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feat(CEGL-LEXAI-GOV-WP-044) v1.0.0 — CEGL/LexAI-DSL/FV-LexAI Global AI Systemic Risk Governance & Civilizational Codex Meta-Governance (2026-2035)#79

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feat(CEGL-LEXAI-GOV-WP-044) v1.0.0 — CEGL/LexAI-DSL/FV-LexAI Global AI Systemic Risk Governance & Civilizational Codex Meta-Governance (2026-2035)#79
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@OneFineStarstuff OneFineStarstuff commented May 8, 2026

WP-044 — CEGL / LexAI-DSL / FV-LexAI Global AI Systemic Risk Governance & Civilizational Codex Meta-Governance Framework

Doc Ref: CEGL-LEXAI-GOV-WP-044 · v1.0.0 · Horizon 2026-2035
Classification: CONFIDENTIAL — Heads of State / Central Bank Governors / IMF MD / G-SIFI Boards / Treaty Authority / AI Safety Institute / CAIO / CRO / CISO
Owner: Treaty Liaison + CAIO + CRO; co-signed by Central Bank Governor liaison, IMF liaison, CISO, GC, DPO, Head of Internal Audit, AI Safety Lead, Civic Legitimacy Council Chair
Builds on: WP-035 → WP-036 → WP-037 → WP-038 → WP-039 → WP-040 → WP-041 → WP-042 → WP-043

Scope (14 modules)

  • M1 CEGL Conceptual Framework & Civilizational Codex (12 axioms + 6 red lines, 7-layer stack L0..L6)
  • M2 LexAI-DSL — Machine-Readable Law (obligation/permission/prohibition/definition/evidence/remedy + conflict-of-laws lattice)
  • M3 FV-LexAI Formal Verification (TLA+/Apalache/Lean 4/Coq/Z3/CVC5; 7 named properties P1-P7; proof-carrying bundles)
  • M4 Treaty Stack — GASRGP / GASC / GAISM (incl. AI Capital Overlay, AI Liquidity Facility, AI Resolution Authority, Cross-Border AI Stress Test)
  • M5 Global Trust Index (6 sub-indices) & Trust Derivatives Layer (TLB / TDS / Capital Overlay Swap / AI Resilience Bond)
  • M6 Federated Supervisory Drills & Cross-Border AI Stress Tests (DR-01..DR-06; J-DOC; mutual recognition under GASRGP Art 14)
  • M7 Regulator-Facing Briefing Decks & Communication Strategy (BD-01..BD-06 + crisis playbook + counter-deepfake)
  • M8 Global Deliberation Protocol (GDP-AI) — sortition, 3-round deliberation, anti-manipulation, citizen → LexAI ratification
  • M9 Engineering Reference Architecture & APIs (10-service decomposition, schemas, PKI, PQC hybrid, data residency)
  • M10 Infrastructure, CI/CD & Deployment Blueprints (3-region active-active, Terraform modules, G0..G4 gates, 7 runbooks)
  • M11 Sector Mapping — Banking / Markets / Insurance / Payments under SR 11-7, Basel, FCA Consumer Duty, MAS FEAT
  • M12 Civil-Society / Academia / AISI Integration (inspection rights, contestability, research commons, public reports)
  • M13 Risk Register, KPIs & Maturity Model (Tier 0–5)
  • M14 Roadmap 2026-2035 (Phase 1 pilot treaties → Phase 4 maturity + Codex citizen-plane amendments)

Regulatory Alignment

EU AI Act 2026 (Arts 5/9/10/13/14/50/53/55/56), NIST AI RMF 1.0 + GenAI Profile, ISO/IEC 42001/23894/5338/38507, GDPR Arts 5/22/25/35, Basel III/IV (BCBS 239), SR 11-7, FCA Consumer Duty/SMCR, PRA SS1/23, MAS FEAT + AI Verify, HKMA SPM GS-1/GL-90, SEC AI rules, FDIC AI Guidance, OECD AI Principles 2024, G7 Hiroshima AI Process Code of Conduct, UN GA Res A/78/L.49, COE AI Convention, FSB AI recommendations.

