Ensure governance runner records failure diagnostics in report

Author: OneFineStarstuff

.github/workflows/sentinel-governance-gates.yml

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+name: Sentinel Governance Gates
+
+on:
+  pull_request:
+  push:
+    branches: [main]
+
+jobs:
+  governance-gates:
+    runs-on: ubuntu-latest
+    timeout-minutes: 20
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install Python dependencies
+        run: pip install -r requirements-dev.txt
+
+      - name: Install ripgrep
+        run: sudo apt-get update && sudo apt-get install -y ripgrep
+
+      - name: Run governance gate bundle (strict OPA)
+        env:
+          STRICT_OPA: "1"
+          OPA_VERSION: "v1.7.1"
+        run: ./tools/run_governance_gates.sh --strict-opa
+
+      - name: Upload validation report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: sentinel-governance-validation-report
+          path: /tmp/sentinel_governance_validation_report.json
+        if-no-files-found: error

docs/sentinel_ai_governance_v2_4_reference_architecture_2026_2035.md

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+# Sentinel AI Governance Stack v2.4 — Enterprise AGI/ASI Governance, Containment, and zk-Compliance Reference Architecture (2026–2035)
+
+## 1. Scope and Design Principles
+
+This blueprint defines an implementation roadmap and target architecture for Fortune 500, Global 2000, and G-SIFI institutions deploying advanced frontier AI under strict safety, model risk, operational resilience, and privacy obligations.
+
+### Core principles
+1. **Safety-over-availability defaults** for AGI/ASI class systems.
+2. **Provable compliance** via machine-readable controls + cryptographic attestations.
+3. **Dual-loop supervision**: autonomous supervisory agents + human accountable officers.
+4. **Containment depth**: identity, network, compute, data, and behavior constraints.
+5. **Continuous assurance**: BBOM/perpetual assurance replacing point-in-time audits.
+6. **Regulatory portability** through normalized OSCAL control abstraction.
+
+## 2. Reference Architecture (Logical)
+
+## 2.1 Layered Stack
+
+1. **Governance Layer (Sentinel AI Governance Stack v2.4 / G-Stack)**
+   - Policy registry, regulator profile pack, board dashboards, risk appetite and delegation matrices.
+2. **Control Orchestration (WorkflowAI Pro)**
+   - Workflow compiler for controls-as-code, evidence jobs, attestations, exception routing.
+3. **Safety & Containment Plane (Omni-Sentinel)**
+   - Runtime guardrails, secure enclaves, process isolation, kill-switch graph, policy enforcement.
+4. **Autonomous Supervisory Agents (ASA mesh)**
+   - Independent model sentinels monitoring capability drift, deception signatures, and unsafe tool use.
+5. **Observability & Response (GAI-SOC)**
+   - AI-native SOC telemetry, causal graph analytics, anomaly triage, incident playbooks.
+6. **Assurance & Audit Plane**
+   - Kafka event backbone, PQC signatures, WORM retention, reproducible evidence manifests.
+7. **Cryptographic Compliance Plane**
+   - Circom/Groth16 (fast proving) + STARK proofs (transparency), GC-IR bridge for regulator verifiers.
+8. **Enterprise Integration Layer**
+   - IAM, SIEM, ITSM, MRM platforms, treasury/risk engines, data governance and legal hold systems.
+
+## 2.2 Trust Zones and Data Flow
+
+- **Zone A (Regulated CorpNet)**: user applications, workflow interfaces.
+- **Zone B (AI Control Plane)**: orchestrators, policy engines, signed deployment artifacts.
+- **Zone C (Containment Compute Fabric)**: frontier model runtimes, tool execution sandboxes.
+- **Zone D (Assurance Vault)**: append-only audit storage, proof artifacts, regulator export bundles.
+- **Zone E (Regulator/Assessor Verifier Edge)**: read-only validation endpoints, proof verification services.
+
+All inter-zone calls require mTLS, hardware-backed workload identity, and signed policy tokens.
+
+## 3. Sentinel v2.4 Component Blueprint
+
+## 3.1 G-Stack Governance Kernel
+
+- **Policy Object Model**: risk domain, control objective, implementation assertion, evidence schema.
