateDigest","requestDigest","resultDigest","keyId","algorithm","signature"],"additionalProperties":false} | Developer-preview signed receipt generated by the trusted executor rather than by the calling agent. | $.format | true | | {"const":"palo-agentic-execution-receipt"} | | $.schemaVersion | true | | {"enum":["1.0.0","1.1.0"]} | | $.executionId | true | string | {"pattern":"^execution-[a-f0-9-]{36}$"} | | $.capabilityId | true | string | {"pattern":"^capability-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.claimDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.executorId | true | string | {"pattern":"^executor-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.status | true | | {"enum":["succeeded","failed","unknown"]} | | $.startedAt | true | string | {"format":"date-time"} | | $.completedAt | true | string | {"format":"date-time"} | | $.preStateDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.resourceVersion | false | string | {"maxLength":500} | | $.requestDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.resultDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.disclosureReceiptId | false | string | {"pattern":"^disclosure-receipt-[a-f0-9-]{36}$"} | | $.disclosureReceiptDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.error | false | string | {"maxLength":4000} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"const":"HMAC-SHA256"} | | $.signature | true | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["schemaVersion"]} | | $.allOf[0].if.schemaVersion | true | | {"const":"1.1.0"} | | $.allOf[0].then | false | | {"required":["disclosureReceiptId","disclosureReceiptDigest"]} | | $.allOf[0].then.disclosureReceiptId | true | | {} | | $.allOf[0].then.disclosureReceiptDigest | true | | {} | PALO Agent Profile palo-agentic-interface.schema.json Versioned authority-profile contract intended for registration by a governance administrator. The reference runtime does not yet authenticate that administrative role or attest the profile publisher. The profile never contains signing secrets. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","profileVersion","agentId","identity","authority","delegation","evidence"],"additionalProperties":false} | Versioned authority-profile contract intended for registration by a governance administrator. The reference runtime does not yet authenticate that administrative role or attest the profile publisher. The profile never contains signing secrets. | $.format | true | | {"const":"palo-agentic-interface"} | | $.schemaVersion | true | | {"const":"1.1.0"} | | $.profileVersion | true | string | {"pattern":"^[1-9][0-9]*\\.[0-9]+\\.[0-9]+$"} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.status | false | | {"enum":["active","suspended","retired"]} | | $.identity | true | object | {"required":["role","lineage","baseModel","systemPromptHash"],"additionalProperties":false} | | $.identity.role | true | string | {"minLength":1,"maxLength":100} | | $.identity.lineage | true | string | {"minLength":1,"maxLength":500} | | $.identity.baseModel | true | string | {"minLength":1,"maxLength":200} | | $.identity.systemPromptHash | true | string | {"pattern":"^sha256:[a-fA-F0-9]{64}$"} | | $.identity.temperature | false | number | {"minimum":0,"maximum":2} | | $.authority | true | object | {"required":["allowedTools","allowedOperations","externalNetwork","readScopes","writeScopes","argumentSchemas","requireVibeGate"],"additionalProperties":false} | | $.authority.allowedTools | true | array | {"uniqueItems":true} | | $.authority.allowedTools[] | false | string | {"minLength":1} | | $.authority.allowedOperations | true | array | {"uniqueItems":true} | | $.authority.allowedOperations[] | false | | {"enum":["read","create","update","delete","execute","delegate"]} | | $.authority.externalNetwork | true | boolean | {} | | $.authority.allowedNetworkHosts | false | array | {"uniqueItems":true} | | $.authority.allowedNetworkHosts[] | false | string | {"pattern":"^(\\*|[a-zA-Z0-9.-]+)$"} | | $.authority.readScopes | true | array | {"uniqueItems":true} | | $.authority.readScopes[] | false | string | {"minLength":1} | | $.authority.writeScopes | true | array | {"uniqueItems":true} | | $.authority.writeScopes[] | false | string | {"minLength":1} | | $.authority.argumentSchemas | true | object | {"minProperties":1,"additionalProperties":{"type":"object"}} | | $.authority.argumentSchemas.additionalProperties | false | object | {} | | $.authority.requireVibeGate | true | boolean | {} | | $.delegation | true | object | {"required":["maxDepth","maxSubagents","allowedSubagentRoles","requireHumanValidation"],"additionalProperties":false} | | $.delegation.maxDepth | true | integer | {"minimum":0,"maximum":20} | | $.delegation.maxSubagents | true | integer | {"minimum":0,"maximum":1000} | | $.delegation.allowedSubagentRoles | true | array | {"uniqueItems":true} | | $.delegation.allowedSubagentRoles[] | false | string | {"minLength":1} | | $.delegation.requireHumanValidation | true | boolean | {} | | $.evidence | true | object | {"required":["keyId","algorithm","auditTrailId","redactFields"],"additionalProperties":false} | | $.evidence.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.evidence.algorithm | true | | {"const":"HMAC-SHA256"} | | $.evidence.auditTrailId | true | string | {"pattern":"^ledger-[a-zA-Z0-9._-]{3,100}$"} | | $.evidence.redactFields | true | array | {"uniqueItems":true} | | $.evidence.redactFields[] | false | string | {"minLength":1} | | $.metadata | false | object | {"additionalProperties":true} | PALO Outcome Attestation palo-agentic-outcome-attestation.schema.json Developer-preview signed comparison between an Effect Contract and authoritative observed state. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","attestationId","executionId","claimId","verifierId","status","checkedAt","postStateDigest","checks","keyId","algorithm","signature"],"additionalProperties":false} | Developer-preview signed comparison between an Effect Contract and authoritative observed state. | $.format | true | | {"const":"palo-agentic-outcome-attestation"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.attestationId | true | string | {"pattern":"^attestation-[a-f0-9-]{36}$"} | | $.executionId | true | string | {"pattern":"^execution-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.verifierId | true | string | {"pattern":"^verifier-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.status | true | | {"enum":["verified","mismatch","inconclusive"]} | | $.checkedAt | true | string | {"format":"date-time"} | | $.postStateDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.checks | true | array | {"maxItems":300} | | $.checks[] | false | object | {"required":["predicateId","category","status","reason"],"additionalProperties":false} | | $.checks[].predicateId | true | string | {"pattern":"^predicate-[a-zA-Z0-9._-]{1,100}$"} | | $.checks[].category | true | | {"enum":["precondition","expected","forbidden"]} | | $.checks[].status | true | | {"enum":["pass","fail","unknown"]} | | $.checks[].reason | true | string | {"minLength":1,"maxLength":1000} | | $.incidentId | false | string | {"pattern":"^incident-[a-f0-9-]{36}$"} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"const":"HMAC-SHA256"} | | $.signature | true | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | PALO Agentic Policy Decision palo-agentic-policy-decision.schema.json Developer-preview policy-decision contract. An allowed status is not proof that an action is safe, lawful, currently authorized, exactly once, executed, or durably evidenced. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","decisionId","claimId","agentId","status","reasons","policyVersion","profileVersion","claimDigest","decidedAt","obligations"],"additionalProperties":false} | Developer-preview policy-decision contract. An allowed status is not proof that an action is safe, lawful, currently authorized, exactly once, executed, or durably evidenced. | $.format | true | | {"const":"palo-agentic-policy-decision"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.decisionId | true | string | {"pattern":"^decision-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.agentId | true | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.status | true | | {"enum":["allowed","denied","pending_approval"]} | | $.reasons | true | array | {"minItems":1} | | $.reasons[] | false | string | {"minLength":1} | | $.policyVersion | true | string | {"minLength":1} | | $.profileVersion | true | string | {"minLength":1} | | $.claimDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.decidedAt | true | string | {"format":"date-time"} | | $.approvalId | false | string | {"pattern":"^approval-[a-f0-9-]{36}$"} | | $.obligations | true | array | {} | | $.obligations[] | false | string | {"minLength":1} | | $.enforcementProvider | false | object | {"required":["providerId","providerVersion","policyReference"],"additionalProperties":false} | Portable reference to the provider that produced the pre-action decision. It is evidence linkage, not vendor endorsement or proof of provider integrity. | $.enforcementProvider.providerId | true | string | {"pattern":"^provider-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.enforcementProvider.providerVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+(?:-[0-9A-Za-z.-]+)?$"} | | $.enforcementProvider.policyReference | true | string | {"minLength":1,"maxLength":500} | | $.enforcementProvider.decisionReference | false | string | {"minLength":1,"maxLength":500} | | $.enforcementProvider.evidenceDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["status"]} | | $.allOf[0].if.status | true | | {"const":"pending_approval"} | | $.allOf[0].then | false | | {"required":["approvalId"]} | | $.allOf[0].then.approvalId | true | | {} | PALO OPA Agentic Policy Input palo-agentic-policy-input.schema.json Developer-preview OPA input contract. A conforming input or policy response is not a production authorization or compliance determination. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["claim","claim_digest","profile","policy","approval","now"],"additionalProperties":false} | Developer-preview OPA input contract. A conforming input or policy response is not a production authorization or compliance determination. | $.claim | true | / palo-agentic-action-claim.schema.json | {} | | $.claim_digest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.profile | true | / palo-agentic-interface.schema.json | {} | | $.policy | true | / palo-agentic-policy.schema.json | {} | | $.approval | true | | {} | | $.approval.oneOf[0] | false | / palo-agentic-approval.schema.json | {} | | $.approval.oneOf[1] | false | null | {} | | $.now | true | string | {"format":"date-time"} | PALO Policy Registration palo-agentic-policy.schema.json Developer-preview policy-manifest contract. The reference runtime does not yet authenticate the publisher or attest that the active OPA bundle matches this manifest. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","policyId","policyVersion","status","regoPackage","entrypoint","bundleDigest"],"additionalProperties":false} | Developer-preview policy-manifest contract. The reference runtime does not yet authenticate the publisher or attest that the active OPA bundle matches this manifest. | $.format | true | | {"const":"palo-agentic-policy"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.policyId | true | string | {"pattern":"^policy-[a-zA-Z0-9._-]{3,100}$"} | | $.policyVersion | true | string | {"pattern":"^[1-9][0-9]*\\.[0-9]+\\.[0-9]+$"} | | $.status | true | | {"enum":["active","suspended","retired"]} | | $.regoPackage | true | string | {"pattern":"^[a-zA-Z0-9_.]+$"} | | $.entrypoint | true | string | {"minLength":1,"maxLength":300} | | $.bundleDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.metadata | false | object | {"additionalProperties":true} | PALO AI System and Agent Registry Record palo-ai-system-record.schema.json Versioned registry record linking an AI system to models, agents, tools, data, providers, owners, policy and evidence. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","systemId","recordVersion","tenantId","name","useCase","status","riskClass","jurisdictions","owners","relationships","deployedVersion","policyBundleDigest","updatedAt"],"additionalProperties":false} | Versioned registry record linking an AI system to models, agents, tools, data, providers, owners, policy and evidence. | $.format | true | | {"const":"palo-ai-system-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.systemId | true | string | {"pattern":"^ai-system-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.recordVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.name | true | string | {"minLength":1,"maxLength":300} | | $.useCase | true | string | {"minLength":1,"maxLength":4000} | | $.status | true | | {"enum":["design","pilot","production","suspended","decommissioned"]} | | $.riskClass | true | | {"enum":["minimal","limited","high","prohibited","gpai","systemic-gpai","pending"]} | | $.jurisdictions | true | array | {"minItems":1,"uniqueItems":true} | | $.jurisdictions[] | false | string | {"minLength":1,"maxLength":100} | | $.owners | true | array | {"minItems":1,"uniqueItems":true} | | $.owners[] | false | string | {"minLength":1,"maxLength":500} | | $.relationships | true | object | {"required":["models","agents","tools","dataSubjects","providers"],"additionalProperties":false} | | $.relationships.models | true | / #/$defs/idList | {} | | $.relationships.agents | true | / #/$defs/idList | {} | | $.relationships.tools | true | / #/$defs/idList | {} | | $.relationships.dataSubjects | true | / #/$defs/idList | {} | | $.relationships.providers | true | / #/$defs/idList | {} | | $.deployedVersion | true | string | {"minLength":1,"maxLength":200} | | $.policyBundleDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.evidenceRefs | false | array | {"uniqueItems":true} | | $.evidenceRefs[] | false | string | {"pattern":"^evidence-ref-[a-f0-9-]{36}$"} | | $.updatedAt | true | string | {"format":"date-time"} | | $.$defs.idList | false | array | {"uniqueItems":true,"maxItems":1000} | | $.$defs.idList[] | false | string | {"minLength":1,"maxLength":1000} | PALO ISO IEC 42001 AIMS Overlay Record palo-aims-overlay-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","organization","scope","context","leadership","planning","support","operation","performanceEvaluation","improvement","authorityBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-aims-overlay-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {} | | $.organization | true | string | {} | | $.scope | true | / #/$defs/section | {} | | $.context | true | / #/$defs/section | {} | | $.leadership | true | / #/$defs/section | {} | | $.planning | true | / #/$defs/section | {} | | $.support | true | / #/$defs/section | {} | | $.operation | true | / #/$defs/section | {} | | $.performanceEvaluation | true | / #/$defs/section | {} | | $.improvement | true | / #/$defs/section | {} | | $.authorityBoundary | true | string | {"minLength":40} | | $.$defs.section | false | object | {"required":["owner","requirements","evidenceRefs","status","reviewedAt","reviewedBy","findings"],"additionalProperties":false} | | $.$defs.section.owner | true | string | {} | | $.$defs.section.requirements | true | array | {"minItems":1} | | $.$defs.section.requirements[] | false | string | {} | | $.$defs.section.evidenceRefs | true | array | {"minItems":1} | | $.$defs.section.evidenceRefs[] | false | string | {} | | $.$defs.section.status | true | | {"enum":["implemented","partial","gap","not-applicable"]} | | $.$defs.section.reviewedAt | true | string | {"format":"date-time"} | | $.$defs.section.reviewedBy | true | string | {} | | $.$defs.section.findings | true | array | {} | | $.$defs.section.findings[] | false | string | {} | PALO Article 50 Transparency Record palo-article50-transparency-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","caseId","systemVersion","actorRoles","modalities","interactionNotice","marking","deployerLabelling","provenance","exceptions","releaseDecision"],"additionalProperties":false} | | $.format | true | | {"const":"palo-article50-transparency-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {} | | $.caseId | true | string | {} | | $.systemVersion | true | string | {} | | $.actorRoles | true | array | {"minItems":1,"uniqueItems":true} | | $.actorRoles[] | false | | {"enum":["provider","deployer","importer","distributor","authorized-representative"]} | | $.modalities | true | array | {"minItems":1,"uniqueItems":true} | | $.modalities[] | false | | {"enum":["interactive","text","image","audio","video","biometric-categorisation","emotion-recognition"]} | | $.interactionNotice | true | / #/$defs/testedMeasure | {} | | $.marking | true | object | {"required":["required","method","machineReadable","standardOrProfile","keyOrIssuer","coverageTest"],"additionalProperties":false} | | $.marking.required | true | boolean | {} | | $.marking.method | true | string | {"minLength":3} | | $.marking.machineReadable | true | boolean | {} | | $.marking.standardOrProfile | true | string | {"minLength":3} | | $.marking.keyOrIssuer | true | string | {"minLength":3} | | $.marking.coverageTest | true | / #/$defs/testedMeasure | {} | | $.deployerLabelling | true | array | {} | | $.deployerLabelling[] | false | object | {"required":["contentType","required","label","placement","testResult"],"additionalProperties":false} | | $.deployerLabelling[].contentType | true | string | {} | | $.deployerLabelling[].required | true | boolean | {} | | $.deployerLabelling[].label | true | string | {} | | $.deployerLabelling[].placement | true | string | {} | | $.deployerLabelling[].testResult | true | | {"enum":["pass","conditional","fail","not-applicable"]} | | $.provenance | true | object | {"required":["assertionFormat","boundToContentDigest","verificationTool","transformationTests"],"additionalProperties":false} | | $.provenance.assertionFormat | true | string | {} | | $.provenance.boundToContentDigest | true | boolean | {} | | $.provenance.verificationTool | true | string | {} | | $.provenance.transformationTests | true | array | {"minItems":1} | | $.provenance.transformationTests[] | false | / #/$defs/testedMeasure | {} | | $.exceptions | true | array | {} | | $.exceptions[] | false | object | {"required":["obligation","basis","sourceProvision","approvedBy"],"additionalProperties":false} | | $.exceptions[].obligation | true | string | {} | | $.exceptions[].basis | true | string | {"minLength":20} | | $.exceptions[].sourceProvision | true | string | {} | | $.exceptions[].approvedBy | true | string | {} | | $.releaseDecision | true | object | {"required":["status","decidedAt","decidedBy","validUntil"],"additionalProperties":false} | | $.releaseDecision.status | true | | {"enum":["accepted","conditional","rejected"]} | | $.releaseDecision.decidedAt | true | string | {"format":"date-time"} | | $.releaseDecision.decidedBy | true | string | {} | | $.releaseDecision.validUntil | true | string | {"format":"date-time"} | | $.$defs.testedMeasure | false | object | {"required":["required","implementation","testedAt","result","evidenceRef"],"additionalProperties":false} | | $.$defs.testedMeasure.required | true | boolean | {} | | $.$defs.testedMeasure.implementation | true | string | {} | | $.$defs.testedMeasure.testedAt | true | string | {"format":"date-time"} | | $.$defs.testedMeasure.result | true | | {"enum":["pass","conditional","fail","not-applicable"]} | | $.$defs.testedMeasure.evidenceRef | true | string | {} | PALO Continuous Assurance Signal palo-assurance-signal.schema.json Immutable external change signal that invalidates prior data-fitness assumptions and may revoke unconsumed capabilities. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","signalId","tenantId","subject","sourceSystem","signalType","severity","observedAt","changeDigest","reason"],"additionalProperties":false} | Immutable external change signal that invalidates prior data-fitness assumptions and may revoke unconsumed capabilities. | $.format | true | | {"const":"palo-assurance-signal"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.signalId | true | string | {"pattern":"^assurance-signal-[a-f0-9-]{36}$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.subject | true | object | {"required":["type","id"],"additionalProperties":false} | | $.subject.type | true | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.subject.id | true | string | {"minLength":1,"maxLength":1000} | | $.sourceSystem | true | string | {"minLength":1,"maxLength":100} | | $.signalType | true | | {"enum":["quality-changed","classification-changed","lineage-changed","access-changed","contract-changed","incident-opened","incident-resolved","system-release","policy-release"]} | | $.severity | true | | {"enum":["info","low","medium","high","critical"]} | | $.observedAt | true | string | {"format":"date-time"} | | $.evidenceRefId | false | string | {"pattern":"^evidence-ref-[a-f0-9-]{36}$"} | | $.changeDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.reason | true | string | {"minLength":1,"maxLength":2000} | PALO Case File palo-case-file.