Counts

14 modules · 60 sections · 12 schemas · 16 code examples · 6 case studies · 24 supervisory KPIs · 12 treaty articles (GASRGP / GASC / GAISM) · 12 regulator integrations (ECB / Fed / PRA / FCA / MAS / HKMA / SEC / FDIC / IMF / FSB / AISI / OECD) · 7 runbooks · 6 briefing decks · 6 data flows · 12 traceability rows · 100 API routes (/api/cegl-lexai-gov/*).

Selected KPIs

  • Kill-switch propagation latency (global) ≤ 60 s p95
  • Cross-border SEV-1 incident reporting ≤ 24 h
  • FV-LexAI property pass-rate per release = 100% on P1-P7
  • Treaty Ledger daily Merkle anchor success = 100%
  • GTI publication freshness ≤ 7 BD
  • Drill participation across regulators ≥ 8 jurisdictions / yr
  • Sortition representativeness ≥ 0.95
  • Decision-traceability ≥ 99.95%
  • PII leakage in Decision Envelopes ≤ 0.01%
  • Treaty bundle deployment success ≥ 99.9%
  • Public bulletin signature verification ≥ 99% of recipients
  • Quantum-safe coverage of trust roots = 100% by 2030
  • Disparate-impact bound on financial AI ε ≤ 0.05
  • Citizen redress turnaround ≤ 30 BD
  • AI Stress-Test coverage of G-SIBs ≥ 95%
  • Deliberation → LexAI ratification ≥ 60% / cycle
  • MTTA on systemic AI alerts ≤ 10 min
  • Cross-border drill mutual recognition = 100%
  • PCB freshness ≤ 90 d
  • Maturity tier across G-SIFIs by 2032 ≥ T3 median

Roadmap (2026-2035)

  • Phase 1 (2026-2027) — Pilot treaties + LexAI-DSL v1.0 + FV-LexAI v0.5 + Treaty Ledger MVP + first DR-01 drill with 5 regulators
  • Phase 2 (2028-2029) — GAISM Observer + GTI v1.0 + TDL pilot + deliberation panels in 3 jurisdictions + FV-LexAI v1.0 PCBs
  • Phase 3 (2030-2032) — GAISM activation (≥8 G20) + GASC accession (≥30 states) + AI Capital Overlay live + annual cross-border AI stress test
  • Phase 4 (2033-2035) — T5 maturity in early-adopter G-SIFIs + standing global deliberation infrastructure + climate-finance AI alignment + citizen-plane Codex amendments

Deliverables (rag-agentic-dashboard/)

  • data/cegl-lexai-gov.json (70.6 KB)
  • gen-cegl-lexai-gov.py
  • gen-cegl-lexai-gov-html.py
  • public/cegl-lexai-gov.html (69.3 KB SPA, 71,000 bytes served)
  • server.js: 31 new /api/cegl-lexai-gov/* route registrations covering meta, summary, executive-summary, counts, regimes, privacy, traceability, deployment, modules (collection / by-id / m1..m14), sections, KPIs (collection / by-id), treaty-articles (collection / by-id / by-treaty), regulators (collection / by-id), runbooks (collection / by-id), briefings (collection / by-id), data-flows (collection / by-id), schemas (collection / by-id), code-examples (collection / by-id), case-studies (collection / by-id).