+- **Regulator Mapping Engine**: maps normalized controls to EU AI Act Annex IV, NIST AI RMF, ISO/IEC 42001, Basel/SR guidance, DORA/NIS2, consumer protection rules.
+- **Board/C-suite Views**: KRIs (G-SRI), risk heat maps, unresolved exceptions, model inventory criticality.
+- **Delegation Graph**: links accountable executives (e.g., SMCR functions) to control ownership.
+
+## 3.2 WorkflowAI Pro Control Automation
+
+- DAG-based control execution with deterministic runbooks.
+- Multi-stage approvals (4-eyes/6-eyes) for high-impact model releases.
+- Evidence packaging into OSCAL assessment-results + cryptographic hash manifests.
+- CI/CD gates: policy checks, failed evidence freshness, formal spec violations.
+
+## 3.3 Omni-Sentinel Containment
+
+- **Runtime constraints**: egress allow-lists, syscall policy, capability firewalls.
+- **Tool mediation**: all external actions via broker with risk scoring.
+- **Compute governance**: quota ceilings, conditional escalation approvals, emergency pause.
+- **Cognitive tripwires**: detector ensemble for deception, self-replication attempts, covert channel behavior.
+
+## 3.4 Autonomous Supervisory Agents (ASA)
+
+- Independent model family from production models to reduce common-mode failure.
+- Supervisory protocols:
+  - pre-action review for privileged actions,
+  - post-action forensic consistency checks,
+  - rolling challenge tests against policy constraints.
+- Escalation to human supervisory committee on confidence breach thresholds.
+
+## 3.5 GAI-SOC Telemetry and Red Dawn Simulations
+
+- **Telemetry fabric**: prompts, tool traces, policy decisions, model internal safety signals, infra events.
+- **Red Dawn**: adversarial simulation framework for model jailbreaks, insider threat, data poisoning, and emergent autonomy drills.
+- Replayable incident timelines with deterministic re-simulation and invariant checking.
+
+## 3.6 G-SRI (Systemic Risk Index)
+
+Composite risk metric:
+- capability concentration,
+- cross-institution coupling,
+- market critical function dependency,
+- model opacity,
+- containment maturity,
+- incident velocity.
+
+Used for board risk appetite, capital/liquidity overlays, and supervisory dialogue.
+
+## 3.7 BBOM / Perpetual Assurance
+
+- Business Bill of Operations & Models captures model lineage, dependencies, training provenance, third-party risk, and control inheritance.
+- Continuous attestation loops produce rolling “assurance snapshots” every control interval.
+
+## 4. Formal Methods and Control Logic
+
+## 4.1 TLA+ Specifications
+
+Define critical invariants, e.g.:
+- **Invariant C1**: No high-risk autonomous action executes without active policy token + supervisory quorum.
+- **Invariant C2**: Kill-switch always preempts model action queue within bounded latency.
+- **Invariant C3**: Evidence records are immutable and cryptographically linked.
+- **Invariant C4**: Cross-border data transfer only under jurisdictional policy satisfaction.
+
+Model check each release candidate; block promotion on invariant violation.
+
+## 4.2 OPA/Rego Compliance-as-Code
+
+- Rego policies evaluate deployment manifests, data access requests, and runtime actions.
+- Policy bundles versioned and signed.
+- CI/CD integrates:
+  - static policy lint,
+  - policy unit tests,
+  - synthetic evidence tests,
+  - conformance packs per jurisdiction.
+
+## 5. Cryptographic Assurance and zk Architecture
+
+## 5.1 Kafka + PQC WORM Audit Fabric
+
+- Kafka topics partitioned by control domain and criticality.
+- Event envelopes signed using PQC-capable schemes (hybrid mode during transition).
+- Daily Merkle roots committed to WORM storage with legal hold tagging.
+
+## 5.2 Circom/Groth16 + STARK Proof Strategy
+
+- **Groth16 circuits** for low-latency operational proofs (e.g., policy gate executed).
+- **STARK proofs** for high-assurance transparency proofs and long-term auditability.