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","caseId","title","status","createdAt","updatedAt","context","assessments","evidence","sources","incidents","handoffs"],"additionalProperties":true} | | $.format | true | | {"const":"palo-case-file"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.title | true | string | {"minLength":1,"maxLength":200} | | $.status | true | | {"enum":["draft","active","review","closed","reopened"]} | | $.createdAt | true | string | {"format":"date-time"} | | $.updatedAt | true | string | {"format":"date-time"} | | $.owner | false | string | {"maxLength":200} | | $.context | true | object | {} | | $.assessments | true | array | {} | | $.assessments[] | false | object | {"required":["assessmentId","module","recordedAt","data"],"additionalProperties":true} | | $.assessments[].assessmentId | true | string | {"minLength":1} | | $.assessments[].module | true | string | {"minLength":1} | | $.assessments[].recordedAt | true | string | {"format":"date-time"} | | $.assessments[].data | true | object | {} | | $.evidence | true | array | {} | | $.evidence[] | false | object | {"required":["evidenceId","title","kind","status","recordedAt"],"additionalProperties":true} | | $.evidence[].evidenceId | true | string | {"minLength":1} | | $.evidence[].title | true | string | {"minLength":1} | | $.evidence[].kind | true | string | {"minLength":1} | | $.evidence[].status | true | | {"enum":["open","draft","ready","verified","superseded"]} | | $.evidence[].recordedAt | true | string | {"format":"date-time"} | | $.evidence[].content | false | | {} | | $.sources | true | array | {} | | $.sources[] | false | / #/$defs/source | {} | | $.incidents | true | array | {} | | $.incidents[] | false | object | {"required":["incidentId","triggerId","occurredAt","summary","reopenGates"],"additionalProperties":true} | | $.incidents[].incidentId | true | string | {"minLength":1} | | $.incidents[].triggerId | true | string | {"minLength":1} | | $.incidents[].occurredAt | true | string | {"format":"date-time"} | | $.incidents[].summary | true | string | {"minLength":1} | | $.incidents[].reopenGates | true | array | {"minItems":1,"uniqueItems":true} | | $.incidents[].reopenGates[] | false | string | {} | | $.handoffs | true | array | {} | | $.handoffs[] | false | object | {"required":["handoffId","from","to","createdAt"],"additionalProperties":true} | | $.handoffs[].handoffId | true | string | {"minLength":1} | | $.handoffs[].from | true | string | {"minLength":1} | | $.handoffs[].to | true | string | {"minLength":1} | | $.handoffs[].createdAt | true | string | {"format":"date-time"} | | $.$defs.source | false | object | {"required":["sourceId","title","url","sourceType","publisher","checkedAt","freshness"],"additionalProperties":true} | | $.$defs.source.sourceId | true | string | {"minLength":1} | | $.$defs.source.title | true | string | {"minLength":1} | | $.$defs.source.url | true | string | {"format":"uri"} | | $.$defs.source.sourceType | true | | {"enum":["official","standard","organizational","research","monitoring-signal"]} | | $.$defs.source.publisher | true | string | {"minLength":1} | | $.$defs.source.checkedAt | true | string | {"format":"date-time"} | | $.$defs.source.freshness | true | object | {"required":["status","reviewIntervalDays","nextReviewAt"],"additionalProperties":true} | | $.$defs.source.freshness.status | true | | {"enum":["current","review-due","stale","superseded","unknown"]} | | $.$defs.source.freshness.reviewIntervalDays | true | integer | {"minimum":1,"maximum":3650} | | $.$defs.source.freshness.nextReviewAt | true | string | {"format":"date-time"} | | $.$defs.source.freshness.supersededBy | false | string | {"format":"uri"} | PALO Control Library palo-control-library.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","status","updatedAt","disclaimer","controls"],"additionalProperties":false} | | $.format | true | | {"const":"palo-control-library"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.status | true | | {"const":"educational-non-production"} | | $.updatedAt | true | string | {"format":"date"} | | $.disclaimer | true | string | {"minLength":20} | | $.controls | true | array | {"minItems":1} | | $.controls[] | false | object | {"required":["controlId","title","objective","controlType","lifecycleGates","evidenceKinds","indicatorIds","sourceIds","templateIds"],"additionalProperties":false} | | $.controls[].controlId | true | string | {"pattern":"^ctrl-[a-z0-9-]+$"} | | $.controls[].title | true | string | {"minLength":1} | | $.controls[].objective | true | string | {"minLength":1} | | $.controls[].controlType | true | | {"enum":["preventive","detective","corrective","directive"]} | | $.controls[].lifecycleGates | true | array | {"minItems":1,"uniqueItems":true} | | $.controls[].lifecycleGates[] | false | string | {} | | $.controls[].evidenceKinds | true | array | {"minItems":1,"uniqueItems":true} | | $.controls[].evidenceKinds[] | false | string | {} | | $.controls[].indicatorIds | true | array | {"uniqueItems":true} | | $.controls[].indicatorIds[] | false | string | {} | | $.controls[].sourceIds | true | array | {"minItems":1,"uniqueItems":true} | | $.controls[].sourceIds[] | false | string | {} | | $.controls[].templateIds | true | array | {"uniqueItems":true} | | $.controls[].templateIds[] | false | string | {} | PALO Data Disclosure Contract palo-data-disclosure-contract.schema.json Signed, purpose-bound contract governing data read scope, information egress, provider and region, redaction, tracing and retention. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","disclosureContractId","tenantId","subject","purpose","lawfulBasis","dataScope","egressPolicy","destinationPolicy","tracePolicy","outputPolicy","boundFitnessDecision","issuedAt","expiresAt","status","keyId","algorithm","signature"],"additionalProperties":false} | Signed, purpose-bound contract governing data read scope, information egress, provider and region, redaction, tracing and retention. | $.format | true | | {"const":"palo-data-disclosure-contract"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.disclosureContractId | true | string | {"pattern":"^disclosure-[a-f0-9-]{36}$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.subject | true | / #/$defs/subject | {} | | $.purpose | true | string | {"minLength":1,"maxLength":300} | | $.lawfulBasis | true | | {"enum":["consent","contract","legal-obligation","vital-interests","public-task","legitimate-interests","not-applicable","pending-review"]} | | $.dataScope | true | object | {"required":["sourceRefs","allowedFields","deniedFields","maxRowsRead"],"additionalProperties":false} | | $.dataScope.sourceRefs | true | array | {"minItems":1,"uniqueItems":true} | | $.dataScope.sourceRefs[] | false | string | {"minLength":1,"maxLength":1000} | | $.dataScope.allowedFields | true | array | {"uniqueItems":true,"maxItems":1000} | | $.dataScope.allowedFields[] | false | string | {"minLength":1,"maxLength":500} | | $.dataScope.deniedFields | true | array | {"uniqueItems":true,"maxItems":1000} | | $.dataScope.deniedFields[] | false | string | {"minLength":1,"maxLength":500} | | $.dataScope.maxRowsRead | true | integer | {"minimum":0,"maximum":10000000} | | $.egressPolicy | true | object | {"required":["mode","maxRows","allowedFields","prohibitedCategories","requiredRedactions"],"additionalProperties":false} | | $.egressPolicy.mode | true | | {"enum":["zero-row","aggregated","row-level"]} | | $.egressPolicy.maxRows | true | integer | {"minimum":0,"maximum":1000000} | | $.egressPolicy.allowedFields | true | array | {"uniqueItems":true,"maxItems":1000} | | $.egressPolicy.allowedFields[] | false | string | {"minLength":1,"maxLength":500} | | $.egressPolicy.prohibitedCategories | true | array | {"uniqueItems":true,"maxItems":100} | | $.egressPolicy.prohibitedCategories[] | false | string | {"minLength":1,"maxLength":200} | | $.egressPolicy.requiredRedactions | true | array | {"uniqueItems":true,"maxItems":100} | | $.egressPolicy.requiredRedactions[] | false | string | {"minLength":1,"maxLength":200} | | $.egressPolicy.minimumAggregationGroupSize | false | integer | {"minimum":2,"maximum":1000000} | | $.egressPolicy.allOf[0] | false | | {} | | $.egressPolicy.allOf[0].if | false | | {"required":["mode"]} | | $.egressPolicy.allOf[0].if.mode | true | | {"const":"zero-row"} | | $.egressPolicy.allOf[0].then | false | | {} | | $.egressPolicy.allOf[0].then.maxRows | false | integer | {"const":0} | | $.egressPolicy.allOf[0].then.allowedFields | false | array | {"maxItems":0} | | $.egressPolicy.allOf[1] | false | | {} | | $.egressPolicy.allOf[1].if | false | | {"required":["mode"]} | | $.egressPolicy.allOf[1].if.mode | true | | {"const":"aggregated"} | | $.egressPolicy.allOf[1].then | false | | {"required":["minimumAggregationGroupSize"]} | | $.egressPolicy.allOf[1].then.minimumAggregationGroupSize | true | integer | {} | | $.destinationPolicy | true | object | {"required":["allowedRecipients","allowedProviders","allowedModels","allowedRegions","allowedEndpointHosts"],"additionalProperties":false} | | $.destinationPolicy.allowedRecipients | true | array | {"minItems":1,"uniqueItems":true} | | $.destinationPolicy.allowedRecipients[] | false | string | {"minLength":1,"maxLength":500} | | $.destinationPolicy.allowedProviders | true | array | {"minItems":1,"uniqueItems":true} | | $.destinationPolicy.allowedProviders[] | false | string | {"minLength":1,"maxLength":200} | | $.destinationPolicy.allowedModels | true | array | {"minItems":1,"uniqueItems":true} | | $.destinationPolicy.allowedModels[] | false | string | {"minLength":1,"maxLength":300} | | $.destinationPolicy.allowedRegions | true | array | {"minItems":1,"uniqueItems":true} | | $.destinationPolicy.allowedRegions[] | false | string | {"minLength":1,"maxLength":100} | | $.destinationPolicy.allowedEndpointHosts | true | array | {"minItems":1,"uniqueItems":true} | | $.destinationPolicy.allowedEndpointHosts[] | false | string | {"pattern":"^[a-z0-9.-]+$","maxLength":253} | | $.tracePolicy | true | object | {"required":["allowedModes","maxRetentionSeconds"],"additionalProperties":false} | | $.tracePolicy.allowedModes | true | array | {"minItems":1,"uniqueItems":true} | | $.tracePolicy.allowedModes[] | false | | {"enum":["disabled","metadata-only","redacted-payload"]} | | $.tracePolicy.maxRetentionSeconds | true | integer | {"minimum":0,"maximum":31536000} | | $.outputPolicy | true | object | {"required":["exportAllowed"],"additionalProperties":false} | | $.outputPolicy.exportAllowed | true | boolean | {} | | $.outputPolicy.schemaDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.boundFitnessDecision | true | object | {"required":["decisionId","decisionDigest"],"additionalProperties":false} | | $.boundFitnessDecision.decisionId | true | string | {"pattern":"^fitness-decision-[a-f0-9-]{36}$"} | | $.boundFitnessDecision.decisionDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.approvedBy | false | string | {"minLength":1,"maxLength":500} | | $.issuedAt | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | | $.status | true | | {"enum":["active","revoked"]} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"const":"HMAC-SHA256"} | | $.signature | true | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.$defs.subject | false | object | {"required":["type","id"],"additionalProperties":false} | | $.$defs.subject.type | true | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.$defs.subject.id | true | string | {"minLength":1,"maxLength":1000} | PALO Data Disclosure Observation palo-data-disclosure-observation.schema.json Payload-minimized metadata observed by a trusted executor about rows read and information actually disclosed. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","sourceRefs","fieldsRead","rowsRead","egressFields","egressRows","sensitiveCategories","redactionsApplied","destination","trace","exported","queryDigest","payloadDigest","observedAt"],"additionalProperties":false} | Payload-minimized metadata observed by a trusted executor about rows read and information actually disclosed. | $.format | true | | {"const":"palo-data-disclosure-observation"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.sourceRefs | true | array | {"minItems":1,"uniqueItems":true} | | $.sourceRefs[] | false | string | {"minLength":1,"maxLength":1000} | | $.fieldsRead | true | array | {"uniqueItems":true,"maxItems":1000} | | $.fieldsRead[] | false | string | {"minLength":1,"maxLength":500} | | $.rowsRead | true | integer | {"minimum":0,"maximum":10000000} | | $.egressFields | true | array | {"uniqueItems":true,"maxItems":1000} | | $.egressFields[] | false | string | {"minLength":1,"maxLength":500} | | $.egressRows | true | integer | {"minimum":0,"maximum":1000000} | | $.aggregationGroupSize | false | integer | {"minimum":1,"maximum":10000000} | | $.sensitiveCategories | true | array | {"uniqueItems":true,"maxItems":100} | | $.sensitiveCategories[] | false | string | {"minLength":1,"maxLength":200} | | $.redactionsApplied | true | array | {"uniqueItems":true,"maxItems":100} | | $.redactionsApplied[] | false | string | {"minLength":1,"maxLength":200} | | $.destination | true | object | {"required":["recipient","provider","model","region","endpointHost"],"additionalProperties":false} | | $.destination.recipient | true | string | {"minLength":1,"maxLength":500} | | $.destination.provider | true | string | {"minLength":1,"maxLength":200} | | $.destination.model | true | string | {"minLength":1,"maxLength":300} | | $.destination.region | true | string | {"minLength":1,"maxLength":100} | | $.destination.endpointHost | true | string | {"pattern":"^[a-z0-9.-]+$","maxLength":253} | | $.trace | true | object | {"required":["mode","retentionSeconds"],"additionalProperties":false} | | $.trace.mode | true | | {"enum":["disabled","metadata-only","redacted-payload"]} | | $.trace.retentionSeconds | true | integer | {"minimum":0,"maximum":31536000} | | $.exported | true | boolean | {} | | $.outputSchemaDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.queryDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.payloadDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.observedAt | true | string | {"format":"date-time"} | PALO Data Disclosure Receipt palo-data-disclosure-receipt.schema.json Signed comparison between a Data Disclosure Contract and payload-minimized executor observations. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","receiptId","disclosureContractId","executionId","claimId","executorId","status","observationDigest","checks","checkedAt","keyId","algorithm","signature"],"additionalProperties":false} | Signed comparison between a Data Disclosure Contract and payload-minimized executor observations. | $.format | true | | {"const":"palo-data-disclosure-receipt"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.receiptId | true | string | {"pattern":"^disclosure-receipt-[a-f0-9-]{36}$"} | | $.disclosureContractId | true | string | {"pattern":"^disclosure-[a-f0-9-]{36}$"} | | $.executionId | true | string | {"pattern":"^execution-[a-f0-9-]{36}$"} | | $.claimId | true | string | {"pattern":"^claim-[a-f0-9-]{36}$"} | | $.executorId | true | string | {"pattern":"^executor-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.status | true | | {"enum":["verified","mismatch","inconclusive"]} | | $.observationDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.observedSummary | false | / palo-data-disclosure-observation.schema.json | {} | | $.checks | true | array | {"minItems":1,"maxItems":200} | | $.checks[] | false | object | {"required":["predicateId","category","status","reason"],"additionalProperties":false} | | $.checks[].predicateId | true | string | {"pattern":"^predicate-[a-zA-Z0-9._-]{1,100}$"} | | $.checks[].category | true | | {"const":"forbidden"} | | $.checks[].status | true | | {"enum":["pass","fail","unknown"]} | | $.checks[].reason | true | string | {"minLength":1,"maxLength":1000} | | $.checkedAt | true | string | {"format":"date-time"} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.algorithm | true | | {"const":"HMAC-SHA256"} | | $.signature | true | string | {"pattern":"^hmac-sha256:[a-f0-9]{64}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["status"]} | | $.allOf[0].if.status | true | | {"enum":["verified","mismatch"]} | | $.allOf[0].then | false | | {"required":["observedSummary"]} | | $.allOf[0].then.observedSummary | true | | {} | PALO Data Fitness Decision palo-data-fitness-decision.schema.json Immutable decision binding one subject, purpose, policy version and exact external evidence references. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","decisionId","tenantId","subject","purpose","policyId","policyVersion","status","checks","evidenceRefs","evidenceDigest","decidedAt","expiresAt"],"additionalProperties":false} | Immutable decision binding one subject, purpose, policy version and exact external evidence references. | $.format | true | | {"const":"palo-data-fitness-decision"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.decisionId | true | string | {"pattern":"^fitness-decision-[a-f0-9-]{36}$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.subject | true | object | {"required":["type","id"],"additionalProperties":false} | | $.subject.type | true | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.subject.id | true | string | {"minLength":1,"maxLength":1000} | | $.purpose | true | string | {"minLength":1,"maxLength":300} | | $.policyId | true | string | {"pattern":"^fitness-policy-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.policyVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.status | true | | {"enum":["allowed","denied","review_required"]} | | $.checks | true | array | {"minItems":1,"maxItems":200} | | $.checks[] | false | object | {"required":["checkId","status","reason","evidenceRefIds"],"additionalProperties":false} | | $.checks[].checkId | true | string | {"pattern":"^fitness-check-[a-zA-Z0-9._-]{1,100}$"} | | $.checks[].status | true | | {"enum":["pass","fail","unknown"]} | | $.checks[].reason | true | string | {"minLength":1,"maxLength":1000} | | $.checks[].evidenceRefIds | true | array | {"uniqueItems":true} | | $.checks[].evidenceRefIds[] | false | string | {"pattern":"^evidence-ref-[a-f0-9-]{36}$"} | | $.evidenceRefs | true | array | {"uniqueItems":true} | | $.evidenceRefs[] | false | string | {"pattern":"^evidence-ref-[a-f0-9-]{36}$"} | | $.evidenceDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.decidedAt | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | PALO Data Fitness Policy palo-data-fitness-policy.schema.json Deterministic policy for deciding whether externally referenced data context is fit for a declared purpose. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","policyId","policyVersion","tenantId","targetTypes","requiredEvidenceTypes","requirements","onMissing","effectiveAt","status"],"additionalProperties":false} | Deterministic policy for deciding whether externally referenced data context is fit for a declared purpose. | $.format | true | | {"const":"palo-data-fitness-policy"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.policyId | true | string | {"pattern":"^fitness-policy-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.policyVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.targetTypes | true | array | {"minItems":1,"uniqueItems":true} | | $.targetTypes[] | false | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.requiredEvidenceTypes | true | array | {"minItems":1,"uniqueItems":true} | | $.requiredEvidenceTypes[] | false | | {"enum":["metadata","lineage","quality","classification","ownership","access","data-contract","audit","incident","other"]} | | $.requirements | true | object | {"minProperties":1,"additionalProperties":false} | | $.requirements.minQualityScore | false | number | {"minimum":0,"maximum":100} | | $.requirements.maxEvidenceAgeSeconds | false | integer | {"minimum":1,"maximum":31536000} | | $.requirements.requireVerifiedAuthority | false | boolean | {} | | $.requirements.requireOwner | false | boolean | {} | | $.requirements.requireApproved | false | boolean | {} | | $.requirements.requireLineage | false | boolean | {} | | $.requirements.requireAccessGranted | false | boolean | {} | | $.requirements.denyOpenIncident | false | boolean | {} | | $.requirements.prohibitedClassifications | false | array | {"uniqueItems":true,"maxItems":100} | | $.requirements.prohibitedClassifications[] | false | string | {"minLength":1,"maxLength":200} | | $.requirements.allowedPurposes | false | array | {"minItems":1,"uniqueItems":true,"maxItems":100} | | $.requirements.allowedPurposes[] | false | string | {"minLength":1,"maxLength":300} | | $.onMissing | true | | {"enum":["deny","review"]} | | $.effectiveAt | true | string | {"format":"date-time"} | | $.status | true | | {"enum":["active","inactive"]} | PALO Data Lineage and Lifecycle Record palo-data-lineage-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","caseId","asset","origins","transformations","permissions","privacy","annotation","quality","uses","retention","deletion","owner","review"],"additionalProperties":false} | | $.format | true | | {"const":"palo-data-lineage-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {} | | $.caseId | true | string | {} | | $.asset | true | object | {"required":["assetId","name","version","role","digest","materiality"],"additionalProperties":false} | | $.asset.assetId | true | string | {} | | $.asset.name | true | string | {} | | $.asset.version | true | string | {} | | $.asset.role | true | | {"enum":["training","fine-tuning","evaluation","prompt","retrieval","embedding","operational-input","generated-output","derived","other"]} | | $.asset.digest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.asset.materiality | true | | {"enum":["low","moderate","high","critical"]} | | $.origins | true | array | {"minItems":1} | | $.origins[] | false | object | {"required":["sourceId","sourceType","collectedAt","collector","geography"],"additionalProperties":false} | | $.origins[].sourceId | true | string | {} | | $.origins[].sourceType | true | | {"enum":["first-party","licensed","open","public","synthetic","user-provided","vendor","unknown"]} | | $.origins[].collectedAt | true | string | {"format":"date-time"} | | $.origins[].collector | true | string | {} | | $.origins[].geography | true | string | {} | | $.transformations | true | array | {} | | $.transformations[] | false | object | {"required":["stepId","operation","performedAt","toolVersion","outputDigest"],"additionalProperties":false} | | $.transformations[].stepId | true | string | {} | | $.transformations[].operation | true | string | {} | | $.transformations[].performedAt | true | string | {"format":"date-time"} | | $.transformations[].toolVersion | true | string | {} | | $.transformations[].outputDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.permissions | true | object | {"required":["basis","licenseOrTerms","permittedUses","prohibitedUses","reviewedBy"],"additionalProperties":false} | | $.permissions.basis | true | | {"enum":["ownership","contract","license","consent","law","public-domain","undetermined"]} | | $.permissions.licenseOrTerms | true | string | {} | | $.permissions.permittedUses | true | / #/$defs/strings | {} | | $.permissions.prohibitedUses | true | array | {} | | $.permissions.prohibitedUses[] | false | string | {} | | $.permissions.reviewedBy | true | string | {} | | $.privacy | true | object | {"required":["personalData","specialCategoryData","controllerOrProcessorRole","lawfulBasis","necessityAssessment","rightsRoute"],"additionalProperties":false} | | $.privacy.personalData | true | boolean | {} | | $.privacy.specialCategoryData | true | boolean | {} | | $.privacy.controllerOrProcessorRole | true | | {"enum":["controller","joint-controller","processor","sub-processor","not-applicable","undetermined"]} | | $.privacy.lawfulBasis | true | string | {} | | $.privacy.necessityAssessment | true | string | {} | | $.privacy.rightsRoute | true | string | {} | | $.annotation | true | object | {"required":["applicable","protocolRef","annotatorCompetenceRef","agreementMeasure","disputeRoute"],"additionalProperties":false} | | $.annotation.applicable | true | boolean | {} | | $.annotation.protocolRef | true | string | {} | | $.annotation.annotatorCompetenceRef | true | string | {} | | $.annotation.agreementMeasure | true | string | {} | | $.annotation.disputeRoute | true | string | {} | | $.quality | true | object | {"required":["dimensions","knownLimits","acceptedAt","acceptedBy"],"additionalProperties":false} | | $.quality.dimensions | true | array | {"minItems":1} | | $.quality.dimensions[] | false | object | {"required":["name","result","thresholdDecision"],"additionalProperties":false} | | $.quality.dimensions[].name | true | string | {} | | $.quality.dimensions[].result | true | string | {} | | $.quality.dimensions[].thresholdDecision | true | | {"enum":["pass","conditional","fail"]} | | $.quality.knownLimits | true | / #/$defs/strings | {} | | $.quality.acceptedAt | true | string | {"format":"date-time"} | | $.quality.acceptedBy | true | string | {} | | $.uses | true | array | {"minItems":1} | | $.uses[] | false | object | {"required":["systemVersion","purpose","approved"],"additionalProperties":false} | | $.uses[].systemVersion | true | string | {} | | $.uses[].purpose | true | string | {} | | $.uses[].approved | true | boolean | {} | | $.retention | true | object | {"required":["period","trigger","legalHoldRoute","nextReviewAt"],"additionalProperties":false} | | $.retention.period | true | string | {} | | $.retention.trigger | true | string | {} | | $.retention.legalHoldRoute | true | string | {} | | $.retention.nextReviewAt | true | string | {"format":"date-time"} | | $.deletion | true | object | {"required":["method","covers","verification","dueAt"],"additionalProperties":false} | | $.deletion.method | true | string | {} | | $.deletion.covers | true | / #/$defs/strings | {} | | $.deletion.verification | true | string | {} | | $.deletion.dueAt | true | string | {"format":"date-time"} | | $.owner | true | string | {} | | $.review | true | object | {"required":["status","reviewedAt","reviewedBy","validUntil"],"additionalProperties":false} | | $.review.status | true | | {"enum":["accepted","conditional","rejected"]} | | $.review.reviewedAt | true | string | {"format":"date-time"} | | $.review.reviewedBy | true | string | {} | | $.review.validUntil | true | string | {"format":"date-time"} | | $.$defs.strings | false | array | {"minItems":1,"uniqueItems":true} | | $.$defs.strings[] | false | string | {"minLength":1} | PALO Decision Gates palo-decision-gates.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","status","updatedAt","disclaimer","gates"],"additionalProperties":false} | | $.format | true | | {"const":"palo-decision-gates"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.status | true | | {"const":"educational-non-production"} | | $.updatedAt | true | string | {"format":"date"} | | $.disclaimer | true | string | {"minLength":20} | | $.gates | true | array | {"minItems":1} | | $.gates[] | false | object | {"required":["gateId","label","purpose","entryCriteria","decisionOptions","requiredControlIds","conditionalControlIds","indicatorIds","sourceIds","templateIds"],"additionalProperties":false} | | $.gates[].gateId | true | | {"enum":["frame","classify","assess","control","measure","prove"]} | | $.gates[].label | true | string | {"minLength":1} | | $.gates[].purpose | true | string | {"minLength":1} | | $.gates[].entryCriteria | true | array | {"minItems":1} | | $.gates[].entryCriteria[] | false | string | {} | | $.gates[].decisionOptions | true | array | {"minItems":2,"uniqueItems":true} | | $.gates[].decisionOptions[] | false | | {"enum":["proceed","proceed-with-conditions","hold","redesign","stop"]} | | $.gates[].requiredControlIds | true | array | {"uniqueItems":true} | | $.gates[].requiredControlIds[] | false | string | {} | | $.gates[].conditionalControlIds | true | array | {"uniqueItems":true} | | $.gates[].conditionalControlIds[] | false | string | {} | | $.gates[].indicatorIds | true | array | {"uniqueItems":true} | | $.gates[].indicatorIds[] | false | string | {} | | $.gates[].sourceIds | true | array | {"minItems":1,"uniqueItems":true} | | $.gates[].sourceIds[] | false | string | {} | | $.gates[].templateIds | true | array | {"uniqueItems":true} | | $.gates[].templateIds[] | false | string | {} | PALO AI System Decommission Record palo-decommission-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","caseId","systemVersion","reason","plan","stakeholders","capabilityRevocation","dataDisposition","supplierExit","residualMonitoring","closureDecision"],"additionalProperties":false} | | $.format | true | | {"const":"palo-decommission-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {} | | $.caseId | true | string | {} | | $.systemVersion | true | string | {} | | $.reason | true | string | {"minLength":20} | | $.plan | true | object | {"required":["owner","approvedAt","targetEndAt","rollbackWindow","dependencies"],"additionalProperties":false} | | $.plan.owner | true | string | {} | | $.plan.approvedAt | true | string | {"format":"date-time"} | | $.plan.targetEndAt | true | string | {"format":"date-time"} | | $.plan.rollbackWindow | true | string | {} | | $.plan.dependencies | true | array | {} | | $.plan.dependencies[] | false | string | {} | | $.stakeholders | true | array | {"minItems":1} | | $.stakeholders[] | false | object | {"required":["group","noticeAt","transitionRoute","supportOwner"],"additionalProperties":false} | | $.stakeholders[].group | true | string | {} | | $.stakeholders[].noticeAt | true | string | {"format":"date-time"} | | $.stakeholders[].transitionRoute | true | string | {} | | $.stakeholders[].supportOwner | true | string | {} | | $.capabilityRevocation | true | / #/$defs/closureCheck | {} | | $.dataDisposition | true | array | {"minItems":1} | | $.dataDisposition[] | false | object | {"required":["assetId","action","dueAt","verificationRef","status"],"additionalProperties":false} | | $.dataDisposition[].assetId | true | string | {} | | $.dataDisposition[].action | true | | {"enum":["delete","archive","return","transfer","legal-hold","anonymize"]} | | $.dataDisposition[].dueAt | true | string | {"format":"date-time"} | | $.dataDisposition[].verificationRef | true | string | {} | | $.dataDisposition[].status | true | | {"enum":["planned","in-progress","verified-complete"]} | | $.supplierExit | true | / #/$defs/closureCheck | {} | | $.residualMonitoring | true | object | {"required":["period","owner","indicators","reopenTriggers"],"additionalProperties":false} | | $.residualMonitoring.period | true | string | {} | | $.residualMonitoring.owner | true | string | {} | | $.residualMonitoring.indicators | true | array | {"minItems":1} | | $.residualMonitoring.indicators[] | false | string | {} | | $.residualMonitoring.reopenTriggers | true | array | {"minItems":1} | | $.residualMonitoring.reopenTriggers[] | false | string | {} | | $.closureDecision | true | object | {"required":["status","decidedAt","decidedBy","evidenceRefs"],"additionalProperties":false} | | $.closureDecision.status | true | | {"enum":["conditional","closed","rejected"]} | | $.closureDecision.decidedAt | true | string | {"format":"date-time"} | | $.closureDecision.decidedBy | true | string | {} | | $.closureDecision.evidenceRefs | true | array | {"minItems":1} | | $.closureDecision.evidenceRefs[] | false | string | {} | | $.$defs.closureCheck | false | object | {"required":["status","verifiedAt","verifiedBy","evidenceRef"],"additionalProperties":false} | | $.$defs.closureCheck.status | true | | {"enum":["planned","in-progress","verified-complete","not-applicable"]} | | $.$defs.closureCheck.verifiedAt | true | string | {"format":"date-time"} | | $.$defs.closureCheck.verifiedBy | true | string | {} | | $.$defs.closureCheck.evidenceRef | true | string | {} | PALO scoped dependency and governance graph palo-dependency-graph.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","extensionVersion","tenantId","snapshotAt","evidenceClass","authorityBoundary","nodes","edges"],"additionalProperties":false} | | $.format | true | | {"const":"palo-dependency-graph"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.extensionVersion | true | | {"const":"0.1.0"} | | $.tenantId | true | string | {"minLength":1} | | $.snapshotAt | true | string | {"format":"date-time"} | | $.evidenceClass | true | | {"enum":["illustrative-local-preview","human-review-required"]} | | $.authorityBoundary | true | string | {"minLength":1} | | $.nodes | true | array | {"minItems":1} | | $.nodes[] | false | object | {"required":["id","label","type","recordedAt","validFrom","sourceRefs","properties"],"additionalProperties":false} | | $.nodes[].id | true | string | {"pattern":"^[a-zA-Z0-9][a-zA-Z0-9:._-]{0,159}$"} | | $.nodes[].recordedAt | true | string | {"format":"date-time"} | | $.nodes[].validFrom | true | string | {"format":"date-time"} | | $.nodes[].validTo | false | string | {"format":"date-time"} | | $.nodes[].sourceRefs | true | array | {"uniqueItems":true} | | $.nodes[].sourceRefs[] | false | string | {"minLength":1} | | $.nodes[].label | true | string | {"minLength":1} | | $.nodes[].type | true | | {"enum":["Layer","Capability","GovernancePlane","ComponentVersion","AISystemVersion","Agent","ModelVersion","Tool","DataAsset","Provider","Service","PublicPolicy","PolicyVersion","ChangeSignal","GovernanceCase","ApplicabilityAssessment","RequirementVersion","ControlDefinition","ControlImplementation","EvidenceArtifact","EvidenceClaim","EvidenceEvaluation","GateInstance","GateDecisionRecord","Actor"]} | | $.nodes[].version | false | string | {"minLength":1} | | $.nodes[].canonicalRef | false | string | {"format":"uri"} | | $.nodes[].properties | true | object | {} | | $.edges | true | array | {} | | $.edges[] | false | object | {"required":["id","source","target","relation","recordedAt","validFrom","sourceRefs","reviewState","mappingBasis","evidenceRefs"],"additionalProperties":false} | | $.edges[].id | true | string | {"pattern":"^[a-zA-Z0-9][a-zA-Z0-9:._-]{0,159}$"} | | $.edges[].recordedAt | true | string | {"format":"date-time"} | | $.edges[].validFrom | true | string | {"format":"date-time"} | | $.edges[].validTo | false | string | {"format":"date-time"} | | $.edges[].sourceRefs | true | array | {"uniqueItems":true} | | $.edges[].sourceRefs[] | false | string | {"minLength":1} | | $.edges[].source | true | string | {"minLength":1} | | $.edges[].target | true | string | {"minLength":1} | | $.edges[].relation | true | | {"enum":["PROVIDES_CAPABILITY","BELONGS_TO_LAYER","GOVERNS_LAYER","INFORMS","OFFERS","USES_SERVICE","DEPENDS_ON","USES_MODEL","CALLS_TOOL","READS","HAS_VERSION","FROM_VERSION","TO_VERSION","AFFECTS_SERVICE","GOVERNS_VERSION","ASSESSES_SIGNAL","ASSESSES_SYSTEM","IN_CASE","CONSIDERS_REQUIREMENT","REVIEWED_BY","IMPLEMENTS","ADDRESSES_REQUIREMENT","APPLIES_TO_SYSTEM","USES_ARTIFACT","SUPPORTS_TARGET","EVALUATES_CLAIM","REVIEWS_SYSTEM","DECISION_FOR_GATE","DECIDED_BY","BASED_ON_ASSESSMENT","SUPERSEDES"]} | | $.edges[].reviewState | true | | {"enum":["proposed","accepted","rejected"]} | | $.edges[].mappingBasis | true | string | {"minLength":1} | | $.edges[].evidenceRefs | true | array | {"uniqueItems":true} | | $.edges[].evidenceRefs[] | false | string | {"minLength":1} | PALO EU agentic review inventory; not an attestation palo-eu-agentic-review.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"additionalProperties":false,"required":["format","profileVersion","sourceReviewDate","createdAt","status","system","controls","limitations"]} | | $.format | true | | {"const":"palo-eu-agentic-review"} | | $.profileVersion | true | | {"const":"0.2.0"} | | $.sourceReviewDate | true | | {"const":"2026-09-22"} | | $.createdAt | true | string | {"format":"date-time","pattern":"^\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}\\.\\d{3}Z$"} | | $.status | true | | {"const":"self-declared-review-not-certification"} | | $.system | true | object | {"additionalProperties":false,"required":["name","owner","context","reviewer"]} | | $.system.name | true | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.system.owner | true | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.system.context | true | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.system.reviewer | true | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.controls | true | array | {"minItems":12,"maxItems":12} | | $.controls[] | false | object | {"additionalProperties":false,"required":["id","state","evidence","note","reviewer"]} | | $.controls[].id | true | | {"enum":["DAG-01","DAG-02","DAG-03","DAG-04","DAG-05","DAG-06","DAG-07","DAG-08","DAG-09","DAG-10","DAG-11","DAG-12"]} | | $.controls[].state | true | | {"enum":["missing","claimed","reviewed","not-applicable"]} | | $.controls[].evidence | true | string | {"maxLength":4000} | | $.controls[].note | true | string | {"maxLength":4000} | | $.controls[].reviewer | true | string | {"maxLength":4000} | | $.controls[].allOf[0] | false | | {} | | $.controls[].allOf[0].if | false | | {} | | $.controls[].allOf[0].if.state | false | | {"const":"reviewed"} | | $.controls[].allOf[0].then | false | | {} | | $.controls[].allOf[0].then.evidence | false | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.controls[].allOf[0].then.reviewer | false | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.controls[].allOf[1] | false | | {} | | $.controls[].allOf[1].if | false | | {} | | $.controls[].allOf[1].if.state | false | | {"const":"not-applicable"} | | $.controls[].allOf[1].then | false | | {} | | $.controls[].allOf[1].then.note | false | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.controls[].allOf[1].then.reviewer | false | string | {"minLength":1,"maxLength":4000,"pattern":"\\S"} | | $.controls.allOf[0] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[0].contains | false | object | {"required":["id"]} | | $.controls.allOf[0].contains.id | true | | {"const":"DAG-01"} | | $.controls.allOf[1] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[1].contains | false | object | {"required":["id"]} | | $.controls.allOf[1].contains.id | true | | {"const":"DAG-02"} | | $.controls.allOf[2] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[2].contains | false | object | {"required":["id"]} | | $.controls.allOf[2].contains.id | true | | {"const":"DAG-03"} | | $.controls.allOf[3] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[3].contains | false | object | {"required":["id"]} | | $.controls.allOf[3].contains.id | true | | {"const":"DAG-04"} | | $.controls.allOf[4] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[4].contains | false | object | {"required":["id"]} | | $.controls.allOf[4].contains.id | true | | {"const":"DAG-05"} | | $.controls.allOf[5] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[5].contains | false | object | {"required":["id"]} | | $.controls.allOf[5].contains.id | true | | {"const":"DAG-06"} | | $.controls.allOf[6] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[6].contains | false | object | {"required":["id"]} | | $.controls.allOf[6].contains.id | true | | {"const":"DAG-07"} | | $.controls.allOf[7] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[7].contains | false | object | {"required":["id"]} | | $.controls.allOf[7].contains.id | true | | {"const":"DAG-08"} | | $.controls.allOf[8] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[8].contains | false | object | {"required":["id"]} | | $.controls.allOf[8].contains.id | true | | {"const":"DAG-09"} | | $.controls.allOf[9] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[9].contains | false | object | {"required":["id"]} | | $.controls.allOf[9].contains.id | true | | {"const":"DAG-10"} | | $.controls.allOf[10] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[10].contains | false | object | {"required":["id"]} | | $.controls.allOf[10].contains.id | true | | {"const":"DAG-11"} | | $.controls.allOf[11] | false | | {"minContains":1,"maxContains":1} | | $.controls.allOf[11].contains | false | object | {"required":["id"]} | | $.controls.allOf[11].contains.id | true | | {"const":"DAG-12"} | | $.limitations | true | | {"const":"Inventory of reviewer declarations only. Evidence authenticity, adequacy, legal compliance and production readiness are not verified."