AI GOVERNANCE & SECURITY ASSESSMENT

Blaze Platform:
AI Governance &
Security Assessment

Enterprise governance-as-code for regulated organizations. Evidence-first compliance across 16 regulatory frameworks. 54 risks analyzed, 41 controls deployed, 33 governance documents, 9-stage SAST+DAST security battery.

Governance-as-Code for Regulated Enterprises

Blaze produces compliance evidence as a first-class output of every workflow. The platform maps to whatever regulatory obligations each customer has — not just AI-specific regulations.

This assessment serves three audiences: the CISO (security controls and scan battery), the Chief Compliance Officer (evidence-first compliance across all regulatory obligations), and the AI Governance Board (ISO 42001 AIMS and responsible AI). What follows is a 4-phase analysis: standard risk identification, adversarial 4-agent review, synthetic CISO stress test, and adversarial challenge with full remediation.

Four-Phase Methodology

PHASE 1

Standard Risk Analysis

Systematic identification of 45 risks across data sovereignty, access control, compliance, and operational categories using enterprise risk frameworks.

45 risks identified

PHASE 2

Adversarial 4-Agent Review

Four specialized security agents performed independent adversarial analysis, discovering 9 additional risks invisible to standard frameworks.

9 additional risks surfaced

PHASE 3

Synthetic CISO Construct

The most demanding CISO persona possible — financial services + healthcare, zero tolerance — 10 policy demands mapped to deployed controls.

10 demands satisfied

PHASE 4

Adversarial Challenge

Three agents found 37 gaps. 33 governance documents written. 4 CISO blockers resolved. 16 regulatory frameworks mapped. All before this meeting.

37 gaps closed (33 complete, 4 post-pilot)

Assessment at a Glance

STRONG

Technical Controls

41 hooks, 513 tests (37 suites), 62 agents, 9-stage SAST+DAST battery, fail-closed gates

COMPLETE

Governance Documentation

33 governance docs deployed, all 4 CISO blockers resolved, all processes documented

COMPLETE

Regulatory Frameworks

16 frameworks mapped; extensible to any framework the customer operates under

ESTABLISHED

Process Maturity

AI ethics charter, IR playbook, model validation, training curriculum all in place

Risk Disposition

54 Total Risks
76% — Remediated with deployed controls (41)
13% — Resolvable via Bedrock/Vertex migration (7)
7% — Structurally irreducible, documented (4)
4% — Accepted at low severity (2)

The Synthetic CISO Construct

Dr. Sarah Chen, CISSP, CISM, CRISC

Background: 20 years leading security teams across financial services and healthcare — the two most regulated industries. Former CISO at a top-10 US bank. Board advisor for HIPAA-covered entities.

Philosophy: Zero tolerance for shadow IT. 6-month minimum evaluation. Vendor questionnaires, penetration tests, and regulatory mapping completed before any pilot.

Required Frameworks: SOC 2, HIPAA, GDPR, NIST 800-53, ISO 27001, FedRAMP, PCI DSS, CCPA, EU AI Act, OWASP — all mapped before tool adoption.

MOST CONSERVATIVE
CISO IMAGINABLE
CISSP CISM CRISC 20yr FinServ Healthcare

Dr. Chen's 10 Non-Negotiable Demands

Dr. Chen's Verdict

The technical control architecture is genuinely impressive. What sets this apart is the completed governance layer: 33 governance documents, DPIA with DPO sign-off, vendor security questionnaire, formal risk acceptance, BCP, AI ethics charter, IR playbook, model validation program, and 16 regulatory framework mappings.

Recommendation: Approve for immediate pilot deployment with 5 core users, standard monitoring cadence (monthly evidence review, quarterly re-assessment).

Compliance Evidence Is a First-Class Output, Not an Afterthought

Blaze is not an AI governance tool. It is a governance-as-code platform for regulated enterprises. AI governance is one important capability among many.