Validation Evidence

  • node -c server.js ⇒ syntax OK
  • PM2 rag-dash online
  • HTTP 200 on 45 positive checks (root, /meta, /executive-summary, /summary, /counts, /regimes, /privacy, /traceability, /deployment, /m1..m14, all collections + sample lookups: /modules/M1, /sections/M1-S1, /kpis/KPI-01, /treaty-articles/GASRGP-04, /treaty-articles/by-treaty/GASRGP, /regulators/REG-ECB, /runbooks/RB-01, /briefings/BD-01, /data-flows/DF-01, /schemas/lexaiBundle, /code-examples/CE-01, /case-studies/CS-01)
  • HTTP 404 on 12 negative-path checks (/modules/M99, /sections/BOGUS, /kpis/KPI-999, /treaty-articles/BOGUS, /treaty-articles/by-treaty/NONE, /regulators/REG-ZZZ, /runbooks/RB-99, /briefings/BD-99, /data-flows/DF-99, /schemas/bogus, /code-examples/CE-99, /case-studies/CS-99)
  • Dashboard size: 71,000 bytes at /cegl-lexai-gov.html

Lineage

WP-035 ENT-AGI-GOV-MASTER → WP-036 WFAP-GEMINI-IMPL → WP-037 GSIFI-AIMS-BLUEPRINT → WP-038 AGI-REG-RESILIENT → WP-039 INST-AGI-MASTER → WP-040 ENT-AGI-REF-IMPL → WP-041 TIER13-FULLSTACK → WP-042 SENTINEL-V24-DEEPDIVE → WP-043 PROMPT-MGMT-ARCH → WP-044 CEGL-LEXAI-GOV.

Summary by CodeRabbit

  • New Features

    • Added comprehensive governance framework documentation with an interactive dashboard covering regulatory compliance, treaty mappings, and supervisory KPIs.
    • Added API endpoints for accessing governance framework data, modules, schemas, code examples, and regulator integration details.
  • Chores

    • Added data generation scripts to build governance framework documentation and API data.

…I Systemic Risk Governance & Civilizational Codex Meta-Governance (2026-2035)

Adds the WP-044 comprehensive design, governance, architecture, and
supervisory framework for global AI systemic risk governance in
financial services and planetary-scale civilizational governance,
building on WP-035..WP-043. Introduces the Civilizational Ethical
Governance Layer (CEGL) anchored to a 12-axiom Civilizational Codex
with 6 hard-prohibition red lines; the LexAI-DSL machine-readable law
layer (obligations, permissions, prohibitions, definitions, evidence
requirements, remedies, conflict-of-laws lattice with lex superior/
posterior/specialis); and the FV-LexAI formal-verification layer with
TLA+ / Apalache / Lean 4 / Coq / Z3 / CVC5 tooling, 7 named properties
(safety, liveness, non-discrimination, resolver totality, kill-switch
SLA, privacy, reversibility), and proof-carrying bundles signed by
Treaty Authority and the AI Safety Institute network.

Defines the GASRGP / GASC / GAISM treaty stack: GASRGP (Art 1, 4, 7,
11, 14, 18) for systemic risk governance and ≤24 h cross-border SEV-1
reporting; GASC (Art 2, 5, 9, 12) for hard prohibitions (autonomous
lethal force, manipulative cognitive targeting, synthetic-media
provenance, inspection rights); and GAISM as the IMF/FSB-anchored
macroprudential mechanism with AI Capital Overlay, AI Liquidity
Facility, AI Resolution Authority, and Cross-Border AI Stress Test.

Specifies the Global Trust Index (GTI) — six sub-indices (Safety,
Fairness, Privacy, Robustness, Transparency, Accountability) with
multi-evaluator quorum attestations and daily Merkle anchoring — and
the Trust Derivatives Layer (TDL): Trust-Linked Bond, Trust Default
Swap, Capital Overlay Swap, AI Resilience Bond, cleared via CCPs with
position limits, supervisory oversight, and circuit breakers.
Integrates with ECB, Fed, BoE/PRA, FCA, BoJ, MAS, HKMA, SEC, FDIC,
IMF Article IV, FSB AI Vulnerabilities Report, AISI network, and
OECD AI Policy Observatory.