+- **GC-IR bridge**: canonical intermediate representation allowing regulator-side verifier portability.
+
+## 5.3 Example Proof Statements
+
+1. “All production model deployments in period T passed required SR 11-7 validation controls.”
+2. “No restricted personal-data category left approved zones without lawful basis policy pass.”
+3. “All systemic-risk simulation scenarios above threshold had approved mitigation actions executed.”
+
+## 6. Regulatory Mapping Framework (Multi-jurisdiction)
+
+## 6.1 Normalized Control Families
+
+- GOV (governance/accountability)
+- RSK (risk management)
+- SAF (safety/containment)
+- SEC (cybersecurity/operational resilience)
+- DAT (data/privacy)
+- MOD (model lifecycle and validation)
+- AUD (auditability and assurance)
+- ETH (fairness/consumer outcomes)
+
+## 6.2 Mappings
+
+- **EU AI Act**: Annex IV technical documentation, post-market monitoring, systemic-risk GPAI obligations.
+- **NIST AI RMF 1.0 + AI 600-1 profile alignment**: govern/map/measure/manage functions.
+- **ISO/IEC 42001 AIMS**: management system clauses and control objectives.
+- **Basel III/IV + SR 11-7/SR 26-2**: model risk governance, validation independence, stress and scenario integrity.
+- **DORA + NIS2**: ICT risk, incident reporting, resilience testing.
+- **GDPR + FCRA/ECOA**: lawful basis, transparency, adverse action explainability, fairness outcomes.
+- **MAS/HKMA FEAT; FCA SMCR/Consumer Duty; HKMA Fintech 2030**: accountability and customer outcome governance.
+- **ICGC/GASO compute governance**: frontier compute registration, safety case gating, and emergency coordination protocols.
+
+## 7. Phased Roadmap
+
+## 7.1 Phase 0 (Q3 2026–Q2 2027): Foundation
+
+- Establish enterprise AI control taxonomy in OSCAL.
+- Stand up GAI-SOC minimum telemetry and incident runbooks.
+- Deploy baseline OPA policies for model release governance.
+- Implement TLA+ specs for top-10 high-risk workflows.
+- Begin BBOM data model and inventory normalization.
+
+Deliverables:
+- Control catalog v1, evidence schema v1, board-level KRI pack.
+
+## 7.2 Phase 1 (Q3 2027–Q4 2028): Verified Controls (ICGC Phase 1)
+
+- Productionize Omni-Sentinel containment with enforceable runtime boundaries.
+- Add Groth16 proofs for critical control families (GOV/SAF/MOD/AUD).
+- Integrate WorkflowAI Pro with CI/CD across all AI deployment pipelines.
+- Launch Red Dawn quarterly simulation program with regulator-observer mode.
+
+Deliverables:
+- zk-verified control attestations for high-risk models.
+
+## 7.3 Phase 2 (2029–2030): Systemic-Risk-Integrated Governance (ICGC Phase 2)
+
+- Extend proof coverage to cross-entity systemic-risk controls and concentration constraints.
+- Introduce STARK-based transparent audit proofs for annual supervisory reviews.
+- Mature ASA mesh with independent adjudication and confidence-weighted escalation.
+- Operationalize G-SRI as capital/risk appetite input in board governance.
+
+Deliverables:
+- End-to-end cryptographic compliance dossier and systemic-risk posture scorecards.
+
+## 7.4 2031–2035 Extension: ASI-Ready Supervisory Regime
+
+- Dynamic regulator profiles update automatically from signed supervisory bulletins.
+- Interbank federated simulation exchanges for contagion and coordination drills.
+- Confidential multi-party proofs for sector-wide aggregate compliance reporting.
+- Compute governance integration with civilizational risk protocols and emergency compute throttling.
+
+## 8. Machine-Readable Artifact Templates
+
+## 8.1 OSCAL Control Snippet (YAML)
+
+```yaml
+control:
+  id: SAF-OMNI-001
+  title: "Containment boundary enforcement for high-capability models"
+  props:
+    - name: jurisdiction
+      value: "EU,US,UK,HK,SG"
+    - name: criticality
+      value: "systemic"
+  statements:
+    - id: SAF-OMNI-001_smt
+      description: "All privileged model actions require broker mediation and supervisory quorum."