Every workflow on the platform produces structured, auditable compliance evidence. That evidence maps to whatever regulatory framework the customer operates under — financial services, healthcare, government, EU, or any combination. The 16 frameworks currently mapped are a starting set. The architecture supports any framework.

Compliance-Driven Development (CDD)

Evidence collection is built into every SDLC phase

Phase 1: Strategic Intelligence
Phase 2: Development
Phase 3: Deployment
Phase 4: PR Review + Attestation

At every phase, the CDD methodology agent collects structured JSON evidence with SHA-256 integrity hashing, collector identity, timestamps, and work-item linkage. This evidence chain maps to ANY regulatory framework — not just AI regulations.

The Evidence Chain Maps to Any Framework

Financial Services Customer

Same evidence chain, mapped to:

SOC 2 Type II DORA SR 11-7 PCI DSS NIST 800-53

Bank CISO reaches for SR 11-7 first when evaluating AI tools. Already mapped.

Healthcare Customer

Same evidence chain, mapped to:

HIPAA FDA ISO 27001 SOC 2

BAA available with Enterprise + ZDR. DPIA completed with DPO sign-off block.

Government Customer

Same evidence chain, mapped to:

FedRAMP NIST 800-53 NIST AI RMF NIST AI 600-1

Bedrock/Vertex deployment provides data residency guarantees for GovCloud.

EU Customer

Same evidence chain, mapped to:

GDPR EU AI Act NIS2 DORA ISO 42001

Full EU AI Act risk classification and Art. 4 AI literacy analysis completed.

Governance-as-Code

Policies Are Code

Security policies, SDLC gates, and compliance rules are enforced by executable hooks and agents — not PDF documents. They are version-controlled, testable, and auditable.

Controls Are Tested

513 hook+script tests across 37 suites validate the security control layer. 3,014 total platform tests. Every control has a corresponding test. Meta-regression ensures no hook lacks a test file.

Evidence Is Structured

JSON evidence with sort_keys, SHA-256 hashing, timestamps in ISO 8601 UTC. Machine-readable for automated compliance reporting. Human-readable for auditor review.

The Governance Bridge: 21 Controls x 16 Frameworks

The governance-bridge skill provides machine-readable mappings from every deployed control to every regulatory framework. This is the starting set for Claude Code adoption. The same architecture maps to any framework a customer requires.

SOC 2 GDPR HIPAA NIST 800-53 ISO 27001 FedRAMP PCI DSS CCPA EU AI Act OWASP ISO 42001 DORA SR 11-7 ISO 23894 NIST AI 600-1 NIST AI RMF

Extensible architecture: new frameworks are added by mapping controls to requirements. No re-engineering required.

Key Differentiator

The same governance architecture that secures Claude Code adoption produces compliance evidence for every solution built on the platform. A financial services customer deploying a COBOL migration solution gets SOC 2 + DORA + SR 11-7 evidence as a byproduct of normal development workflow — not as a separate compliance project.

Commercial Terms — What the License Provides

Under Anthropic's Commercial Terms of Service (Team, Enterprise, API), several risks identified for consumer plans are already resolved by the license itself.

No Training on Customer Content

"Anthropic may not train models on Customer Content from Services." Eliminates training opt-in risk.

Data Processing Addendum (DPA)

Incorporated by reference into all commercial agreements. GDPR-compliant data processing guarantees.

Zero Data Retention (Enterprise)

Prompts and responses not stored after response returned. Safety violations retained up to 2 years (industry standard).

BAA for Healthcare (Enterprise + ZDR)

Business Associate Agreements extend to Claude Code for Enterprise customers with ZDR enabled.

Telemetry Defaults by API Provider

ServiceClaude APIBedrock / Vertex / Foundry
Statsig (Metrics)ON by defaultOFF by default
Sentry (Errors)ON by defaultOFF by default
Feedback (/feedback)ON by defaultOFF by default
Session SurveysON by defaultON by default

Disable all non-essential traffic: CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

All 54 Risks — Status at a Glance

45 risks from the initial analysis + 9 from adversarial 4-agent review. 41 remediated with deployed controls. 7 require Bedrock/Vertex. 4 structurally irreducible. 2 accepted at low severity.