} | PALO Evidence Artifact palo-evidence-artifact.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","artifactId","caseId","artifactType","title","mediaType","recordedAt","contentDigest","storageReference","provenance","sensitivity","status"],"additionalProperties":false} | | $.format | true | | {"const":"palo-evidence-artifact"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.artifactId | true | string | {"pattern":"^evidence-artifact-[a-z0-9][a-z0-9-]{5,80}$"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.artifactType | true | string | {"minLength":1} | | $.title | true | string | {"minLength":1} | | $.mediaType | true | string | {"pattern":"^[a-z0-9.+-]+/[a-z0-9.+-]+$"} | | $.recordedAt | true | string | {"format":"date-time"} | | $.contentDigest | true | / #/$defs/digest | {} | | $.storageReference | true | string | {"format":"uri"} | | $.provenance | true | object | {"required":["producerId","captureMethod","sourceSystem"],"additionalProperties":false} | | $.provenance.producerId | true | string | {"minLength":1} | | $.provenance.captureMethod | true | | {"enum":["generated","exported","observed","uploaded","signed-receipt"]} | | $.provenance.sourceSystem | true | string | {"minLength":1} | | $.sensitivity | true | | {"enum":["public","internal","confidential","restricted"]} | | $.status | true | | {"enum":["draft","ready","verified","superseded","revoked"]} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO Evidence Bundle Manifest palo-evidence-bundle-manifest.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","bundleId","caseId","assessmentRunId","generatedAt","lifecycleDefinitionRef","semanticReleaseManifestRef","semanticReleaseDigest","items","bundleDigest","authorityBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-evidence-bundle-manifest"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.bundleId | true | string | {"pattern":"^bundle-[a-z0-9][a-z0-9-]{5,63}$"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.assessmentRunId | true | string | {"pattern":"^assessment-run-[a-z0-9][a-z0-9-]{5,80}$"} | | $.generatedAt | true | string | {"format":"date-time"} | | $.lifecycleDefinitionRef | true | string | {"format":"uri"} | | $.semanticReleaseManifestRef | true | string | {"minLength":1} | | $.semanticReleaseDigest | true | / #/$defs/digest | {} | | $.items | true | array | {"minItems":1} | | $.items[] | false | object | {"required":["itemType","recordId","recordDigest"],"additionalProperties":false} | | $.items[].itemType | true | | {"enum":["evidence-artifact","evidence-claim","evidence-evaluation","gate-decision","metric-observation","source-record"]} | | $.items[].recordId | true | string | {"minLength":1} | | $.items[].recordDigest | true | / #/$defs/digest | {} | | $.bundleDigest | true | / #/$defs/digest | {} | | $.authorityBoundary | true | string | {"minLength":1} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO Evidence Bundle palo-evidence-bundle.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","bundleId","generatedAt","artifacts","sourceRegistry","freshness"],"additionalProperties":true} | | $.format | true | | {"const":"palo-evidence-bundle"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.bundleId | true | string | {"pattern":"^bundle-[a-z0-9][a-z0-9-]{5,63}$"} | | $.caseId | false | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.generatedAt | true | string | {"format":"date-time"} | | $.assessment | false | object | {} | | $.route | false | array | {} | | $.route[] | false | object | {} | | $.evidenceReadiness | false | object | {"additionalProperties":{"type":"boolean"}} | | $.evidenceReadiness.additionalProperties | false | boolean | {} | | $.artifacts | true | array | {} | | $.artifacts[] | false | object | {"required":["artifactId","title","kind","status"],"additionalProperties":true} | | $.artifacts[].artifactId | true | string | {"minLength":1} | | $.artifacts[].title | true | string | {"minLength":1} | | $.artifacts[].kind | true | string | {"minLength":1} | | $.artifacts[].status | true | | {"enum":["open","draft","ready","verified","superseded"]} | | $.artifacts[].content | false | | {} | | $.sourceRegistry | true | array | {} | | $.sourceRegistry[] | false | / palo-case-file.schema.json#/$defs/source | {} | | $.freshness | true | object | {"required":["evaluatedAt","status"],"additionalProperties":true} | | $.freshness.evaluatedAt | true | string | {"format":"date-time"} | | $.freshness.status | true | | {"enum":["current","review-due","stale","unknown"]} | | $.disclaimer | false | string | {} | PALO Atomic Evidence Claim palo-evidence-claim.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","claimId","artifactId","target","scope","statement","integrityReference","createdAt","status","appendOnly"],"additionalProperties":false} | | $.format | true | | {"const":"palo-evidence-claim"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.claimId | true | string | {"pattern":"^evidence-claim-[a-z0-9][a-z0-9-]{5,80}$"} | | $.artifactId | true | string | {"pattern":"^evidence-artifact-[a-z0-9][a-z0-9-]{5,80}$"} | | $.target | true | object | {"required":["targetType","targetId"],"additionalProperties":false} | | $.target.targetType | true | | {"enum":["gate-instance","control-implementation","metric-observation","decision-record","assessment-run","agentic-execution"]} | | $.target.targetId | true | string | {"minLength":1} | | $.scope | true | object | {"required":["caseId","validFrom"],"additionalProperties":false} | | $.scope.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.scope.validFrom | true | string | {"format":"date-time"} | | $.scope.validTo | false | string | {"format":"date-time"} | | $.statement | true | string | {"minLength":1} | | $.integrityReference | true | / #/$defs/digest | {} | | $.createdAt | true | string | {"format":"date-time"} | | $.status | true | | {"enum":["asserted","under-review","accepted","rejected","superseded"]} | | $.supersedesClaimId | false | string | {"pattern":"^evidence-claim-[a-z0-9][a-z0-9-]{5,80}$"} | | $.appendOnly | true | | {"const":true} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO Evidence Evaluation palo-evidence-evaluation.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","evaluationId","claimId","assessmentRunId","evaluator","evaluatedAt","outcome","quality","rationale","inputClaimDigest","recordDigest","appendOnly"],"additionalProperties":false} | | $.format | true | | {"const":"palo-evidence-evaluation"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.evaluationId | true | string | {"pattern":"^evidence-evaluation-[a-z0-9][a-z0-9-]{5,80}$"} | | $.claimId | true | string | {"pattern":"^evidence-claim-[a-z0-9][a-z0-9-]{5,80}$"} | | $.assessmentRunId | true | string | {"pattern":"^assessment-run-[a-z0-9][a-z0-9-]{5,80}$"} | | $.evaluator | true | object | {"required":["actorId","role"],"additionalProperties":false} | | $.evaluator.actorId | true | string | {"minLength":1} | | $.evaluator.role | true | string | {"minLength":1} | | $.evaluatedAt | true | string | {"format":"date-time"} | | $.outcome | true | | {"enum":["sufficient","partial","insufficient","unverified"]} | | $.quality | true | object | {"required":["relevance","integrity","recency","independence"],"additionalProperties":false} | | $.quality.relevance | true | / #/$defs/score | {} | | $.quality.integrity | true | / #/$defs/score | {} | | $.quality.recency | true | / #/$defs/score | {} | | $.quality.independence | true | / #/$defs/score | {} | | $.rationale | true | string | {"minLength":1} | | $.inputClaimDigest | true | / #/$defs/digest | {} | | $.recordDigest | true | / #/$defs/digest | {} | | $.appendOnly | true | | {"const":true} | | $.$defs.score | false | number | {"minimum":0,"maximum":1} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO External Agentic Evidence Collection palo-external-agentic-evidence.schema.json Metadata-minimized external observations that can inform, but never replace, a PALO use-case assessment. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","providerId","retrievedAt","sourcePayloadDigest","signals","ingestion","boundary","collectionDigest"],"additionalProperties":false} | Metadata-minimized external observations that can inform, but never replace, a PALO use-case assessment. | $.format | true | | {"const":"palo-external-agentic-evidence-collection"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.providerId | true | string | {"pattern":"^[a-z][a-z0-9-]{2,63}$"} | | $.retrievedAt | true | string | {"format":"date-time"} | | $.sourcePayloadDigest | true | / #/$defs/digest | {} | | $.signals | true | array | {"maxItems":1000} | | $.signals[] | false | / #/$defs/signal | {} | | $.ingestion | true | object | {"required":["received","accepted","deduplicated","skipped"],"additionalProperties":false} | | $.ingestion.received | true | integer | {"minimum":0} | | $.ingestion.accepted | true | integer | {"minimum":0} | | $.ingestion.deduplicated | true | integer | {"minimum":0} | | $.ingestion.skipped | true | integer | {"minimum":0} | | $.boundary | true | / #/$defs/boundary | {} | | $.collectionDigest | true | / #/$defs/digest | {} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.$defs.boundary | false | object | {"required":["externalCapabilityEvidence","notUseCaseRiskScore","requiresLocalAssessment","networkOptional"],"additionalProperties":false} | | $.$defs.boundary.externalCapabilityEvidence | true | | {"const":true} | | $.$defs.boundary.notUseCaseRiskScore | true | | {"const":true} | | $.$defs.boundary.requiresLocalAssessment | true | | {"const":true} | | $.$defs.boundary.networkOptional | true | | {"const":true} | | $.$defs.signal | false | object | {"required":["signalId","externalId","provider","title","canonicalUrl","observedContext","capabilityObservations","provenance","review","confidence","retrievedAt","signalDigest","boundary"],"additionalProperties":false} | | $.$defs.signal.signalId | true | string | {"pattern":"^eas-[a-f0-9]{64}$"} | | $.$defs.signal.externalId | true | string | {"minLength":1,"maxLength":500} | | $.$defs.signal.provider | true | object | {"required":["providerId","adapterVersion","contractVersion"],"additionalProperties":false} | | $.$defs.signal.provider.providerId | true | string | {"pattern":"^[a-z][a-z0-9-]{2,63}$"} | | $.$defs.signal.provider.adapterVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.signal.provider.contractVersion | true | | {"const":"1.0.0"} | | $.$defs.signal.title | true | string | {"minLength":1,"maxLength":300} | | $.$defs.signal.canonicalUrl | true | string | {"format":"uri","pattern":"^https://"} | | $.$defs.signal.observedContext | true | object | {"required":["setting","agency"],"additionalProperties":false} | | $.$defs.signal.observedContext.eventAt | false | string | {"format":"date-time"} | | $.$defs.signal.observedContext.publishedAt | false | string | {"format":"date-time"} | | $.$defs.signal.observedContext.setting | true | | {"enum":["laboratory","field","mixed","unknown"]} | | $.$defs.signal.observedContext.agency | true | | {"enum":["human-directed","agent-initiated","mixed","unknown"]} | | $.$defs.signal.capabilityObservations | true | array | {"minItems":1,"maxItems":32} | | $.$defs.signal.capabilityObservations[] | false | / #/$defs/capabilityObservation | {} | | $.$defs.signal.provenance | true | object | {"required":["retrievalDigest","sources"],"additionalProperties":false} | | $.$defs.signal.provenance.retrievalDigest | true | / #/$defs/digest | {} | | $.$defs.signal.provenance.sources | true | array | {"minItems":1,"maxItems":20} | | $.$defs.signal.provenance.sources[] | false | object | {"required":["name","url","role"],"additionalProperties":false} | | $.$defs.signal.provenance.sources[].name | true | string | {"minLength":1,"maxLength":200} | | $.$defs.signal.provenance.sources[].url | true | string | {"format":"uri","pattern":"^https://"} | | $.$defs.signal.provenance.sources[].role | true | | {"enum":["primary","supporting"]} | | $.$defs.signal.provenance.sources[].publishedAt | false | string | {"format":"date-time"} | | $.$defs.signal.review | true | object | {"required":["reviewState","providerReviewState"],"additionalProperties":false} | | $.$defs.signal.review.reviewState | true | | {"enum":["unreviewed","in-review","reviewed","rejected","superseded"]} | | $.$defs.signal.review.providerReviewState | true | string | {"minLength":1,"maxLength":80} | | $.$defs.signal.confidence | true | object | {"required":["state","basis"],"additionalProperties":false} | | $.$defs.signal.confidence.state | true | | {"enum":["not-assessed","low","moderate","high"]} | | $.$defs.signal.confidence.basis | true | string | {"minLength":20,"maxLength":500} | | $.$defs.signal.retrievedAt | true | string | {"format":"date-time"} | | $.$defs.signal.signalDigest | true | / #/$defs/digest | {} | | $.$defs.signal.boundary | true | / #/$defs/boundary | {} | | $.$defs.capabilityObservation | false | object | {"required":["observationId","paloCapabilityId","providerCapabilityId","providerLabel","providerScore","providerScale","providerRubricVersion","mappingVersion","mappingReviewState","contextOnly","notUseCaseRiskScore"],"additionalProperties":false} | | $.$defs.capabilityObservation.observationId | true | string | {"pattern":"^eao-[a-f0-9]{64}$"} | | $.$defs.capabilityObservation.paloCapabilityId | true | string | {"pattern":"^palo-cap-[a-z0-9-]+$"} | | $.$defs.capabilityObservation.providerCapabilityId | true | string | {"minLength":1,"maxLength":120} | | $.$defs.capabilityObservation.providerLabel | true | string | {"minLength":1,"maxLength":160} | | $.$defs.capabilityObservation.providerScore | true | number | {} | | $.$defs.capabilityObservation.providerScale | true | object | {"required":["minimum","maximum"],"additionalProperties":false} | | $.$defs.capabilityObservation.providerScale.minimum | true | number | {} | | $.$defs.capabilityObservation.providerScale.maximum | true | number | {} | | $.$defs.capabilityObservation.providerRubricVersion | true | string | {"minLength":1,"maxLength":100} | | $.$defs.capabilityObservation.mappingVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.capabilityObservation.mappingReviewState | true | | {"enum":["draft","in-review","approved","rejected","superseded"]} | | $.$defs.capabilityObservation.contextOnly | true | | {"const":true} | | $.$defs.capabilityObservation.notUseCaseRiskScore | true | | {"const":true} | PALO External Agentic Evidence Provider Registry palo-external-evidence-provider-registry.schema.json Provider-neutral registry for optional, read-only external agentic evidence adapters. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","updatedAt","authorityBoundary","providers"],"additionalProperties":false} | Provider-neutral registry for optional, read-only external agentic evidence adapters. | $.format | true | | {"const":"palo-external-evidence-provider-registry"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.updatedAt | true | string | {"format":"date"} | | $.authorityBoundary | true | string | {"minLength":40} | | $.providers | true | array | {"minItems":1} | | $.providers[] | false | / #/$defs/provider | {} | | $.$defs.provider | false | object | {"required":["providerId","displayName","sourceId","adapter","mode","defaultState","networkOptional","dataPolicy","reviewBoundary"],"additionalProperties":false} | | $.$defs.provider.providerId | true | string | {"pattern":"^[a-z][a-z0-9-]{2,63}$"} | | $.$defs.provider.displayName | true | string | {"minLength":1,"maxLength":120} | | $.$defs.provider.sourceId | true | string | {"pattern":"^src-[a-z0-9-]+$"} | | $.$defs.provider.adapter | true | object | {"required":["adapterId","adapterVersion","contractVersion"],"additionalProperties":false} | | $.$defs.provider.adapter.adapterId | true | string | {"pattern":"^adapter-[a-z0-9-]+$"} | | $.$defs.provider.adapter.adapterVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.provider.adapter.contractVersion | true | | {"const":"1.0.0"} | | $.$defs.provider.mode | true | | {"enum":["local-import","http-pull"]} | | $.$defs.provider.defaultState | true | | {"enum":["enabled","disabled"]} | | $.$defs.provider.networkOptional | true | | {"const":true} | | $.$defs.provider.endpoint | false | string | {"format":"uri","pattern":"^https://"} | | $.$defs.provider.fetchPolicy | false | object | {"required":["timeoutMs","maxResponseBytes","maxRecords","redirects"],"additionalProperties":false} | | $.$defs.provider.fetchPolicy.timeoutMs | true | integer | {"minimum":500,"maximum":30000} | | $.$defs.provider.fetchPolicy.maxResponseBytes | true | integer | {"minimum":1024,"maximum":5242880} | | $.$defs.provider.fetchPolicy.maxRecords | true | integer | {"minimum":1,"maximum":1000} | | $.$defs.provider.fetchPolicy.redirects | true | | {"const":"reject"} | | $.$defs.provider.cachePolicy | false | object | {"required":["content","ttlSeconds","maxStaleSeconds","staleIfError","rawPayloadStored"],"additionalProperties":false} | | $.$defs.provider.cachePolicy.content | true | | {"const":"normalized-metadata-only"} | | $.$defs.provider.cachePolicy.ttlSeconds | true | integer | {"minimum":60,"maximum":2592000} | | $.$defs.provider.cachePolicy.maxStaleSeconds | true | integer | {"minimum":60,"maximum":7776000} | | $.$defs.provider.cachePolicy.staleIfError | true | boolean | {} | | $.$defs.provider.cachePolicy.rawPayloadStored | true | | {"const":false} | | $.$defs.provider.dataPolicy | true | object | {"required":["metadataOnly","prohibitedFields"],"additionalProperties":false} | | $.$defs.provider.dataPolicy.metadataOnly | true | | {"const":true} | | $.$defs.provider.dataPolicy.prohibitedFields | true | array | {"minItems":5,"uniqueItems":true} | | $.$defs.provider.dataPolicy.prohibitedFields[] | false | | {"enum":["fullText","sourceBody","details","summary","whyItMatters","justificationText"]} | | $.$defs.provider.reviewBoundary | true | string | {"minLength":30} | | $.$defs.provider.allOf[0] | false | | {} | | $.$defs.provider.allOf[0].if | false | | {} | | $.$defs.provider.allOf[0].if.mode | false | | {"const":"http-pull"} | | $.$defs.provider.allOf[0].then | false | | {"required":["endpoint","fetchPolicy","cachePolicy"]} | PALO External Evidence Reference palo-external-evidence-ref.schema.json Immutable, payload-minimized reference to context asserted by an external catalog, observability, identity or source system. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","evidenceRefId","tenantId","subject","source","evidenceType","normalizedClaims","observedAt","validUntil","payloadDigest","authority","connector","status"],"additionalProperties":false} | Immutable, payload-minimized reference to context asserted by an external catalog, observability, identity or source system. | $.format | true | | {"const":"palo-external-evidence-ref"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.evidenceRefId | true | string | {"pattern":"^evidence-ref-[a-f0-9-]{36}$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.subject | true | / #/$defs/subject | {} | | $.source | true | object | {"required":["system","objectId"],"additionalProperties":false} | | $.source.system | true | string | {"minLength":1,"maxLength":100} | | $.source.objectId | true | string | {"minLength":1,"maxLength":1000} | | $.source.objectVersion | false | string | {"minLength":1,"maxLength":500} | | $.source.uri | false | string | {"format":"uri","maxLength":2000} | | $.evidenceType | true | | {"enum":["metadata","lineage","quality","classification","ownership","access","data-contract","audit","incident","other"]} | | $.normalizedClaims | true | object | {"minProperties":1,"additionalProperties":false} | | $.normalizedClaims.qualityScore | false | number | {"minimum":0,"maximum":100} | | $.normalizedClaims.freshnessAt | false | string | {"format":"date-time"} | | $.normalizedClaims.classifications | false | array | {"uniqueItems":true,"maxItems":100} | | $.normalizedClaims.classifications[] | false | string | {"minLength":1,"maxLength":200} | | $.normalizedClaims.owner | false | string | {"minLength":1,"maxLength":500} | | $.normalizedClaims.approved | false | boolean | {} | | $.normalizedClaims.accessState | false | | {"enum":["granted","requested","denied","revoked","unknown"]} | | $.normalizedClaims.lineageComplete | false | boolean | {} | | $.normalizedClaims.permittedPurposes | false | array | {"uniqueItems":true,"maxItems":100} | | $.normalizedClaims.permittedPurposes[] | false | string | {"minLength":1,"maxLength":300} | | $.normalizedClaims.lifecycleState | false | string | {"minLength":1,"maxLength":100} | | $.normalizedClaims.incidentOpen | false | boolean | {} | | $.normalizedClaims.contractVersion | false | string | {"minLength":1,"maxLength":100} | | $.normalizedClaims.additionalClaimsDigest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.observedAt | true | string | {"format":"date-time"} | | $.validUntil | true | string | {"format":"date-time"} | | $.payloadDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.authority | true | object | {"required":["type","assertedBy","verified"],"additionalProperties":false} | | $.authority.type | true | | {"enum":["source-api","catalog-api","observability-api","identity-api","signed-import","manual-attestation"]} | | $.authority.assertedBy | true | string | {"minLength":1,"maxLength":500} | | $.authority.verified | true | boolean | {} | | $.connector | true | object | {"required":["connectorId","version","mode","importedAt"],"additionalProperties":false} | | $.connector.connectorId | true | string | {"pattern":"^connector-[a-zA-Z0-9][a-zA-Z0-9._-]{2,100}$"} | | $.connector.version | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+(?:-[0-9A-Za-z.