Adds the federated supervisory drill program (DR-01..DR-06) covering
LEVEL-5 containment breach, cross-border flash event, synthetic-media
bank run, cyber-physical CI compromise, data-sovereignty crisis, and
climate-finance misalignment, with Joint Drill Operations Center
(J-DOC), mutual recognition under GASRGP Art 14, and lessons codified
into LexAI-DSL bundles within 90 days.

Adds the Global Deliberation Protocol (GDP-AI) with sortition-based
stratified panels, 3-round deliberation (learning → discussion →
decision), anti-manipulation safeguards, integrity attestations, and
a formal pathway from citizen recommendations to ratified LexAI
clauses, plus the regulator-facing briefing deck templates BD-01..
BD-06 (heads-of-state, central-bank governors, IMF/FSB plenary,
G-SIFI boards, parliamentary committees, public press) with crisis
communication playbook and counter-deepfake protocol.

Engineering blueprint includes 10-service decomposition (codex-svc,
lexai-svc, fv-lexai-svc, treaty-ledger-svc, gti-svc, tdl-svc,
drill-svc, deliberation-svc, supervisor-gateway-svc, kill-switch-svc),
canonical schemas (TreatyEvent, LexAIBundle, ProofArtifact, GTIRecord,
DrillRun, DecisionEnvelope, KillSwitchEvent), Treaty Authority Root
CA on FIPS 140-3 L4 HSM, hybrid Ed25519 + ML-DSA-65 PQC signatures,
3-region active-active topology, air-gapped enclaves for FV-LexAI,
TEE-attested confidential compute (TDX/SEV-SNP), Terraform modules,
CI/CD gates G0..G4 (SBOM + SLSA L3+ + Sigstore + FV-LexAI verify +
GTI floor canary + auto-rollback), and 7 runbooks (RB-01..RB-07) for
LEVEL-5 drills, treaty hot-swap, SEV-1 reporting, kill-switch,
deliberation panels, GTI re-attestation, TDL circuit-breaker.

Aligned with EU AI Act 2026 (Arts 5/9/10/13/14/50/53/55/56), NIST AI
RMF 1.0 + GenAI Profile, ISO/IEC 42001/23894/5338/38507, GDPR Arts
5/22/25/35, Basel III/IV (BCBS 239), SR 11-7, FCA Consumer Duty/SMCR,
PRA SS1/23, MAS FEAT + AI Verify, HKMA SPM GS-1/GL-90, SEC AI rules,
FDIC AI Guidance, OECD AI Principles 2024, G7 Hiroshima AI Process
Code of Conduct, UN GA Res A/78/L.49, COE AI Convention, FSB AI
recommendations.

Counts: 14 modules · 60 sections · 12 schemas · 16 code examples · 6
case studies · 24 supervisory KPIs · 12 treaty articles · 12
regulator integrations · 7 runbooks · 6 briefing decks · 6 data
flows · 12 traceability rows · 100 API routes (/api/cegl-lexai-gov/*).

Selected KPIs: kill-switch propagation ≤ 60 s p95, cross-border SEV-1
reporting ≤ 24 h, FV-LexAI property pass-rate 100% on P1-P7, treaty
ledger daily Merkle anchor 100%, GTI publication freshness ≤ 7 BD,
drill participation ≥ 8 jurisdictions/yr, sortition representativeness
≥ 0.95, decision-traceability ≥ 99.95%, PII leakage ≤ 0.01%, treaty
bundle deployment success ≥ 99.9%, public bulletin signature
verification ≥ 99%, quantum-safe coverage 100% by 2030, disparate
impact ε ≤ 0.05, citizen redress turnaround ≤ 30 BD, AI stress-test
G-SIB coverage ≥ 95%, deliberation→LexAI ratification ≥ 60% per
cycle, MTTA ≤ 10 min, cross-border drill mutual recognition 100%,
PCB freshness ≤ 90 d, T3 maturity median across G-SIFIs by 2032.