41 Remediated — Controls Deployed & Tested
7 Irreducible on Direct API — Requires Bedrock/Vertex
4 Structurally Irreducible — Documented
2 Accepted — Low Severity
#RiskCategoryStatus
1Arbitrary command executionCommand ExecutionREMEDIATED
2File system modification without reviewCode IntegrityREMEDIATED
3Unauthorized package installationSupply ChainREMEDIATED
4Sensitive data in prompts/contextData ClassificationREMEDIATED
5Credential exposure via tool outputCredential ProtectionREMEDIATED
6Environment variable leakageCredential ProtectionREMEDIATED
7Git history credential miningCredential ProtectionREMEDIATED
8SSH key exposureCredential ProtectionREMEDIATED
9API key in generated codeCode IntegrityREMEDIATED
10MCP server data exfiltrationMCP SecurityREMEDIATED
11Unauthorized MCP server connectionAccess ControlREMEDIATED
12Shadow IT tool usageAcceptable UseREMEDIATED
13Insufficient authenticationAccess ControlREMEDIATED
14Offboarding gapIdentityREMEDIATED
15PII/PHI in AI contextData ClassificationREMEDIATED
16Uncontrolled code generation patternsCode IntegrityREMEDIATED
17Domain boundary violationAccess ControlREMEDIATED
18Multi-tenant isolation breachAccess ControlREMEDIATED
19Destructive git operationsIncident ResponseREMEDIATED
20Base64 encoded secrets bypassData ClassificationREMEDIATED
21Project file injectionProject IntegrityREMEDIATED
22Stuck agent escalation failureIncident ResponseREMEDIATED
23Prompt injection via code commentsMCP SecurityREMEDIATED
24MCP SSRF attacksThird-Party RiskREMEDIATED
25MCP command injectionThird-Party RiskREMEDIATED
26MCP schema poisoningThird-Party RiskREMEDIATED
27MCP tool shadowingThird-Party RiskREMEDIATED
28MCP credential relayThird-Party RiskREMEDIATED
29MCP data exfiltration via DNSThird-Party RiskREMEDIATED
30Insufficient audit granularityAudit TrailREMEDIATED
31Privacy settings bypassData ClassificationREMEDIATED
32Evidence tamperingAudit TrailREMEDIATED
33MCP data flow opacityAudit TrailREMEDIATED
34Bypass audit loggingAudit TrailREMEDIATED
35Governance config tamperingModel GovernanceREMEDIATED
36Unauthorized protected file editIncident ResponseREMEDIATED
37Unreviewed code mergeChange ManagementREMEDIATED
38SDLC phase bypassChange ManagementREMEDIATED
39Insufficient test coverage mergeChange ManagementREMEDIATED
40Non-compliant code patternsAcceptable UseREMEDIATED
41Unmapped regulatory controlsRegulatoryREMEDIATED
42Missing compliance evidenceChange ManagementREMEDIATED
43Data residency violationData SovereigntyBEDROCK/VERTEX
44Cross-border data transferData SovereigntyBEDROCK/VERTEX
45Training data contaminationData SovereigntyBEDROCK/VERTEX
46Model behavior driftModel GovernanceIRREDUCIBLE
47Context window exhaustionModel GovernanceACCEPTED
48Hook timeout exploitationModel GovernanceIRREDUCIBLE
49VPC endpoint unavailabilityData SovereigntyBEDROCK/VERTEX
50Token cost attacksOperationalACCEPTED
51Same-principal trust paradoxArchitectureIRREDUCIBLE
52Evidence integrity (insider)Audit TrailIRREDUCIBLE
53Worktree isolation failuresArchitectureREMEDIATED
54Credential file Read bypassData ClassificationREMEDIATED
REMEDIATED — Control deployed and tested (41) BEDROCK/VERTEX — Resolvable via API migration (7) IRREDUCIBLE — Structurally impossible to eliminate (4) ACCEPTED — Low severity, documented (2)

9-Stage Security Scan Battery

Deterministic scan battery runs on every PR. Any finding blocks merge. Achieves Burp Suite equivalence through open-source portfolio.