-]+)?$"} | | $.connector.mode | true | | {"const":"read-only"} | | $.connector.importedAt | true | string | {"format":"date-time"} | | $.status | true | | {"enum":["active","revoked"]} | | $.$defs.subject | false | object | {"required":["type","id"],"additionalProperties":false} | | $.$defs.subject.type | true | | {"enum":["dataset","data-product","model","ai-system","agent","tool","access-entitlement","other"]} | | $.$defs.subject.id | true | string | {"minLength":1,"maxLength":1000} | PALO Append-Only Gate Decision Record palo-gate-decision-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","decisionId","gateInstanceId","caseId","sequence","outcome","decidedAt","decisionActor","authorityBasis","rationale","conditions","inputSnapshotHash","definitionRefs","evidenceClaimIds","recordDigest","appendOnly"],"additionalProperties":false} | | $.format | true | | {"const":"palo-gate-decision-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.decisionId | true | string | {"pattern":"^gate-decision-[a-z0-9][a-z0-9-]{5,80}$"} | | $.gateInstanceId | true | string | {"pattern":"^gate-instance-[a-z0-9][a-z0-9-]{5,80}$"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.sequence | true | integer | {"minimum":1} | | $.supersedesDecisionId | false | string | {"pattern":"^gate-decision-[a-z0-9][a-z0-9-]{5,80}$"} | | $.previousDecisionDigest | false | / #/$defs/digest | {} | | $.outcome | true | | {"enum":["proceed","proceed-with-conditions","hold","redesign","stop","unresolved"]} | | $.decidedAt | true | string | {"format":"date-time"} | | $.expiresAt | false | string | {"format":"date-time"} | | $.decisionActor | true | object | {"required":["actorId","role","displayName"],"additionalProperties":false} | | $.decisionActor.actorId | true | string | {"minLength":1} | | $.decisionActor.role | true | string | {"minLength":1} | | $.decisionActor.displayName | true | string | {"minLength":1} | | $.authorityBasis | true | string | {"minLength":1} | | $.rationale | true | string | {"minLength":1} | | $.conditions | true | array | {} | | $.conditions[] | false | string | {} | | $.inputSnapshotHash | true | / #/$defs/digest | {} | | $.definitionRefs | true | array | {"minItems":1,"uniqueItems":true} | | $.definitionRefs[] | false | string | {"format":"uri"} | | $.evidenceClaimIds | true | array | {"uniqueItems":true} | | $.evidenceClaimIds[] | false | string | {} | | $.recordDigest | true | / #/$defs/digest | {} | | $.appendOnly | true | | {"const":true} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["sequence"]} | | $.allOf[0].if.sequence | true | integer | {"minimum":2} | | $.allOf[0].then | false | | {"required":["supersedesDecisionId","previousDecisionDigest"]} | | $.allOf[0].then.supersedesDecisionId | true | string | {"pattern":"^gate-decision-[a-z0-9][a-z0-9-]{5,80}$"} | | $.allOf[0].then.previousDecisionDigest | true | / #/$defs/digest | {} | | $.allOf[1] | false | | {} | | $.allOf[1].if | false | | {"required":["outcome"]} | | $.allOf[1].if.outcome | true | | {"const":"proceed-with-conditions"} | | $.allOf[1].then | false | | {} | | $.allOf[1].then.conditions | false | array | {"minItems":1} | PALO Gate Instance palo-gate-instance.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","gateInstanceId","caseId","lifecycleDefinitionRef","gateDefinitionRef","phaseDefinitionRef","openedAt","status","currentDecisionSequence"],"additionalProperties":false} | | $.format | true | | {"const":"palo-gate-instance"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.gateInstanceId | true | string | {"pattern":"^gate-instance-[a-z0-9][a-z0-9-]{5,80}$"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.lifecycleDefinitionRef | true | string | {"format":"uri"} | | $.gateDefinitionRef | true | string | {"format":"uri"} | | $.phaseDefinitionRef | true | string | {"format":"uri"} | | $.openedAt | true | string | {"format":"date-time"} | | $.closedAt | false | string | {"format":"date-time"} | | $.status | true | | {"enum":["not-started","open","ready-for-review","decided","reopened","closed"]} | | $.currentDecisionSequence | true | integer | {"minimum":0} | | $.reopenedBy | false | array | {"uniqueItems":true} | | $.reopenedBy[] | false | string | {} | PALO Governance Assurance Record palo-governance-assurance-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","caseId","domainId","systemVersion","applicability","applicabilityRationale","controlIds","owner","status","evidenceItems","measurements","findings","authorityBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-governance-assurance-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {"pattern":"^assurance-[a-zA-Z0-9._-]+$"} | | $.caseId | true | string | {"minLength":1} | | $.domainId | true | | {"enum":["domain-fairness-subgroups","domain-system-card-explanations","domain-notice-appeal-remedy","domain-article50-transparency","domain-data-lifecycle","domain-gpai-systemic-risk","domain-serious-incident-decommissioning","domain-accessibility","domain-environment","domain-ai-literacy","domain-iso42001-aims","domain-palo-ai-production"]} | | $.systemVersion | true | string | {"minLength":1} | | $.applicability | true | | {"enum":["applicable","not-applicable","undetermined"]} | | $.applicabilityRationale | true | string | {"minLength":20} | | $.controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.controlIds[] | false | string | {"pattern":"^ctrl-[a-z0-9-]+$"} | | $.owner | true | / #/$defs/actor | {} | | $.status | true | | {"enum":["draft","in-review","accepted","rejected","expired"]} | | $.evidenceItems | true | array | {} | | $.evidenceItems[] | false | / #/$defs/evidenceItem | {} | | $.measurements | true | array | {} | | $.measurements[] | false | / #/$defs/measurement | {} | | $.findings | true | array | {} | | $.findings[] | false | / #/$defs/finding | {} | | $.gateDecisionRef | false | string | {"minLength":1} | | $.reviewedAt | false | string | {"format":"date-time"} | | $.reviewedBy | false | / #/$defs/actor | {} | | $.validUntil | false | string | {"format":"date-time"} | | $.authorityBoundary | true | string | {"minLength":30} | | $.$defs.actor | false | object | {"required":["actorId","role"],"additionalProperties":false} | | $.$defs.actor.actorId | true | string | {"minLength":1} | | $.$defs.actor.role | true | string | {"minLength":1} | | $.$defs.actor.independenceStatement | false | string | {"minLength":10} | | $.$defs.evidenceItem | false | object | {"required":["evidenceId","kind","artifactRef","sha256","capturedAt","evaluation"],"additionalProperties":false} | | $.$defs.evidenceItem.evidenceId | true | string | {"minLength":1} | | $.$defs.evidenceItem.kind | true | string | {"pattern":"^[a-z0-9-]+$"} | | $.$defs.evidenceItem.artifactRef | true | string | {"minLength":1} | | $.$defs.evidenceItem.sha256 | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.$defs.evidenceItem.capturedAt | true | string | {"format":"date-time"} | | $.$defs.evidenceItem.evaluation | true | | {"enum":["accepted","conditional","rejected","not-evaluated"]} | | $.$defs.measurement | false | object | {"required":["indicatorId","observedValue","thresholdDecision","measuredAt"],"additionalProperties":false} | | $.$defs.measurement.indicatorId | true | string | {"pattern":"^(kpi|kri)-[a-z0-9-]+$"} | | $.$defs.measurement.observedValue | true | | {} | | $.$defs.measurement.observedValue.oneOf[0] | false | number | {} | | $.$defs.measurement.observedValue.oneOf[1] | false | string | {"minLength":1} | | $.$defs.measurement.thresholdDecision | true | | {"enum":["pass","conditional","fail","not-established"]} | | $.$defs.measurement.measuredAt | true | string | {"format":"date-time"} | | $.$defs.finding | false | object | {"required":["findingId","severity","description","status","actionOwner","dueAt"],"additionalProperties":false} | | $.$defs.finding.findingId | true | string | {"minLength":1} | | $.$defs.finding.severity | true | | {"enum":["low","moderate","high","critical"]} | | $.$defs.finding.description | true | string | {"minLength":10} | | $.$defs.finding.status | true | | {"enum":["open","accepted-risk","remediated","verified-closed"]} | | $.$defs.finding.actionOwner | true | string | {"minLength":1} | | $.$defs.finding.dueAt | true | string | {"format":"date-time"} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["applicability"]} | | $.allOf[0].if.applicability | true | | {"const":"applicable"} | | $.allOf[0].then | false | | {} | | $.allOf[0].then.evidenceItems | false | array | {"minItems":1} | | $.allOf[0].then.measurements | false | array | {"minItems":1} | | $.allOf[1] | false | | {} | | $.allOf[1].if | false | | {"required":["status"]} | | $.allOf[1].if.status | true | | {"const":"accepted"} | | $.allOf[1].then | false | | {"required":["gateDecisionRef","reviewedAt","reviewedBy","validUntil"]} | | $.allOf[1].then.gateDecisionRef | true | string | {"minLength":1} | | $.allOf[1].then.reviewedAt | true | string | {"format":"date-time"} | | $.allOf[1].then.reviewedBy | true | / #/$defs/actor | {} | | $.allOf[1].then.validUntil | true | string | {"format":"date-time"} | PALO Governance Control Packs palo-governance-control-packs.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","releaseVersion","status","updatedAt","authorityBoundary","completionDefinitions","domains"],"additionalProperties":false} | | $.format | true | | {"const":"palo-governance-control-packs"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.releaseVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.status | true | | {"const":"approved-for-release"} | | $.updatedAt | true | string | {"format":"date"} | | $.authorityBoundary | true | string | {"minLength":40} | | $.completionDefinitions | true | object | {"required":["governanceComplete","operationalComplete","productionComplete","certificationComplete"],"additionalProperties":false} | | $.completionDefinitions.governanceComplete | true | string | {"minLength":40} | | $.completionDefinitions.operationalComplete | true | string | {"minLength":40} | | $.completionDefinitions.productionComplete | true | string | {"minLength":40} | | $.completionDefinitions.certificationComplete | true | string | {"minLength":40} | | $.domains | true | array | {"minItems":12,"uniqueItems":true} | | $.domains[] | false | object | {"required":["domainId","title","objective","completionLevel","applicabilityQuestions","controlIds","indicatorIds","gateIds","evidenceContractRefs","minimumEvidenceKinds","completionCriteria","stopConditions","residualBoundary"],"additionalProperties":false} | | $.domains[].domainId | true | string | {"pattern":"^domain-[a-z0-9-]+$"} | | $.domains[].title | true | string | {"minLength":1} | | $.domains[].objective | true | string | {"minLength":20} | | $.domains[].completionLevel | true | | {"enum":["governance-control-plane","reference-runtime-only"]} | | $.domains[].applicabilityQuestions | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].applicabilityQuestions[] | false | string | {"minLength":10} | | $.domains[].controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].controlIds[] | false | string | {"pattern":"^ctrl-[a-z0-9-]+$"} | | $.domains[].indicatorIds | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].indicatorIds[] | false | string | {"pattern":"^(kpi|kri)-[a-z0-9-]+$"} | | $.domains[].gateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].gateIds[] | false | | {"enum":["frame","classify","assess","control","measure","prove"]} | | $.domains[].evidenceContractRefs | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].evidenceContractRefs[] | false | string | {"pattern":"^schemas/[a-z0-9-]+\\.schema\\.json$"} | | $.domains[].minimumEvidenceKinds | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].minimumEvidenceKinds[] | false | string | {"pattern":"^[a-z0-9-]+$"} | | $.domains[].completionCriteria | true | array | {"minItems":2,"uniqueItems":true} | | $.domains[].completionCriteria[] | false | string | {"minLength":15} | | $.domains[].stopConditions | true | array | {"minItems":1,"uniqueItems":true} | | $.domains[].stopConditions[] | false | string | {"minLength":15} | | $.domains[].residualBoundary | true | string | {"minLength":30} | PALO GPAI and Systemic-Risk Record palo-gpai-systemic-risk-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","recordId","caseId","model","roleAssessment","providerObligations","deployerControls","systemicRisk","incidents","review"],"additionalProperties":false} | | $.format | true | | {"const":"palo-gpai-systemic-risk-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.recordId | true | string | {} | | $.caseId | true | string | {} | | $.model | true | object | {"required":["modelId","provider","version","releaseDate","componentInventoryRef"],"additionalProperties":false} | | $.model.modelId | true | string | {} | | $.model.provider | true | string | {} | | $.model.version | true | string | {} | | $.model.releaseDate | true | string | {"format":"date"} | | $.model.componentInventoryRef | true | string | {} | | $.roleAssessment | true | object | {"required":["roles","materialModification","systemicRiskStatus","legalReviewRef"],"additionalProperties":false} | | $.roleAssessment.roles | true | array | {"minItems":1,"uniqueItems":true} | | $.roleAssessment.roles[] | false | | {"enum":["provider","downstream-provider","deployer","importer","distributor"]} | | $.roleAssessment.materialModification | true | boolean | {} | | $.roleAssessment.systemicRiskStatus | true | | {"enum":["designated","presumed","not-designated","undetermined"]} | | $.roleAssessment.legalReviewRef | true | string | {} | | $.providerObligations | true | array | {} | | $.providerObligations[] | false | / #/$defs/obligation | {} | | $.deployerControls | true | array | {} | | $.deployerControls[] | false | / #/$defs/obligation | {} | | $.systemicRisk | true | object | {"required":["scenarios","evaluations","mitigations","residualFindings","modelReportingRoute"],"additionalProperties":false} | | $.systemicRisk.scenarios | true | / #/$defs/strings | {} | | $.systemicRisk.evaluations | true | / #/$defs/strings | {} | | $.systemicRisk.mitigations | true | / #/$defs/strings | {} | | $.systemicRisk.residualFindings | true | array | {} | | $.systemicRisk.residualFindings[] | false | string | {} | | $.systemicRisk.modelReportingRoute | true | string | {} | | $.incidents | true | object | {"required":["providerRoute","authorityRoute","sharingProtocol"],"additionalProperties":false} | | $.incidents.providerRoute | true | string | {} | | $.incidents.authorityRoute | true | string | {} | | $.incidents.sharingProtocol | true | string | {} | | $.review | true | object | {"required":["status","reviewedAt","reviewedBy","validUntil"],"additionalProperties":false} | | $.review.status | true | | {"enum":["accepted","conditional","rejected"]} | | $.review.reviewedAt | true | string | {"format":"date-time"} | | $.review.reviewedBy | true | string | {} | | $.review.validUntil | true | string | {"format":"date-time"} | | $.$defs.strings | false | array | {"minItems":1,"uniqueItems":true} | | $.$defs.strings[] | false | string | {} | | $.$defs.obligation | false | object | {"required":["obligationId","applicable","evidenceRef","status"],"additionalProperties":false} | | $.$defs.obligation.obligationId | true | string | {} | | $.$defs.obligation.applicable | true | boolean | {} | | $.$defs.obligation.evidenceRef | true | string | {} | | $.$defs.obligation.status | true | | {"enum":["accepted","conditional","missing","not-applicable"]} | PALO KPI KRI Registry palo-kpi-kri-registry.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","status","updatedAt","disclaimer","indicators"],"additionalProperties":false} | | $.format | true | | {"const":"palo-kpi-kri-registry"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.status | true | | {"const":"educational-non-production"} | | $.updatedAt | true | string | {"format":"date"} | | $.disclaimer | true | string | {"minLength":20} | | $.indicators | true | array | {"minItems":1} | | $.indicators[] | false | object | {"required":["indicatorId","type","name","purpose","formula","cadence","direction","thresholds","controlIds","gateIds","sourceIds","caveat"],"additionalProperties":false} | | $.indicators[].indicatorId | true | string | {"pattern":"^(kpi|kri)-[a-z0-9-]+$"} | | $.indicators[].type | true | | {"enum":["KPI","KRI"]} | | $.indicators[].name | true | string | {"minLength":1} | | $.indicators[].purpose | true | string | {"minLength":1} | | $.indicators[].formula | true | string | {"minLength":1} | | $.indicators[].cadence | true | string | {"minLength":1} | | $.indicators[].direction | true | | {"enum":["higher-is-better","lower-is-better","within-range"]} | | $.indicators[].thresholds | true | object | {"required":["amber","red"],"additionalProperties":false} | | $.indicators[].thresholds.amber | true | string | {} | | $.indicators[].thresholds.red | true | string | {} | | $.indicators[].controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.indicators[].controlIds[] | false | string | {} | | $.indicators[].gateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.indicators[].gateIds[] | false | string | {} | | $.indicators[].sourceIds | true | array | {"minItems":1,"uniqueItems":true} | | $.indicators[].sourceIds[] | false | string | {} | | $.indicators[].caveat | true | string | {"minLength":10} | PALO Lifecycle Definition palo-lifecycle-definition.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","lifecycleId","definitionVersion","label","status","releasedAt","frameworkRef","phases","gateDefinitions","provenance"],"additionalProperties":false} | | $.format | true | | {"const":"palo-lifecycle-definition"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.lifecycleId | true | string | {"format":"uri"} | | $.definitionVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.label | true | string | {"minLength":1} | | $.status | true | | {"enum":["draft","in-review","approved-for-release","deprecated","superseded"]} | | $.releasedAt | true | string | {"format":"date"} | | $.frameworkRef | true | string | {"format":"uri"} | | $.phases | true | array | {"minItems":1} | | $.phases[] | false | object | {"required":["phaseDefinitionId","semanticId","definitionVersion","ordinal","label","purpose","gateDefinitionRef"],"additionalProperties":false} | | $.phases[].phaseDefinitionId | true | string | {"pattern":"^phase-[a-z0-9-]+$"} | | $.phases[].semanticId | true | string | {"format":"uri"} | | $.phases[].definitionVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.phases[].ordinal | true | integer | {"minimum":1} | | $.phases[].label | true | string | {"minLength":1} | | $.phases[].purpose | true | string | {"minLength":1} | | $.phases[].gateDefinitionRef | true | string | {"format":"uri"} | | $.gateDefinitions | true | array | {"minItems":1} | | $.gateDefinitions[] | false | object | {"required":["gateDefinitionId","gateId","definitionVersion","label","purpose","entryCriteria","decisionOptions","requiredControlIds","conditionalControlIds","indicatorIds","sourceIds","templateIds"],"additionalProperties":false} | | $.gateDefinitions[].gateDefinitionId | true | string | {"format":"uri"} | | $.gateDefinitions[].gateId | true | string | {"pattern":"^[a-z0-9-]+$"} | | $.gateDefinitions[].definitionVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.gateDefinitions[].label | true | string | {"minLength":1} | | $.gateDefinitions[].purpose | true | string | {"minLength":1} | | $.gateDefinitions[].entryCriteria | true | array | {"minItems":1} | | $.gateDefinitions[].entryCriteria[] | false | string | {} | | $.gateDefinitions[].decisionOptions | true | array | {"minItems":2,"uniqueItems":true} | | $.gateDefinitions[].decisionOptions[] | false | | {"enum":["proceed","proceed-with-conditions","hold","redesign","stop"]} | | $.gateDefinitions[].requiredControlIds | true | array | {"uniqueItems":true} | | $.gateDefinitions[].requiredControlIds[] | false | string | {} | | $.gateDefinitions[].conditionalControlIds | true | array | {"uniqueItems":true} | | $.gateDefinitions[].conditionalControlIds[] | false | string | {} | | $.gateDefinitions[].indicatorIds | true | array | {"uniqueItems":true} | | $.gateDefinitions[].indicatorIds[] | false | string | {} | | $.gateDefinitions[].sourceIds | true | array | {"minItems":1,"uniqueItems":true} | | $.gateDefinitions[].sourceIds[] | false | string | {} | | $.gateDefinitions[].templateIds | true | array | {"uniqueItems":true} | | $.gateDefinitions[].templateIds[] | false | string | {} | | $.provenance | true | object | {"required":["generatedFrom","authorityBoundary"],"additionalProperties":false} | | $.provenance.generatedFrom | true | array | {"minItems":1,"uniqueItems":true} | | $.provenance.generatedFrom[] | false | string | {} | | $.provenance.authorityBoundary | true | string | {"minLength":1} | PALO Local Validation Receipt palo-local-validation-receipt.