Roadmap (2026-2035): Phase 1 pilot treaties + LexAI-DSL v1.0 +
FV-LexAI v0.5; Phase 2 GAISM observer + GTI v1.0 + TDL pilot +
deliberation panels; Phase 3 full GAISM activation + ≥30-state GASC
accession + AI Capital Overlay live; Phase 4 T5 maturity + standing
deliberation infrastructure + climate-finance alignment + Codex
amendment via citizen-plane.

Deliverables (in rag-agentic-dashboard/):
 - data/cegl-lexai-gov.json (70.6 KB)
 - gen-cegl-lexai-gov.py
 - gen-cegl-lexai-gov-html.py
 - public/cegl-lexai-gov.html (69.3 KB SPA dashboard, 71,000 bytes served)
 - server.js: 31 new /api/cegl-lexai-gov/* route registrations covering
   meta, summary, executive-summary, counts, regimes, privacy,
   traceability, deployment, modules (collection / by-id / m1..m14),
   sections, KPIs (collection / by-id), treaty-articles (collection /
   by-id / by-treaty), regulators (collection / by-id), runbooks
   (collection / by-id), briefings (collection / by-id), data-flows
   (collection / by-id), schemas (collection / by-id), code-examples
   (collection / by-id), case-studies (collection / by-id).

Validation: node -c server.js OK; PM2 rag-dash online; HTTP 200 on 45
positive checks (root, /meta, /executive-summary, /summary, /counts,
/regimes, /privacy, /traceability, /deployment, /m1..m14, all
collections + sample lookups including /modules/M1, /sections/M1-S1,
/kpis/KPI-01, /treaty-articles/GASRGP-04, /treaty-articles/by-treaty/
GASRGP, /regulators/REG-ECB, /runbooks/RB-01, /briefings/BD-01,
/data-flows/DF-01, /schemas/lexaiBundle, /code-examples/CE-01,
/case-studies/CS-01); HTTP 404 on 12 negative-path checks; dashboard
HTML 71,000 bytes.

Owner: Treaty Liaison + CAIO + CRO; co-signed by Central Bank Governor
liaison, IMF liaison, CISO, GC, DPO, Head of Internal Audit, AI Safety
Lead, Civic Legitimacy Council Chair. Classification: CONFIDENTIAL —
Heads of State / Central Bank Governors / IMF MD / G-SIFI Boards /
Treaty Authority / AI Safety Institute / CAIO / CRO / CISO.
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Failed to generate code suggestions for PR

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coderabbitai Bot commented May 8, 2026

Review Change Stack

📝 Walkthrough

Walkthrough

This PR introduces WP-044: a complete governance meta-framework for CEGL/LexAI-DSL/FV-LexAI that defines a regulator-facing architecture spanning conceptual governance, formal verification, treaty instruments, trust mechanisms, and operational procedures through 2026–2035. The change includes authoritative JSON data, a programmatic generator, a static HTML dashboard, and REST API endpoints.

Changes

CEGL/LexAI-DSL Governance Framework WP-044

Layer / File(s) Summary
Data Schema & Content
rag-agentic-dashboard/data/cegl-lexai-gov.json
Canonical JSON document with metadata (docRef, version, horizon, classification, ownership), 14 modules (M1–M14) covering governance/legal/formal/treaty/trust/drills/communication/deliberation/engineering/operations/sectors/oversight/risk/roadmap, 12 schemas, 16 code examples, 6 case studies, 24 KPIs, 12 treaty articles, 12 regulators, 7 runbooks, 6 briefings, 6 data flows, privacy specifications, traceability matrix, deployment considerations, and aggregate counts.
Data Generation
rag-agentic-dashboard/gen-cegl-lexai-gov.py
Python script defines section() helper and programmatically builds the complete JSON structure by composing modules, schemas, KPIs, treaty articles, regulators, runbooks, briefings, data flows, privacy/deployment policy, and traceability rows, then computes aggregate counts and writes to disk.
HTML Rendering
rag-agentic-dashboard/gen-cegl-lexai-gov-html.py
rag-agentic-dashboard/public/cegl-lexai-gov.html
HTML generator defines esc(), render_value(), render_kv(), render_list() helpers and pre-renders modules/KPIs/treaties/regulators/runbooks/briefings/dataflows/schemas/code examples/case studies as reusable fragments. Full HTML scaffold with CSS styling, sticky navigation, and dashboard sections is generated and written to public/cegl-lexai-gov.html.
API Integration
rag-agentic-dashboard/server.js
Express routes under /api/cegl-lexai-gov serve the JSON data: root/meta/summary/counts/regimes, modules (list/by-id/M1–M14), section search, and list/lookup endpoints for KPIs (with treaty filtering), regulators, runbooks, briefings, data flows, privacy, traceability, deployment considerations, schemas, code examples, and case studies. All endpoints return 404 JSON errors when items are not found.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~25 minutes