SAST 1

Semgrep

17 custom rules. OWASP Top 10, secrets detection, Blaze-specific patterns.

SAST 2

Bandit

Python security linter. SQL injection, command injection, insecure deserialization.

SAST 3

ESLint Security

JS/TS security rules. Prototype pollution, regex DoS, unsafe eval, DOM XSS.

SAST 4

TruffleHog

800+ secret detectors across git history and current files.

SAST 5

pip-audit

Python dependency CVE scanner against PyPI advisory database.

SAST 6

npm audit

Node.js dependency vulnerability scanner with severity thresholds.

DAST 1

Security Headers

Live endpoint checks: HSTS, CSP, X-Frame-Options, X-Content-Type-Options.

DAST 2

Nuclei

7,000+ community templates for CVEs, misconfigurations, default credentials.

DAST 3

OWASP ZAP

Active XSS, SQL injection, CSRF, path traversal scanning. Burp equivalent.

On-Demand: Extended Capabilities

ffuf HTTP fuzzing. CVE reachability analysis. kube-bench CIS benchmarks. Conftest/OPA Terraform policy-as-code. Syft SBOM generation. Canarytokens deception detection.

Governance Completeness — 33 Documents

Adversarial review identified 37 gaps. 33 closed with substantive documents. 4 remaining are execution-phase items that begin after pilot.

CISO Blockers — All Resolved 4/4

COMPLETED

DPIA / Privacy Impact Assessment

docs/governance/dpia-claude-code.md. GDPR Art. 35 with DPO sign-off.

COMPLETED

Vendor Security Questionnaire

docs/governance/vendor-assessment-anthropic.md. Tier 1 Approved.

COMPLETED

Formal Risk Acceptance Sign-Off

docs/governance/risk-acceptance-signoff.md. 4 executive signatures.

COMPLETED

Business Continuity Plan

docs/governance/bcp-ai-tooling.md. 4 impact scenarios.

Governance Processes ALL ESTABLISHED

COMPLETED

AI Ethics Charter

docs/governance/ai-ethics-charter.md. Scope, authority, decision framework.

COMPLETED

AI Incident Response Playbook

docs/governance/ai-incident-response-playbook.md. Severity levels, SLAs.

COMPLETED

Model Validation Program

docs/governance/model-validation-program.md. Golden test suite, SR 11-7 aligned.

COMPLETED

Employee AI Training Program

docs/governance/ai-training-curriculum.md. 8 modules, EU AI Act Art. 4.

CategoryGapsRemainingStatus
CISO Blockers40ALL RESOLVED
Frameworks6016/16 MAPPED
Risk Policies80ALL DOCUMENTED
Evidence52POST-PILOT
Processes40ALL ESTABLISHED
Total374 (non-blocking)33 closed

Regulatory Framework Crosswalk

16 frameworks mapped to 21 deployed controls. The starting set for Claude Code — the same architecture maps to any framework a customer requires.

CISO DemandRisksControls DeployedFrameworks
Data Classification#4 #15 #20 #54data-classification-gate.sh, .env blocker, privacy-settings-gate.jsSOC2 CC6.1 GDPR Art.9 HIPAA 164.312 NIST SC-28
Access Control#11 #13 #14 #17identity-enforcement-gate.sh, pre-edit-validation.sh, worktree enforcementSOC2 CC6.2 GDPR Art.32 HIPAA 164.312(d) NIST AC-2
Audit Trail#30 #32 #33 #34evidence-generator.py, mcp-data-flow-logger.js, CDD phasesSOC2 CC7.2 GDPR Art.30 HIPAA 164.312(b) NIST AU-2
Third-Party Risk#24-#29mcp-security-gate.js, approved-mcp-servers.yamlSOC2 CC6.6 GDPR Art.28 HIPAA 164.308(b) NIST AC-4
Incident Response#19 #22 #36block-destructive-commands.sh, stuck-detector.js, deviation-rules.mdSOC2 CC7.4 GDPR Art.33 HIPAA 164.308(a)(6) NIST IR-4
Change Management#37 #38 #39 #42unified-sdlc-enforcement, pr-orchestrator, testing-gatesSOC2 CC8.1 GDPR Art.25 NIST CM-3 DORA Art.9
Model Governance#35 #46 #48policy-change-detector.js, project-integrity-scanner.jsISO 42001 6.1 EU AI Act Art.9 NIST AI RMF SR 11-7
Regulatory Mapping#41governance-bridge skill16 frameworks mapped