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","receiptId","caseId","generatedAt","result","artifactDigest","checks","validator","privacyBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-local-validation-receipt"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.receiptId | true | string | {"pattern":"^receipt-[a-f0-9]{16}$"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.generatedAt | true | string | {"format":"date-time"} | | $.result | true | | {"enum":["valid","invalid"]} | | $.artifactDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.checks | true | array | {"minItems":1} | | $.checks[] | false | object | {"required":["checkId","status","message"],"additionalProperties":false} | | $.checks[].checkId | true | string | {"minLength":1} | | $.checks[].status | true | | {"enum":["passed","failed"]} | | $.checks[].message | true | string | {"minLength":1} | | $.validator | true | object | {"required":["name","version","execution"],"additionalProperties":false} | | $.validator.name | true | | {"const":"PALO Evidence Pack local validator"} | | $.validator.version | true | string | {"minLength":1} | | $.validator.execution | true | | {"enum":["browser-local","node-local"]} | | $.privacyBoundary | true | string | {"minLength":1} | | $.shareMode | false | | {"const":"voluntary-export"} | PALO OWASP GenAI LLM Top 10 2026 Crosswalk palo-owasp-genai-2026-crosswalk.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","analysisVersion","status","reviewedAt","source","licensing","authorityBoundary","ratingScale","routes","summary","risks","governance"],"additionalProperties":false} | | $.format | true | | {"const":"palo-owasp-genai-2026-crosswalk"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.analysisVersion | true | string | {"pattern":"^[0-9]+\\.[0-9]+\\.[0-9]+$"} | | $.status | true | | {"const":"source-backed-context"} | | $.reviewedAt | true | string | {"format":"date"} | | $.technicalReview | false | object | {"required":["reviewer","publicRole","scope","creditAuthorizedAt","independenceBoundary"],"additionalProperties":false} | | $.technicalReview.reviewer | true | string | {"minLength":3} | | $.technicalReview.publicRole | true | string | {"minLength":10} | | $.technicalReview.scope | true | array | {"minItems":3,"uniqueItems":true} | | $.technicalReview.scope[] | false | string | {"minLength":10} | | $.technicalReview.creditAuthorizedAt | true | string | {"format":"date"} | | $.technicalReview.independenceBoundary | true | string | {"minLength":40} | | $.source | true | object | {"required":["sourceId","version","artifact","sha256","officialProjectUrl","editorialStatus"],"additionalProperties":false} | | $.source.sourceId | true | string | {"pattern":"^src-[a-z0-9-]+$"} | | $.source.version | true | | {"const":"2026-v1.0"} | | $.source.artifact | true | | {"const":"assets/OWASP-GenAI-LLM-Top-10-2026-v1.0.pdf"} | | $.source.sha256 | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.source.officialProjectUrl | true | string | {"format":"uri"} | | $.source.editorialStatus | true | | {"enum":["verified","provisional","superseded"]} | | $.licensing | true | object | {"required":["sourceLicense","sourceLicenseUrl","crosswalkLicense","attribution","endorsementBoundary"],"additionalProperties":false} | | $.licensing.sourceLicense | true | | {"const":"CC BY-SA 4.0"} | | $.licensing.sourceLicenseUrl | true | string | {"format":"uri"} | | $.licensing.crosswalkLicense | true | | {"const":"CC BY-SA 4.0"} | | $.licensing.attribution | true | string | {"minLength":20} | | $.licensing.endorsementBoundary | true | string | {"minLength":20} | | $.authorityBoundary | true | string | {"minLength":40} | | $.ratingScale | true | object | {"required":["direct","supporting","gap"],"additionalProperties":false} | | $.ratingScale.direct | true | string | {"minLength":20} | | $.ratingScale.supporting | true | string | {"minLength":20} | | $.ratingScale.gap | true | string | {"minLength":20} | | $.routes | true | array | {"minItems":3,"maxItems":3} | | $.routes[] | false | object | {"required":["routeId","label","role","maturity","counts"],"additionalProperties":false} | | $.routes[].routeId | true | | {"enum":["palo","palo-am","palo-ai"]} | | $.routes[].label | true | string | {"minLength":1} | | $.routes[].role | true | string | {"minLength":10} | | $.routes[].maturity | true | string | {"minLength":5} | | $.routes[].counts | true | object | {"required":["direct","supporting","gap"],"additionalProperties":false} | | $.routes[].counts.direct | true | integer | {"minimum":0,"maximum":10} | | $.routes[].counts.supporting | true | integer | {"minimum":0,"maximum":10} | | $.routes[].counts.gap | true | integer | {"minimum":0,"maximum":10} | | $.summary | true | object | {"required":["overallFit","unionDirect","unionSupporting","targetedExtensions"],"additionalProperties":false} | | $.summary.overallFit | true | string | {"minLength":20} | | $.summary.unionDirect | true | integer | {"const":8} | | $.summary.unionSupporting | true | integer | {"const":2} | | $.summary.targetedExtensions | true | array | {"minItems":2,"maxItems":2,"uniqueItems":true} | | $.summary.targetedExtensions[] | false | | {"enum":["LLM09:2026","LLM10:2026"]} | | $.risks | true | array | {"minItems":10,"maxItems":10} | | $.risks[] | false | object | {"required":["riskId","title","routeFit","verdict","paloResponse","controlIds","externalSafeguards","minimumEvidence","accountableOwner","reopenTriggers"],"additionalProperties":false} | | $.risks[].riskId | true | string | {"pattern":"^LLM(0[1-9]|10):2026$"} | | $.risks[].title | true | string | {"minLength":1} | | $.risks[].routeFit | true | object | {"required":["palo","paloAm","paloAi"],"additionalProperties":false} | | $.risks[].routeFit.palo | true | | {"enum":["direct","supporting","gap"]} | | $.risks[].routeFit.paloAm | true | | {"enum":["direct","supporting","gap"]} | | $.risks[].routeFit.paloAi | true | | {"enum":["direct","supporting","gap"]} | | $.risks[].verdict | true | string | {"minLength":20} | | $.risks[].paloResponse | true | string | {"minLength":30} | | $.risks[].controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.risks[].controlIds[] | false | string | {"pattern":"^ctrl-[a-z0-9-]+$"} | | $.risks[].externalSafeguards | true | array | {"minItems":1,"uniqueItems":true} | | $.risks[].externalSafeguards[] | false | string | {"minLength":5} | | $.risks[].minimumEvidence | true | array | {"minItems":1,"uniqueItems":true} | | $.risks[].minimumEvidence[] | false | string | {"minLength":5} | | $.risks[].accountableOwner | true | string | {"minLength":5} | | $.risks[].reopenTriggers | true | array | {"minItems":1,"uniqueItems":true} | | $.risks[].reopenTriggers[] | false | string | {"minLength":5} | | $.governance | true | object | {"required":["sourceClass","accountableOwner","reviewIntervalDays","nextReviewAt","applicabilityRule","requiredRiskRecord","reopenTriggers"],"additionalProperties":false} | | $.governance.sourceClass | true | | {"const":"informative-security-source"} | | $.governance.accountableOwner | true | string | {"minLength":5} | | $.governance.reviewIntervalDays | true | integer | {"const":90} | | $.governance.nextReviewAt | true | string | {"format":"date"} | | $.governance.applicabilityRule | true | string | {"minLength":40} | | $.governance.requiredRiskRecord | true | array | {"minItems":7,"uniqueItems":true} | | $.governance.requiredRiskRecord[] | false | string | {"minLength":3} | | $.governance.reopenTriggers | true | array | {"minItems":4,"uniqueItems":true} | | $.governance.reopenTriggers[] | false | string | {"minLength":5} | PALO P2 Adoption Index palo-p2-index.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","status","artifacts","workedCases","templates"],"additionalProperties":false} | | $.format | true | | {"const":"palo-p2-adoption-index"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.status | true | | {"const":"educational-non-production"} | | $.artifacts | true | array | {"minItems":1} | | $.artifacts[] | false | / #/$defs/artifact | {} | | $.workedCases | true | array | {"minItems":6} | | $.workedCases[] | false | / #/$defs/case | {} | | $.templates | true | array | {"minItems":5} | | $.templates[] | false | / #/$defs/template | {} | | $.$defs.artifact | false | object | {"required":["artifactId","kind","path","schemaPath"],"additionalProperties":false} | | $.$defs.artifact.artifactId | true | string | {} | | $.$defs.artifact.kind | true | string | {} | | $.$defs.artifact.path | true | string | {} | | $.$defs.artifact.schemaPath | true | string | {} | | $.$defs.case | false | object | {"required":["caseId","domain","path","controlIds","indicatorIds","gateIds","sourceIds","templateIds"],"additionalProperties":false} | | $.$defs.case.caseId | true | string | {} | | $.$defs.case.domain | true | string | {} | | $.$defs.case.path | true | string | {} | | $.$defs.case.controlIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.case.controlIds[] | false | string | {} | | $.$defs.case.indicatorIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.case.indicatorIds[] | false | string | {} | | $.$defs.case.gateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.case.gateIds[] | false | string | {} | | $.$defs.case.sourceIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.case.sourceIds[] | false | string | {} | | $.$defs.case.templateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.case.templateIds[] | false | string | {} | | $.$defs.template | false | object | {"required":["templateId","title","path","gateIds"],"additionalProperties":false} | | $.$defs.template.templateId | true | string | {} | | $.$defs.template.title | true | string | {} | | $.$defs.template.path | true | string | {} | | $.$defs.template.gateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.$defs.template.gateIds[] | false | string | {} | PALO Educational Policy Input palo-policy-input.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","exampleStatus","caseId","decisionContext"],"additionalProperties":false} | | $.format | true | | {"const":"palo-policy-input"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.exampleStatus | true | | {"const":"educational-non-production"} | | $.caseId | true | string | {"pattern":"^case-[a-z0-9][a-z0-9-]{5,63}$"} | | $.decisionContext | true | object | {"required":["gateId","humanApprovalRequired","humanApprovalRecorded","openCriticalFindings","requiredEvidenceComplete"],"additionalProperties":false} | | $.decisionContext.gateId | true | | {"enum":["frame","classify","assess","control","measure","prove"]} | | $.decisionContext.humanApprovalRequired | true | boolean | {} | | $.decisionContext.humanApprovalRecorded | true | boolean | {} | | $.decisionContext.openCriticalFindings | true | integer | {"minimum":0} | | $.decisionContext.requiredEvidenceComplete | true | boolean | {} | PALO PolicyWatcher Browser-local Review Ledger palo-policywatcher-review-ledger.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","exportedAt","sourceRegistryDigest","reviews","localOnly","authorityBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-policywatcher-review-ledger"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.exportedAt | true | string | {"format":"date-time"} | | $.sourceRegistryDigest | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.reviews | true | array | {"maxItems":500} | | $.reviews[] | false | object | {"required":["signalId","signalDigest","transportStatus","reviewState","updatedAt"],"additionalProperties":false} | | $.reviews[].signalId | true | string | {"pattern":"^signal-policywatcher-[a-f0-9-]{36}$"} | | $.reviews[].signalDigest | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.reviews[].transportStatus | true | | {"enum":["active","revoked"]} | | $.reviews[].reviewState | true | | {"enum":["pending-human-review","in-review","routed-to-case-file","reviewed-no-action","rejected"]} | | $.reviews[].updatedAt | true | string | {"format":"date-time"} | | $.localOnly | true | | {"const":true} | | $.authorityBoundary | true | string | {"minLength":80,"maxLength":1000} | PALO PolicyWatcher Operational Signal Registry palo-policywatcher-signal-registry.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","updatedAt","source","transport","statistics","entries","alerts","authorityBoundary","collectionDigest"],"additionalProperties":false} | | $.format | true | | {"const":"palo-policywatcher-signal-registry"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.updatedAt | true | string | {"format":"date-time"} | | $.source | true | object | {"required":["providerId","origin","endpoint","mode","networkOptional"],"additionalProperties":false} | | $.source.providerId | true | | {"const":"policywatcher"} | | $.source.origin | true | | {"const":"https://policywatcher.online"} | | $.source.endpoint | true | | {"const":"/api/v1/integrations/palo/signals"} | | $.source.mode | true | | {"const":"optional-pull"} | | $.source.networkOptional | true | | {"const":true} | | $.transport | true | object | {"required":["state","lastAttemptAt","lastSuccessfulSyncAt","completeTraversal","pageCount","stale","errorCode"],"additionalProperties":false} | | $.transport.state | true | | {"enum":["not-synchronized","healthy","degraded","unavailable"]} | | $.transport.lastAttemptAt | true | | {} | | $.transport.lastAttemptAt.oneOf[0] | false | string | {"format":"date-time"} | | $.transport.lastAttemptAt.oneOf[1] | false | null | {} | | $.transport.lastSuccessfulSyncAt | true | | {} | | $.transport.lastSuccessfulSyncAt.oneOf[0] | false | string | {"format":"date-time"} | | $.transport.lastSuccessfulSyncAt.oneOf[1] | false | null | {} | | $.transport.completeTraversal | true | boolean | {} | | $.transport.pageCount | true | integer | {"minimum":0,"maximum":20} | | $.transport.stale | true | boolean | {} | | $.transport.errorCode | true | | {} | | $.transport.errorCode.oneOf[0] | false | | {"enum":["network-error","http-error","schema-error","response-too-large","pagination-error","capacity-exceeded"]} | | $.transport.errorCode.oneOf[1] | false | null | {} | | $.statistics | true | object | {"required":["active","revoked","received","accepted","rejected","changed"],"additionalProperties":false} | | $.statistics.active | true | integer | {"minimum":0,"maximum":500} | | $.statistics.revoked | true | integer | {"minimum":0,"maximum":500} | | $.statistics.received | true | integer | {"minimum":0,"maximum":500} | | $.statistics.accepted | true | integer | {"minimum":0,"maximum":500} | | $.statistics.rejected | true | integer | {"minimum":0,"maximum":500} | | $.statistics.changed | true | integer | {"minimum":0,"maximum":500} | | $.entries | true | array | {"maxItems":500} | | $.entries[] | false | / #/$defs/entry | {} | | $.alerts | true | array | {"maxItems":100} | | $.alerts[] | false | / #/$defs/alert | {} | | $.authorityBoundary | true | string | {"minLength":80,"maxLength":1000} | | $.collectionDigest | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.$defs.entry | false | object | {"required":["signalId","changeId","signalDigest","transportStatus","reviewState","firstAcceptedAt","lastValidatedAt","revokedAt","signal"],"additionalProperties":false} | | $.$defs.entry.signalId | true | string | {"pattern":"^signal-policywatcher-[a-f0-9-]{36}$"} | | $.$defs.entry.changeId | true | string | {"format":"uuid"} | | $.$defs.entry.signalDigest | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.$defs.entry.transportStatus | true | | {"enum":["active","revoked"]} | | $.$defs.entry.reviewState | true | | {"enum":["pending-human-review","in-review","routed-to-case-file","reviewed-no-action","rejected"]} | | $.$defs.entry.firstAcceptedAt | true | string | {"format":"date-time"} | | $.$defs.entry.lastValidatedAt | true | string | {"format":"date-time"} | | $.$defs.entry.revokedAt | true | | {} | | $.$defs.entry.revokedAt.oneOf[0] | false | string | {"format":"date-time"} | | $.$defs.entry.revokedAt.oneOf[1] | false | null | {} | | $.$defs.entry.signal | true | | {} | | $.$defs.entry.signal.oneOf[0] | false | / https://paloframework.org/schemas/policywatcher-signal.schema.json | {} | | $.$defs.entry.signal.oneOf[1] | false | null | {} | | $.$defs.entry.allOf[0] | false | | {} | | $.$defs.entry.allOf[0].if | false | | {} | | $.$defs.entry.allOf[0].if.transportStatus | false | | {"const":"active"} | | $.$defs.entry.allOf[0].then | false | | {} | | $.$defs.entry.allOf[0].then.signal | false | / https://paloframework.org/schemas/policywatcher-signal.schema.json | {} | | $.$defs.entry.allOf[0].then.revokedAt | false | null | {} | | $.$defs.entry.allOf[1] | false | | {} | | $.$defs.entry.allOf[1].if | false | | {} | | $.$defs.entry.allOf[1].if.transportStatus | false | | {"const":"revoked"} | | $.$defs.entry.allOf[1].then | false | | {} | | $.$defs.entry.allOf[1].then.signal | false | null | {} | | $.$defs.entry.allOf[1].then.revokedAt | false | string | {"format":"date-time"} | | $.$defs.alert | false | object | {"required":["code","severity","signalId","observedAt","message"],"additionalProperties":false} | | $.$defs.alert.code | true | | {"enum":["transport-unavailable","contract-rejected","pagination-incomplete","capacity-exceeded","signal-revoked","signal-republished"]} | | $.$defs.alert.severity | true | | {"enum":["info","warning","critical"]} | | $.$defs.alert.signalId | true | | {} | | $.$defs.alert.signalId.oneOf[0] | false | string | {"pattern":"^signal-policywatcher-[a-f0-9-]{36}$"} | | $.$defs.alert.signalId.oneOf[1] | false | null | {} | | $.$defs.alert.observedAt | true | string | {"format":"date-time"} | | $.$defs.alert.message | true | string | {"minLength":1,"maxLength":300} | PALO-AI Production Admission Profile palo-production-profile.