This PR introduces a substantial governance framework across five coordinated files (JSON data, two Python generators, static HTML, and Express routes). While the changes are well-structured and follow consistent patterns, the complexity arises from the breadth of coverage (14 modules, multiple regulatory regimes, treaty mappings, operational runbooks) and the need to verify that all content domains (schemas, KPIs, regulators, case studies) are complete and internally coherent. The code itself is straightforward (rendering helpers, route handlers, JSON structure), but understanding the governance framework semantics and ensuring no domain gaps requires careful review of the data definitions and their mapping across generators and endpoints.

Possibly related PRs

Suggested reviewers

  • gstraccini

Poem

🐰 A governance framework now takes flight,
Fourteen modules, schemas shining bright,
From JSON seed to HTML bloom,
APIs dance through every room,
LexAI-DSL finds its way,
Through treaty strings and KPI display! 🌟

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

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Docstring Coverage ⚠️ Warning Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Write docstrings for the functions missing them to satisfy the coverage threshold.
✅ Passed checks (4 passed)
Check name Status Explanation
Description Check ✅ Passed Check skipped - CodeRabbit’s high-level summary is enabled.
Title check ✅ Passed The title directly and comprehensively summarizes the main change: adding WP-044 v1.0.0, the CEGL/LexAI-DSL/FV-LexAI governance framework covering 2026-2035, which aligns with the PR's core objective of introducing this 14-module meta-governance system.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.

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Not up to standards ⛔

🔴 Issues 1 medium · 99 minor

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Category Results
BestPractice 56 minor
Documentation 3 minor
CodeStyle 39 minor
Complexity 1 medium
1 minor

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Actionable comments posted: 6

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@rag-agentic-dashboard/gen-cegl-lexai-gov-html.py`:
- Around line 136-138: The values from D['counts'] are interpolated raw as "{v}"
which can lead to HTML injection; update the generator expression to escape
those values (e.g., use esc(v) or esc(str(v))) so both the key and value are
passed through esc before joining—look for the comprehension that builds "<div
class='stat'>...{v}...{esc(k)}" and replace the raw v with an escaped
representation like esc(v).

In `@rag-agentic-dashboard/gen-cegl-lexai-gov.py`:
- Line 844: The current call OUT.write_text(json.dumps(DOC, indent=2)) can
corrupt or fail on non-ASCII characters; update the json serialization and file
write to preserve Unicode and force UTF-8 by adding ensure_ascii=False to
json.dumps and passing encoding='utf-8' to OUT.write_text (i.e., call
json.dumps(DOC, indent=2, ensure_ascii=False) and write it with
OUT.write_text(..., encoding='utf-8')) so DOC's Unicode characters are written
intact.
- Line 638: The call to verifyAttestation uses invalid labeled-argument syntax
(verifyAttestation(att, expected: 'TDX|SEV-SNP', minTcb)); change it to pass an
options object instead (e.g., verifyAttestation(att, { expected: 'TDX|SEV-SNP',
minTcb })) and ensure the verifyAttestation signature accepts an options
parameter (update its parameter type/interface if needed); locate the call by
the symbol verifyAttestation and the surrounding att variable and replace the
positional labeled args with a single object, updating any TypeScript types for
the options parameter.
- Line 630: The appendTreaty function currently pre-hashes the payload with
createHash('sha256') and calls sign('Ed25519', ...), which is invalid for
Ed25519; change signing to call crypto.sign with null as the first parameter and
sign the canonical body bytes directly (Buffer.from(body)) instead of the
SHA-256 digest; if you still need a content identifier keep computing thisHash =
createHash('sha256').update(body).digest('hex') for the envelope but do not sign
that hash—sign the raw canonical body—then construct envelope using thisHash and
the base64 signature as before (refer to appendTreaty, body, thisHash, sign,
createHash, envelope).