+  implemented-requirements:
+    - uuid: "impl-saf-omni-001"
+      by-components:
+        - component-uuid: "omni-sentinel-runtime"
+          implementation-status: "implemented"
+```
+
+## 8.2 Rego Policy Example
+
+```rego
+package sentinel.release
+
+default allow = false
+
+allow {
+  input.model.risk_tier == "high"
+  input.controls.saf_omni_001 == true
+  input.controls.sr117_validation_complete == true
+  input.signatures.release_bundle_verified == true
+  input.supervision.quorum >= 2
+}
+```
+
+## 8.3 TLA+ Invariant Skeleton
+
+```tla
+Invariant_NoUnsanctionedAction ==
+  \A a \in Actions :
+    (a.risk = "high") =>
+      (a.policyTokenValid /\ a.supervisoryQuorum >= 2 /\ a.containmentState = "ENFORCED")
+```
+
+## 8.4 zk Proof Statement Metadata (JSON)
+
+```json
+{
+  "proof_id": "zkc-2029-q3-saf-001",
+  "statement": "All high-risk actions satisfied containment and quorum constraints",
+  "circuit": "circom/saf_omni_001.circom",
+  "proving_system": "groth16",
+  "public_inputs": ["period_hash", "policy_root", "event_merkle_root"],
+  "verifier_endpoint": "gc-ir://verifier/saf_omni_001/v2"
+}
+```
+
+## 9. Operating Model and Accountability
+
+- **Board Risk Committee**: approves G-SRI thresholds and exception appetite.
+- **Chief AI Safety Officer**: owns containment and supervisory agent assurance.
+- **Chief Risk Officer / MRM**: owns model lifecycle challenge and SR 11-7 style independence.
+- **CISO / GAI-SOC Lead**: owns telemetry integrity and incident response.
+- **General Counsel / DPO**: owns privacy, cross-border controls, legal hold and disclosures.
+
+RACI should be encoded as machine-readable policy metadata and synchronized with HR role systems.
+
+## 10. Implementation KPIs and KRIs
+
+- Mean time to policy decision (MTPD)
+- Percentage of high-risk actions with dual supervisory approval
+- zk-proof generation success rate and verifier latency
+- TLA+ invariant violation count per release
+- Red Dawn scenario pass rate by attack class
+- G-SRI trend and systemic concentration delta
+
+## 11. Technical Delivery Backlog (First 12 Months)
+
+1. Build canonical control ontology and OSCAL pipeline.
+2. Integrate OPA into deployment gates with signed bundle distribution.
+3. Define TLA+ specs and automated model checking in CI.
+4. Implement Kafka event taxonomy + PQC signature envelope.
+5. Build initial Circom circuits for top systemic controls.
+6. Deploy WORM archive + Merkle notarization jobs.
+7. Launch ASA pilot on privileged tool-use pathways.
+8. Run first Red Dawn full-spectrum simulation and close findings.
+
+## 12. Executive Takeaway
+
+Sentinel AI Governance Stack v2.4 should be treated as a **safety-critical digital control system** rather than a conventional AI governance program. The combination of formal invariants, autonomous supervision, and cryptographic compliance evidence enables durable trust across boards, regulators, and market infrastructures while scaling toward AGI/ASI-era risk.
+
+## 13. Repository Artifact Pack (Implementation Starter)
+
+The following machine-readable starter artifacts are included to accelerate implementation:
+
+- `governance_artifacts/oscal/sentinel_control_catalog_v1.yaml`
+- `governance_artifacts/rego/release_gate.rego`
+- `governance_artifacts/tla/containment_invariants.tla`
+- `governance_artifacts/zk/proof_statement_schema.json`
+- `governance_artifacts/kafka/audit_event_schema.json`
+- `governance_artifacts/regulatory_profiles/eu_ai_act_annex_iv_profile.yaml`
+- `.github/workflows/sentinel-governance-gates.yml`
+
+These are baseline templates intended for adaptation to institution-specific control catalogs, model inventories, and supervisory reporting obligations.