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","profileId","deploymentId","environment","identity","tenantIsolation","persistence","keyCustody","executionBoundary","observability","independentAssurance","decision"],"additionalProperties":false} | | $.format | true | | {"const":"palo-production-profile"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.profileId | true | string | {} | | $.deploymentId | true | string | {} | | $.environment | true | | {"enum":["evaluation","staging","production"]} | | $.identity | true | object | {"required":["mode","issuer","audience","workloadIdentity","reviewerIdentity","tokenExpiryEnforced","evidenceRef"],"additionalProperties":false} | | $.identity.mode | true | | {"enum":["oidc","shared-token"]} | | $.identity.issuer | true | string | {} | | $.identity.audience | true | string | {} | | $.identity.workloadIdentity | true | boolean | {} | | $.identity.reviewerIdentity | true | boolean | {} | | $.identity.tokenExpiryEnforced | true | boolean | {} | | $.identity.evidenceRef | true | string | {} | | $.tenantIsolation | true | object | {"required":["mode","tokenTenantBound","claimTenantBound","storageTenantBound","negativeTestRef"],"additionalProperties":false} | | $.tenantIsolation.mode | true | | {"enum":["none","database-per-tenant","schema-per-tenant","row-level-security"]} | | $.tenantIsolation.tokenTenantBound | true | boolean | {} | | $.tenantIsolation.claimTenantBound | true | boolean | {} | | $.tenantIsolation.storageTenantBound | true | boolean | {} | | $.tenantIsolation.negativeTestRef | true | string | {} | | $.persistence | true | object | {"required":["driver","highAvailability","durableQueue","backupRecoveryTestRef","migrationControlRef"],"additionalProperties":false} | | $.persistence.driver | true | | {"enum":["sqlite","postgresql","other-production-database"]} | | $.persistence.highAvailability | true | boolean | {} | | $.persistence.durableQueue | true | boolean | {} | | $.persistence.backupRecoveryTestRef | true | string | {} | | $.persistence.migrationControlRef | true | string | {} | | $.keyCustody | true | object | {"required":["provider","privateKeyInProcess","rotationRef","revocationRef","attestationRef"],"additionalProperties":false} | | $.keyCustody.provider | true | | {"enum":["process-environment","file","kms","hsm","managed-signing-service"]} | | $.keyCustody.privateKeyInProcess | true | boolean | {} | | $.keyCustody.rotationRef | true | string | {} | | $.keyCustody.revocationRef | true | string | {} | | $.keyCustody.attestationRef | true | string | {} | | $.executionBoundary | true | object | {"required":["connectorMode","inProcessBypassDisabled","oneTimeCapabilities","receiptRequired","outcomeVerificationRequired","bypassResistanceTestRef","connectorAttestationRef"],"additionalProperties":false} | | $.executionBoundary.connectorMode | true | | {"enum":["in-process","allowlisted-proxy","remote-attested"]} | | $.executionBoundary.inProcessBypassDisabled | true | boolean | {} | | $.executionBoundary.oneTimeCapabilities | true | boolean | {} | | $.executionBoundary.receiptRequired | true | boolean | {} | | $.executionBoundary.outcomeVerificationRequired | true | boolean | {} | | $.executionBoundary.bypassResistanceTestRef | true | string | {} | | $.executionBoundary.connectorAttestationRef | true | string | {} | | $.observability | true | object | {"required":["securityEvents","tenantSafeTelemetry","alerting","incidentRunbookRef","evidenceRef"],"additionalProperties":false} | | $.observability.securityEvents | true | boolean | {} | | $.observability.tenantSafeTelemetry | true | boolean | {} | | $.observability.alerting | true | boolean | {} | | $.observability.incidentRunbookRef | true | string | {} | | $.observability.evidenceRef | true | string | {} | | $.independentAssurance | true | object | {"required":["completed","scope","reportRef","openCriticalFindings"],"additionalProperties":false} | | $.independentAssurance.completed | true | boolean | {} | | $.independentAssurance.scope | true | string | {} | | $.independentAssurance.reportRef | true | string | {} | | $.independentAssurance.openCriticalFindings | true | integer | {"minimum":0} | | $.decision | true | object | {"required":["status","decidedAt","decidedBy","validUntil","reasons"],"additionalProperties":false} | | $.decision.status | true | | {"enum":["admitted","denied","conditional"]} | | $.decision.decidedAt | true | string | {"format":"date-time"} | | $.decision.decidedBy | true | string | {} | | $.decision.validUntil | true | string | {"format":"date-time"} | | $.decision.reasons | true | array | {"minItems":1} | | $.decision.reasons[] | false | string | {} | | $.allOf[0] | false | | {} | | $.allOf[0].if | false | | {"required":["environment"]} | | $.allOf[0].if.environment | true | | {"const":"production"} | | $.allOf[0].then | false | | {} | | $.allOf[0].then.identity | false | object | {} | | $.allOf[0].then.identity.mode | false | | {"const":"oidc"} | | $.allOf[0].then.identity.workloadIdentity | false | | {"const":true} | | $.allOf[0].then.identity.reviewerIdentity | false | | {"const":true} | | $.allOf[0].then.identity.tokenExpiryEnforced | false | | {"const":true} | | $.allOf[0].then.tenantIsolation | false | object | {} | | $.allOf[0].then.tenantIsolation.mode | false | | {"enum":["database-per-tenant","schema-per-tenant","row-level-security"]} | | $.allOf[0].then.tenantIsolation.tokenTenantBound | false | | {"const":true} | | $.allOf[0].then.tenantIsolation.claimTenantBound | false | | {"const":true} | | $.allOf[0].then.tenantIsolation.storageTenantBound | false | | {"const":true} | | $.allOf[0].then.persistence | false | object | {} | | $.allOf[0].then.persistence.driver | false | | {"enum":["postgresql","other-production-database"]} | | $.allOf[0].then.persistence.highAvailability | false | | {"const":true} | | $.allOf[0].then.persistence.durableQueue | false | | {"const":true} | | $.allOf[0].then.keyCustody | false | object | {} | | $.allOf[0].then.keyCustody.provider | false | | {"enum":["kms","hsm","managed-signing-service"]} | | $.allOf[0].then.keyCustody.privateKeyInProcess | false | | {"const":false} | | $.allOf[0].then.executionBoundary | false | object | {} | | $.allOf[0].then.executionBoundary.connectorMode | false | | {"enum":["allowlisted-proxy","remote-attested"]} | | $.allOf[0].then.executionBoundary.inProcessBypassDisabled | false | | {"const":true} | | $.allOf[0].then.executionBoundary.oneTimeCapabilities | false | | {"const":true} | | $.allOf[0].then.executionBoundary.receiptRequired | false | | {"const":true} | | $.allOf[0].then.executionBoundary.outcomeVerificationRequired | false | | {"const":true} | | $.allOf[0].then.observability | false | object | {} | | $.allOf[0].then.observability.securityEvents | false | | {"const":true} | | $.allOf[0].then.observability.tenantSafeTelemetry | false | | {"const":true} | | $.allOf[0].then.observability.alerting | false | | {"const":true} | | $.allOf[0].then.independentAssurance | false | object | {} | | $.allOf[0].then.independentAssurance.completed | false | | {"const":true} | | $.allOf[0].then.independentAssurance.openCriticalFindings | false | | {"const":0} | | $.allOf[0].then.decision | false | object | {} | | $.allOf[0].then.decision.status | false | | {"const":"admitted"} | PALO Semantic Change Impact palo-semantic-change-impact.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","changeImpactId","fromVersion","toVersion","assessedAt","status","compatibilityPolicy","changes","migrationGates"],"additionalProperties":false} | | $.format | true | | {"const":"palo-semantic-change-impact"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.changeImpactId | true | string | {"format":"uri"} | | $.fromVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.toVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.assessedAt | true | string | {"format":"date"} | | $.status | true | | {"enum":["draft","reviewed","approved-for-release"]} | | $.compatibilityPolicy | true | string | {"minLength":1} | | $.changes | true | array | {"minItems":1} | | $.changes[] | false | object | {"required":["changeId","category","summary","compatibility","affectedArtifacts","requiredAction"],"additionalProperties":false} | | $.changes[].changeId | true | string | {"pattern":"^CHANGE-[0-9]{2}$"} | | $.changes[].category | true | | {"enum":["semantic-model","lifecycle","decision","evidence","mapping","release","user-experience"]} | | $.changes[].summary | true | string | {"minLength":1} | | $.changes[].compatibility | true | | {"enum":["additive","migration-required","generated-projection"]} | | $.changes[].affectedArtifacts | true | array | {"minItems":1,"uniqueItems":true} | | $.changes[].affectedArtifacts[] | false | string | {} | | $.changes[].requiredAction | true | string | {"minLength":1} | | $.migrationGates | true | array | {"minItems":1,"uniqueItems":true} | | $.migrationGates[] | false | string | {} | PALO Atomic Semantic Mapping Registry palo-semantic-mapping-registry.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","semanticVersion","releasedAt","status","authorityBoundary","mappings"],"additionalProperties":false} | | $.format | true | | {"const":"palo-semantic-mapping-registry"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.semanticVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.releasedAt | true | string | {"format":"date"} | | $.status | true | | {"enum":["draft","in-review","approved-for-release","deprecated","superseded"]} | | $.authorityBoundary | true | string | {"minLength":1} | | $.mappings | true | array | {"minItems":1} | | $.mappings[] | false | object | {"required":["mappingId","mappingVersion","mappingType","source","target","coverageType","conditions","rationale","basis","approval","validFrom","provenance"],"additionalProperties":false} | | $.mappings[].mappingId | true | string | {"format":"uri"} | | $.mappings[].mappingVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.mappings[].mappingType | true | | {"enum":["control-to-source","control-to-indicator","control-to-gate","indicator-to-source","indicator-to-gate","gate-to-source"]} | | $.mappings[].source | true | / #/$defs/versionedRef | {} | | $.mappings[].target | true | / #/$defs/versionedRef | {} | | $.mappings[].coverageType | true | | {"enum":["total","partial","conditional","supporting"]} | | $.mappings[].conditions | true | array | {} | | $.mappings[].conditions[] | false | string | {} | | $.mappings[].rationale | true | string | {"minLength":1} | | $.mappings[].basis | true | string | {"minLength":1} | | $.mappings[].approval | true | object | {"required":["status","scope","decidedAt","decidedBy"],"additionalProperties":false} | | $.mappings[].approval.status | true | | {"enum":["draft","in-review","approved","rejected","superseded"]} | | $.mappings[].approval.scope | true | string | {"minLength":1} | | $.mappings[].approval.decidedAt | true | string | {"format":"date-time"} | | $.mappings[].approval.decidedBy | true | string | {"minLength":1} | | $.mappings[].validFrom | true | string | {"format":"date-time"} | | $.mappings[].validTo | false | string | {"format":"date-time"} | | $.mappings[].supersedesMappingId | false | string | {"format":"uri"} | | $.mappings[].provenance | true | object | {"required":["generatedFrom","generationRule"],"additionalProperties":false} | | $.mappings[].provenance.generatedFrom | true | string | {} | | $.mappings[].provenance.generationRule | true | string | {} | | $.$defs.versionedRef | false | object | {"required":["entityType","entityId","semanticId","version"],"additionalProperties":false} | | $.$defs.versionedRef.entityType | true | | {"enum":["control","indicator","gate","source"]} | | $.$defs.versionedRef.entityId | true | string | {"minLength":1} | | $.$defs.versionedRef.semanticId | true | string | {"format":"uri"} | | $.$defs.versionedRef.version | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | PALO Semantic Release Manifest palo-semantic-release-manifest.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","releaseId","semanticVersion","releasedAt","status","digestAlgorithm","items","manifestDigest","authorityBoundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-semantic-release-manifest"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.releaseId | true | string | {"format":"uri"} | | $.semanticVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.releasedAt | true | string | {"format":"date"} | | $.status | true | | {"enum":["draft","in-review","approved-for-release","deprecated","superseded"]} | | $.digestAlgorithm | true | | {"const":"sha256"} | | $.items | true | array | {"minItems":1} | | $.items[] | false | object | {"required":["itemId","path","role","semanticVersion","status","sha256"],"additionalProperties":false} | | $.items[].itemId | true | string | {"format":"uri"} | | $.items[].path | true | string | {"pattern":"^(data|formal|schemas)/"} | | $.items[].role | true | | {"enum":["canonical-catalog","lifecycle-definition","control-registry","indicator-registry","gate-registry","source-registry","provider-registry","crosswalk-registry","control-pack-registry","mapping-registry","invariant-registry","json-ld-context","ontology","constraint-profile","schema","change-impact"]} | | $.items[].schemaPath | false | string | {"pattern":"^schemas/"} | | $.items[].semanticVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.items[].status | true | | {"enum":["approved-for-release","compatibility-contract"]} | | $.items[].sha256 | true | string | {"pattern":"^[a-f0-9]{64}$"} | | $.manifestDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.authorityBoundary | true | string | {"minLength":1} | PALO Semantic Spine palo-semantic-spine.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","semanticVersion","namespace","releasedAt","status","authorityClasses","workspaces","nodes","links","stageIds","navigationIds","weights"],"additionalProperties":false} | | $.format | true | | {"const":"palo-semantic-spine"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.semanticVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.namespace | true | string | {"format":"uri","pattern":"^https://paloframework\\.org/semantic/$"} | | $.releasedAt | true | string | {"format":"date"} | | $.status | true | | {"enum":["draft","in-review","approved-for-release","deprecated","superseded"]} | | $.authorityClasses | true | object | {"required":["canonical-definition","source-backed-context","illustrative-local-preview","human-review-required"],"additionalProperties":false} | | $.authorityClasses.canonical-definition | true | / #/$defs/authorityClass | {} | | $.authorityClasses.source-backed-context | true | / #/$defs/authorityClass | {} | | $.authorityClasses.illustrative-local-preview | true | / #/$defs/authorityClass | {} | | $.authorityClasses.human-review-required | true | / #/$defs/authorityClass | {} | | $.workspaces | true | array | {"minItems":3} | | $.workspaces[] | false | object | {"required":["workspaceId","label","purpose","authorityBoundary"],"additionalProperties":false} | | $.workspaces[].workspaceId | true | | {"enum":["public-catalog","case-workspace","assurance-review"]} | | $.workspaces[].label | true | string | {"minLength":1} | | $.workspaces[].purpose | true | string | {"minLength":1} | | $.workspaces[].authorityBoundary | true | string | {"minLength":1} | | $.nodes | true | array | {"minItems":1} | | $.nodes[] | false | / #/$defs/node | {} | | $.links | true | array | {"minItems":1} | | $.links[] | false | / #/$defs/link | {} | | $.stageIds | true | array | {"minItems":1,"uniqueItems":true} | | $.stageIds[] | false | string | {} | | $.navigationIds | true | array | {"minItems":1,"uniqueItems":true} | | $.navigationIds[] | false | string | {} | | $.weights | true | object | {"minProperties":1,"additionalProperties":{"type":"string"}} | | $.weights.additionalProperties | false | string | {} | | $.$defs.authorityClass | false | object | {"required":["label","meaning","authoritative"],"additionalProperties":false} | | $.$defs.authorityClass.label | true | string | {"minLength":1} | | $.$defs.authorityClass.meaning | true | string | {"minLength":1} | | $.$defs.authorityClass.authoritative | true | boolean | {} | | $.$defs.node | false | object | {"required":["id","label","type","phaseId","role","status","semanticId","definitionVersion","evidenceClass","authorityBoundary","sourceRefs","lastReviewed"],"additionalProperties":true} | | $.$defs.node.id | true | string | {"pattern":"^[a-z0-9][a-z0-9-]*$"} | | $.$defs.node.label | true | string | {"minLength":1} | | $.$defs.node.type | true | | {"enum":["stage","module","artifact","actor","source","control","metric","navigation"]} | | $.$defs.node.phaseId | true | | {"enum":["frame","classify","assess","control","measure","prove"]} | | $.$defs.node.role | true | string | {"minLength":1} | | $.$defs.node.status | true | string | {"minLength":1} | | $.$defs.node.semanticId | true | string | {"format":"uri"} | | $.$defs.node.definitionVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.node.evidenceClass | true | | {"enum":["canonical-definition","source-backed-context","illustrative-local-preview","human-review-required"]} | | $.$defs.node.authorityBoundary | true | string | {"minLength":1} | | $.$defs.node.sourceRefs | true | array | {"uniqueItems":true} | | $.$defs.node.sourceRefs[] | false | string | {} | | $.$defs.node.lastReviewed | true | string | {"format":"date"} | | $.$defs.node.properties | false | object | {} | | $.$defs.node.outputs | false | array | {} | | $.$defs.node.outputs[] | false | string | {} | | $.$defs.link | false | object | {"required":["source","target","verb","weight","meaning","artifactTransferred","relationType","semanticId","relationshipVersion","mappingBasis"],"additionalProperties":false} | | $.$defs.link.source | true | string | {} | | $.$defs.link.target | true | string | {} | | $.$defs.link.verb | true | string | {"minLength":1} | | $.$defs.link.weight | true | string | {"pattern":"^W[2-5]$"} | | $.$defs.link.meaning | true | string | {"minLength":1} | | $.$defs.link.artifactTransferred | true | string | {} | | $.$defs.link.relationType | true | | {"enum":["operational","evidence","feedback","context","support","navigation"]} | | $.$defs.link.semanticId | true | string | {"format":"uri"} | | $.$defs.link.relationshipVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.link.mappingBasis | true | string | {"minLength":1} | PALO Serious Incident and Regulatory Clock Record palo-serious-incident-record.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","incidentId","caseId","systemVersion","detectedAt","containedAt","severity","effects","jurisdictions","reportability","notifications","correctiveActions","closure"],"additionalProperties":false} | | $.format | true | | {"const":"palo-serious-incident-record"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.incidentId | true | string | {} | | $.caseId | true | string | {} | | $.systemVersion | true | string | {} | | $.detectedAt | true | string | {"format":"date-time"} | | $.containedAt | true | string | {"format":"date-time"} | | $.severity | true | | {"enum":["low","moderate","high","critical"]} | | $.effects | true | array | {"minItems":1} | | $.effects[] | false | object | {"required":["effectType","description","affectedScope"],"additionalProperties":false} | | $.effects[].effectType | true | | {"enum":["death","serious-harm","rights-infringement","critical-infrastructure","property-environment","cybersecurity","other"]} | | $.effects[].description | true | string | {"minLength":10} | | $.effects[].affectedScope | true | string | {} | | $.jurisdictions | true | array | {"minItems":1} | | $.jurisdictions[] | false | object | {"required":["jurisdiction","sourceProvision","clockStart","deadline","authorityRoute"],"additionalProperties":false} | | $.jurisdictions[].jurisdiction | true | string | {} | | $.jurisdictions[].sourceProvision | true | string | {} | | $.jurisdictions[].clockStart | true | string | {"format":"date-time"} | | $.jurisdictions[].deadline | true | string | {"format":"date-time"} | | $.jurisdictions[].authorityRoute | true | string | {} | | $.reportability | true | object | {"required":["status","decidedAt","decidedBy","rationale","legalReviewRef"],"additionalProperties":false} | | $.reportability.status | true | | {"enum":["reportable","not-reportable","undetermined"]} | | $.reportability.decidedAt | true | string | {"format":"date-time"} | | $.reportability.decidedBy | true | string | {} | | $.reportability.rationale | true | string | {"minLength":20} | | $.reportability.legalReviewRef | true | string | {} | | $.notifications | true | array | {} | | $.notifications[] | false | object | {"required":["recipient","notificationType","submittedAt","receiptRef"],"additionalProperties":false} | | $.notifications[].recipient | true | string | {} | | $.notifications[].notificationType | true | | {"enum":["initial","follow-up","final","affected-person","provider","other"]} | | $.notifications[].submittedAt | true | string | {"format":"date-time"} | | $.notifications[].receiptRef | true | string | {} | | $.correctiveActions | true | array | {"minItems":1} | | $.correctiveActions[] | false | object | {"required":["actionId","owner","dueAt","status","effectivenessEvidenceRef"],"additionalProperties":false} | | $.correctiveActions[].actionId | true | string | {} | | $.correctiveActions[].owner | true | string | {} | | $.correctiveActions[].dueAt | true | string | {"format":"date-time"} | | $.correctiveActions[].status | true | | {"enum":["open","in-progress","completed","verified-closed"]} | | $.correctiveActions[].effectivenessEvidenceRef | true | string | {} | | $.closure | true | object | {"required":["status","closedAt","closedBy","postIncidentReviewRef"],"additionalProperties":false} | | $.closure.status | true | | {"enum":["open","contained","reporting","correcting","closed"]} | | $.closure.closedAt | true | string | {"format":"date-time"} | | $.closure.closedBy | true | string | {} | | $.closure.postIncidentReviewRef | true | string | {} | PALO Source Registry palo-source-registry.