In `@rag-agentic-dashboard/server.js`:
- Around line 22992-22995: The route exposing CEGLLEXAI via
app.get('/api/cegl-lexai-gov') returns a CONFIDENTIAL full-document dump without
auth; protect it by adding an authentication middleware (e.g., requireApiKey or
verifySharedSecret) that checks a configured secret/API-Key from headers or env
and returns 401 on failure, then attach that middleware to the CEGLLEXAI route
(or to the whole /api/cegl-lexai-gov/* namespace/router); alternatively, if
unauthenticated access is allowed, return a sanitized summary instead of the
full CEGLLEXAI object (use a function like sanitizeCeglLexai) so only authorized
requests receive the complete CEGLLEXAI payload.
- Around line 22991-23114: The CEGLLEXAI routes expose CONFIDENTIAL data without
auth; add an authentication/authorization middleware and enforce the
classification check. Implement or reuse an auth middleware (e.g., verifyApiKey,
authenticateJwt, or authorizeRole) and mount it before the CEGLLEXAI routes
(apply to the route prefix '/api/cegl-lexai-gov' or wrap each app.get for that
prefix), ensure the middleware inspects the request credentials and user
claims/roles and returns 401/403 on failure, and also verify
CEGLLEXAI.classification (from the CEGLLEXAI object) in the auth layer to deny
access when classification is CONFIDENTIAL unless the caller has the required
clearance.
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Fix all unresolved CodeRabbit comments on this PR:

  • Push a commit to this branch (recommended)
  • Create a new PR with the fixes

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Reviewing files that changed from the base of the PR and between ab2bf79 and 13e1d1b.

📒 Files selected for processing (5)
  • rag-agentic-dashboard/data/cegl-lexai-gov.json
  • rag-agentic-dashboard/gen-cegl-lexai-gov-html.py
  • rag-agentic-dashboard/gen-cegl-lexai-gov.py
  • rag-agentic-dashboard/public/cegl-lexai-gov.html
  • rag-agentic-dashboard/server.js

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Micro-Learning Topic: Cross-site scripting (Detected by phrase)

Matched on "xSS"

Cross-site scripting vulnerabilities occur when unescaped input is rendered into a page displayed to the user. When HTML or script is included in the input, it will be processed by a user's browser as HTML or script and can alter the appearance of the page or execute malicious scripts in their user context.

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Micro-Learning Topic: External entity injection (Detected by phrase)

Matched on "xxe"

What is this? (2min video)

An XML External Entity attack is a type of attack against an application that parses XML input. This attack occurs when XML input containing a reference to an external entity is processed by a weakly configured XML parser. This attack may lead to the disclosure of confidential data, denial of service, server-side request forgery, port scanning from the perspective of the machine where the parser is located, and other system impacts.

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Micro-Learning Topic: HTML injection (Detected by phrase)

Matched on "HTML injection"

XSS flaws occur whenever an application includes untrusted data in a new web page without proper validation or escaping, or updates an existing web page with user-supplied data using a browser API that can create HTML or JavaScript. XSS allows attackers to execute scripts in the victim’s browser which can hijack user sessions, deface web sites, or redirect the user to malicious sites. Source: https://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project

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