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","status","updatedAt","disclaimer","sources"],"additionalProperties":false} | | $.format | true | | {"const":"palo-source-registry"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.status | true | | {"const":"educational-non-production"} | | $.updatedAt | true | string | {"format":"date"} | | $.disclaimer | true | string | {"minLength":20} | | $.sources | true | array | {"minItems":1} | | $.sources[] | false | object | {"required":["sourceId","title","url","sourceType","publisher","checkedAt","freshness","authorityStatus","usageNote"],"additionalProperties":false} | | $.sources[].sourceId | true | string | {"pattern":"^src-[a-z0-9-]+$"} | | $.sources[].title | true | string | {"minLength":1} | | $.sources[].url | true | string | {"format":"uri"} | | $.sources[].sourceType | true | | {"enum":["official","standard","organizational","research","monitoring-signal"]} | | $.sources[].publisher | true | string | {"minLength":1} | | $.sources[].checkedAt | true | string | {"format":"date-time"} | | $.sources[].freshness | true | object | {"required":["status","reviewIntervalDays","nextReviewAt"],"additionalProperties":false} | | $.sources[].freshness.status | true | | {"enum":["current","review-due","stale","superseded","unknown"]} | | $.sources[].freshness.reviewIntervalDays | true | integer | {"minimum":1} | | $.sources[].freshness.nextReviewAt | true | string | {"format":"date-time"} | | $.sources[].authorityStatus | true | | {"enum":["authoritative-primary","authoritative-standard","informative","non-authoritative-monitoring-signal"]} | | $.sources[].usageNote | true | string | {"minLength":10} | PALO stack architecture extension palo-stack-governance-model.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","extensionVersion","status","foundationRef","foundationVersion","reviewedAt","authorityBoundary","sources","entityTypes","relationshipTypes","view"],"additionalProperties":false} | | $.format | true | | {"const":"palo-stack-governance-model"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.extensionVersion | true | | {"const":"0.1.0"} | | $.status | true | | {"const":"draft"} | | $.foundationRef | true | string | {"minLength":1} | | $.foundationVersion | true | | {"const":"3.1.0"} | | $.reviewedAt | true | string | {"format":"date"} | | $.authorityBoundary | true | string | {"minLength":1} | | $.sources | true | array | {} | | $.sources[] | false | object | {"required":["id","url"],"additionalProperties":false} | | $.sources[].id | true | string | {"minLength":1} | | $.sources[].url | true | string | {"format":"uri"} | | $.entityTypes | true | array | {} | | $.entityTypes[] | false | object | {"required":["id","semanticId","origin"],"additionalProperties":false} | | $.entityTypes[].id | true | string | {"minLength":1} | | $.entityTypes[].semanticId | true | string | {"format":"uri"} | | $.entityTypes[].origin | true | | {"enum":["palo-3.1","stack-extension-0.1"]} | | $.relationshipTypes | true | array | {} | | $.relationshipTypes[] | false | object | {"required":["id","sourceTypes","targetTypes","meaning"],"additionalProperties":false} | | $.relationshipTypes[].id | true | string | {"minLength":1} | | $.relationshipTypes[].sourceTypes | true | array | {"uniqueItems":true} | | $.relationshipTypes[].sourceTypes[] | false | string | {"minLength":1} | | $.relationshipTypes[].targetTypes | true | array | {"uniqueItems":true} | | $.relationshipTypes[].targetTypes[] | false | string | {"minLength":1} | | $.relationshipTypes[].meaning | true | string | {"minLength":1} | | $.relationshipTypes[].maxPerSource | false | integer | {"minimum":1} | | $.relationshipTypes[].minPerSource | false | integer | {"minimum":0} | | $.view | true | object | {"required":["nodes","links"],"additionalProperties":false} | | $.view.nodes | true | array | {"minItems":1} | | $.view.nodes[] | false | / #/$defs/node | {} | | $.view.links | true | array | {"minItems":1} | | $.view.links[] | false | / #/$defs/link | {} | | $.$defs.authorityClass | false | object | {"required":["label","meaning","authoritative"],"additionalProperties":false} | | $.$defs.authorityClass.label | true | string | {"minLength":1} | | $.$defs.authorityClass.meaning | true | string | {"minLength":1} | | $.$defs.authorityClass.authoritative | true | boolean | {} | | $.$defs.node | false | object | {"required":["id","label","type","phaseId","role","status","semanticId","definitionVersion","evidenceClass","authorityBoundary","sourceRefs","lastReviewed"],"additionalProperties":true} | | $.$defs.node.id | true | string | {"pattern":"^[a-z0-9][a-z0-9-]*$"} | | $.$defs.node.label | true | string | {"minLength":1} | | $.$defs.node.type | true | | {"enum":["layer","plane","component"]} | | $.$defs.node.phaseId | true | | {"enum":["frame","classify","assess","control","measure","prove"]} | | $.$defs.node.role | true | string | {"minLength":1} | | $.$defs.node.status | true | string | {"minLength":1} | | $.$defs.node.semanticId | true | string | {"format":"uri"} | | $.$defs.node.definitionVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.node.evidenceClass | true | | {"enum":["canonical-definition","source-backed-context","illustrative-local-preview","human-review-required"]} | | $.$defs.node.authorityBoundary | true | string | {"minLength":1} | | $.$defs.node.sourceRefs | true | array | {"uniqueItems":true} | | $.$defs.node.sourceRefs[] | false | string | {} | | $.$defs.node.lastReviewed | true | string | {"format":"date"} | | $.$defs.node.properties | false | object | {} | | $.$defs.node.outputs | false | array | {} | | $.$defs.node.outputs[] | false | string | {} | | $.$defs.link | false | object | {"required":["source","target","verb","weight","meaning","artifactTransferred","relationType","semanticId","relationshipVersion","mappingBasis"],"additionalProperties":false} | | $.$defs.link.source | true | string | {} | | $.$defs.link.target | true | string | {} | | $.$defs.link.verb | true | string | {"minLength":1} | | $.$defs.link.weight | true | string | {"pattern":"^W[2-5]$"} | | $.$defs.link.meaning | true | string | {"minLength":1} | | $.$defs.link.artifactTransferred | true | string | {} | | $.$defs.link.relationType | true | | {"enum":["operational","evidence","feedback","context","support","navigation"]} | | $.$defs.link.semanticId | true | string | {"format":"uri"} | | $.$defs.link.relationshipVersion | true | string | {"pattern":"^\\d+\\.\\d+\\.\\d+$"} | | $.$defs.link.mappingBasis | true | string | {"minLength":1} | PALO Swarm Mandate palo-swarm-mandate.schema.json Unreleased local prototype: immutable initial membership, accountable mandate and conservative shared exposure budget. Not distributed swarm assurance. Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"additionalProperties":false,"required":["format","schemaVersion","mandateVersion","swarmId","caseId","tenantId","owner","objective","coordinatorAgentId","members","validFrom","expiresAt","budget","maxConcurrentExecutions","keyId"]} | Unreleased local prototype: immutable initial membership, accountable mandate and conservative shared exposure budget. Not distributed swarm assurance. | $.format | true | | {"const":"palo-swarm-mandate"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.mandateVersion | true | string | {"pattern":"^[1-9][0-9]*\\.[0-9]+\\.[0-9]+$"} | | $.swarmId | true | string | {"pattern":"^swarm-[a-zA-Z0-9-]{6,100}$"} | | $.caseId | true | string | {"minLength":1,"maxLength":128} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.objective | true | string | {"minLength":10,"maxLength":2000} | | $.owner | true | object | {"additionalProperties":false,"required":["subject","issuer"]} | | $.owner.subject | true | string | {"minLength":1,"maxLength":512} | | $.owner.issuer | true | string | {"format":"uri","maxLength":1000} | | $.coordinatorAgentId | true | / #/$defs/agentId | {} | | $.members | true | array | {"minItems":1,"maxItems":1000} | | $.members[] | false | object | {"additionalProperties":false,"required":["agentId","parentAgentId","profileDigest"]} | | $.members[].agentId | true | / #/$defs/agentId | {} | | $.members[].parentAgentId | true | | {} | | $.members[].parentAgentId.anyOf[0] | false | / #/$defs/agentId | {} | | $.members[].parentAgentId.anyOf[1] | false | null | {} | | $.members[].profileDigest | true | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | | $.validFrom | true | string | {"format":"date-time"} | | $.expiresAt | true | string | {"format":"date-time"} | | $.maxConcurrentExecutions | true | integer | {"minimum":1,"maximum":1000} | | $.keyId | true | string | {"pattern":"^key-[a-zA-Z0-9._-]{3,100}$"} | | $.budget | true | object | {"additionalProperties":false,"required":["unit","limitUnits","rules"]} | | $.budget.unit | true | string | {"minLength":1,"maxLength":80} | | $.budget.limitUnits | true | integer | {"minimum":0,"maximum":1000000000000} | | $.budget.rules | true | array | {"minItems":1,"maxItems":100} | | $.budget.rules[] | false | object | {"additionalProperties":false,"required":["tool","operation","resource","pathPrefix","maxUnitsPerAction"]} | | $.budget.rules[].tool | true | string | {"minLength":1,"maxLength":200} | | $.budget.rules[].operation | true | | {"enum":["read","create","update","delete","execute","delegate"]} | | $.budget.rules[].resource | true | string | {"minLength":1,"maxLength":1000} | | $.budget.rules[].pathPrefix | true | string | {"pattern":"^/","maxLength":1000} | | $.budget.rules[].maxUnitsPerAction | true | integer | {"minimum":0,"maximum":1000000000000} | | $.budget.rules[].amountPointer | false | string | {"pattern":"^/","maxLength":500} | | $.budget.rules[].fixedUnits | false | integer | {"minimum":0,"maximum":1000000000000} | | $.budget.rules[].oneOf[0] | false | | {"required":["amountPointer"]} | | $.budget.rules[].oneOf[0].amountPointer | true | | {} | | $.budget.rules[].oneOf[1] | false | | {"required":["fixedUnits"]} | | $.budget.rules[].oneOf[1].fixedUnits | true | | {} | | $.$defs.agentId | false | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | PALO Swarm Membership Change palo-swarm-membership-change.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"additionalProperties":false,"required":["format","schemaVersion","changeId","swarmId","tenantId","expectedMembershipDigest","members","reason"]} | | $.format | true | | {"const":"palo-swarm-membership-change"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.changeId | true | string | {"pattern":"^membership-[a-zA-Z0-9-]{6,100}$"} | | $.swarmId | true | string | {"pattern":"^swarm-[a-zA-Z0-9-]{6,100}$"} | | $.tenantId | true | string | {"minLength":1,"maxLength":128} | | $.expectedMembershipDigest | true | / #/$defs/digest | {} | | $.reason | true | string | {"minLength":1,"maxLength":2000} | | $.members | true | array | {"minItems":1,"maxItems":100} | | $.members[] | false | object | {"additionalProperties":false,"required":["agentId","parentAgentId","profileDigest"]} | | $.members[].agentId | true | / #/$defs/agentId | {} | | $.members[].parentAgentId | true | / #/$defs/agentId | {} | | $.members[].profileDigest | true | / #/$defs/digest | {} | | $.$defs.agentId | false | string | {"pattern":"^agent-[a-zA-Z0-9][a-zA-Z0-9-]{5,63}$"} | | $.$defs.digest | false | string | {"pattern":"^sha256:[a-f0-9]{64}$"} | PALO System and Model Card palo-system-card.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","cardId","caseId","system","purpose","stakeholders","components","data","performance","limitations","humanOversight","transparency","monitoring","changeHistory","owner","review"],"additionalProperties":false} | | $.format | true | | {"const":"palo-system-card"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.cardId | true | string | {"minLength":1} | | $.caseId | true | string | {"minLength":1} | | $.system | true | object | {"required":["name","version","releaseStatus"],"additionalProperties":false} | | $.system.name | true | string | {"minLength":1} | | $.system.version | true | string | {"minLength":1} | | $.system.releaseStatus | true | | {"enum":["development","pilot","production","retiring","retired"]} | | $.purpose | true | object | {"required":["intendedUses","prohibitedUses","decisionSignificance"],"additionalProperties":false} | | $.purpose.intendedUses | true | / #/$defs/nonEmptyStrings | {} | | $.purpose.prohibitedUses | true | / #/$defs/nonEmptyStrings | {} | | $.purpose.decisionSignificance | true | string | {"minLength":20} | | $.stakeholders | true | array | {"minItems":1} | | $.stakeholders[] | false | object | {"required":["group","relationship","explanationNeed"],"additionalProperties":false} | | $.stakeholders[].group | true | string | {"minLength":1} | | $.stakeholders[].relationship | true | string | {"minLength":1} | | $.stakeholders[].explanationNeed | true | string | {"minLength":10} | | $.components | true | array | {"minItems":1} | | $.components[] | false | object | {"required":["componentId","type","provider","version"],"additionalProperties":false} | | $.components[].componentId | true | string | {} | | $.components[].type | true | | {"enum":["model","rule","retrieval","tool","dataset","human-process","other"]} | | $.components[].provider | true | string | {} | | $.components[].version | true | string | {} | | $.data | true | object | {"required":["lineageRecordIds","sensitiveData","knownLimits"],"additionalProperties":false} | | $.data.lineageRecordIds | true | / #/$defs/nonEmptyStrings | {} | | $.data.sensitiveData | true | boolean | {} | | $.data.knownLimits | true | / #/$defs/nonEmptyStrings | {} | | $.performance | true | array | {"minItems":1} | | $.performance[] | false | object | {"required":["metric","scope","value","thresholdDecision"],"additionalProperties":false} | | $.performance[].metric | true | string | {} | | $.performance[].scope | true | string | {} | | $.performance[].value | true | | {} | | $.performance[].value.oneOf[0] | false | number | {} | | $.performance[].value.oneOf[1] | false | string | {} | | $.performance[].thresholdDecision | true | | {"enum":["pass","conditional","fail"]} | | $.limitations | true | / #/$defs/nonEmptyStrings | {} | | $.humanOversight | true | object | {"required":["roles","interventions","escalation"],"additionalProperties":false} | | $.humanOversight.roles | true | / #/$defs/nonEmptyStrings | {} | | $.humanOversight.interventions | true | / #/$defs/nonEmptyStrings | {} | | $.humanOversight.escalation | true | string | {"minLength":10} | | $.transparency | true | object | {"required":["notice","explanationArtifacts","appealRoute"],"additionalProperties":false} | | $.transparency.notice | true | string | {"minLength":10} | | $.transparency.explanationArtifacts | true | / #/$defs/nonEmptyStrings | {} | | $.transparency.appealRoute | true | string | {"minLength":5} | | $.monitoring | true | object | {"required":["indicatorIds","reviewCadence","reopenTriggers"],"additionalProperties":false} | | $.monitoring.indicatorIds | true | / #/$defs/nonEmptyStrings | {} | | $.monitoring.reviewCadence | true | string | {"minLength":1} | | $.monitoring.reopenTriggers | true | / #/$defs/nonEmptyStrings | {} | | $.changeHistory | true | array | {"minItems":1} | | $.changeHistory[] | false | object | {"required":["version","changedAt","summary"],"additionalProperties":false} | | $.changeHistory[].version | true | string | {} | | $.changeHistory[].changedAt | true | string | {"format":"date-time"} | | $.changeHistory[].summary | true | string | {"minLength":10} | | $.owner | true | string | {"minLength":1} | | $.review | true | object | {"required":["status","reviewedAt","reviewedBy","validUntil"],"additionalProperties":false} | | $.review.status | true | | {"enum":["accepted","conditional","rejected"]} | | $.review.reviewedAt | true | string | {"format":"date-time"} | | $.review.reviewedBy | true | string | {"minLength":1} | | $.review.validUntil | true | string | {"format":"date-time"} | | $.$defs.nonEmptyStrings | false | array | {"minItems":1,"uniqueItems":true} | | $.$defs.nonEmptyStrings[] | false | string | {"minLength":1} | PALO PolicyWatcher Signal Batch policywatcher-signal-batch.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","mode","locale","count","limit","hasMore","nextCursor","signals","boundary"],"additionalProperties":false} | | $.format | true | | {"const":"palo-policywatcher-signal-batch"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.mode | true | | {"const":"complete-active-snapshot"} | | $.locale | true | | {"enum":["en","it"]} | | $.count | true | integer | {"minimum":0,"maximum":25} | | $.limit | true | integer | {"minimum":1,"maximum":25} | | $.hasMore | true | boolean | {} | | $.nextCursor | true | | {} | | $.nextCursor.oneOf[0] | false | string | {"pattern":"^[A-Za-z0-9_-]{1,256}$"} | | $.nextCursor.oneOf[1] | false | null | {} | | $.signals | true | array | {"maxItems":25} | | $.signals[] | false | / https://paloframework.org/schemas/policywatcher-signal.schema.json | {} | | $.boundary | true | string | {"minLength":80,"maxLength":1000} | PALO PolicyWatcher Monitoring Signal policywatcher-signal.schema.json Canonical schema · Inspected schema snapshot | Schema path | Required in parent | Type or reference | Values and constraints | Description | $ | false | object | {"required":["format","schemaVersion","signalId","observedAt","source","summary","changeType","subjects","confidence","authority","suggestedHandoff"],"additionalProperties":true} | | $.format | true | | {"const":"palo-policywatcher-signal"} | | $.schemaVersion | true | | {"const":"1.0.0"} | | $.signalId | true | string | {"pattern":"^signal-[a-z0-9-]+$"} | | $.observedAt | true | string | {"format":"date-time"} | | $.source | true | object | {"required":["sourceId","title","url","publisher","checkedAt"],"additionalProperties":true} | | $.source.sourceId | true | string | {} | | $.source.title | true | string | {} | | $.source.url | true | string | {"format":"uri"} | | $.source.publisher | true | string | {} | | $.source.checkedAt | true | string | {"format":"date-time"} | | $.summary | true | string | {"minLength":1} | | $.changeType | true | | {"enum":["new-publication","amendment","guidance","enforcement","consultation","correction","unknown"]} | | $.subjects | true | array | {"minItems":1,"uniqueItems":true} | | $.subjects[] | false | string | {} | | $.jurisdictions | false | array | {"uniqueItems":true} | | $.jurisdictions[] | false | string | {} | | $.confidence | true | object | {"required":["level","score","rationale"],"additionalProperties":true} | | $.confidence.level | true | | {"enum":["low","medium","high"]} | | $.confidence.score | true | number | {"minimum":0,"maximum":1} | | $.confidence.rationale | true | string | {"minLength":1} | | $.authority | true | object | {"required":["status","disclaimer"],"additionalProperties":true} | | $.authority.status | true | | {"const":"non-authoritative-monitoring-signal"} | | $.authority.disclaimer | true | string | {"minLength":20} | | $.suggestedHandoff | true | object | {"required":["module","eventName","reviewGateIds"],"additionalProperties":true} | | $.suggestedHandoff.module | true | | {"const":"PALO_RegulatoryWatch"} | | $.suggestedHandoff.eventName | true | | {"const":"palo:policywatcher:signal"} | | $.suggestedHandoff.reviewGateIds | true | array | {"minItems":1,"uniqueItems":true} | | $.suggestedHandoff.reviewGateIds[] | false | | {"enum":["frame","classify","assess","control","measure","prove"]} | ## Verification This catalogue preserves the earlier inspected snapshot. See the subsequent six-source review, current source registry and current control packs for source-maintenance updates. 61 JSON fixture classifications matched expectation. The core RDF valid fixture conformed; the invalid fixture returned 10 violations. All 40 core release item digests matched. These checks are scoped to the acquired snapshot. Full validation results · Source provenance