Framework Expansion — All Mapped

MAPPED

ISO/IEC 42001:2023

THE AI management system standard. Fully mapped to deployed controls.

MAPPED

DORA

ICT risk management, incident reporting. EU FinServ enablement.

MAPPED

SR 11-7 / OCC 2011-12

US banking model risk management. First framework a bank CISO reaches for.

MAPPED

ISO/IEC 23894

AI-specific risk management. ISO 31000-aligned guidance.

MAPPED

NIST AI 600-1

GenAI risk profile. Confabulation, data privacy, information integrity.

MAPPED

EU AI Act (Deep)

Full risk classification, provider/deployer analysis, Art. 4 AI literacy.

Evidence Portfolio

A CISO does not accept claims — they accept evidence. Every control has corresponding artifacts that can be independently verified.

What Your CISO Isn't Thinking About (But We Are)

Counterfactual, adversarial, and second-order thinking to surface risks beyond standard frameworks. Nine additional risks from the adversarial 4-agent review.

Counterfactual

What if the AI model changes behavior silently?

Risk #46: Model Behavior Drift — Anthropic updates Claude without notice. Controls that work today may be ignored tomorrow.

Response: policy-change-detector.js monitors terms. project-integrity-scanner.js detects config tampering. Multi-agent review catches drift. IRREDUCIBLE

Blind Spot

What if the governance layer IS the attack surface?

Risk #48 + #21 — Hook timeout exploitation and config file injection.

Response: Explicit timeouts on all 41 hooks. Fail-closed on critical hooks. 12-file integrity baseline. pre-edit-validation.sh blocks edits on main.

Second-Order

What if the evidence system itself is compromised?

Risk #52: Evidence Integrity — CDD hashes stored alongside evidence. An insider could alter both.

Response: SHA-256 + git history + multi-phase cross-referencing. True fix requires RFC 3161 TSA. ACCEPTED

Adversarial

What if a trusted insider weaponizes the AI agent?

Risk #51: Same-Principal Trust — The AI agent enforcing security runs with same privileges as the user.

Response: Multi-agent review (9+), multi-AI consensus (3-of-4 models), identity enforcement independent of model. IRREDUCIBLE

Temporal

What if controls break after a model update?

Risk #46 + #47 — Model drift + context window exhaustion.

Response: Pre/post-compact snapshot hooks. CLAUDE.md reloaded every session. Hooks are shell/JS, independent of model. Quarterly re-validation.

4 Honest Irreducible Risks

Fundamental constraints of the Claude Code architecture. Cannot be eliminated — only documented, monitored, and mitigated through defense-in-depth.

#RiskMitigation StrategySeverity
46Model behavior drift — governance layer assumes Claude honors system prompts. A model update could change interpretation.Monitor Anthropic releases; re-validate controls after each update. Defense-in-depth.HIGH
48Hook timeout exploitation — 5-second fail-open timeout. Crafted inputs could bypass hooks.Explicit timeouts (3s-10s). Hooks designed fast (<100ms typical).HIGH
51Same-principal trust — no privilege separation between enforcement and execution.Multi-agent review (9+) and multi-AI consensus (3-of-4) provide partial separation.HIGH
52Evidence integrity without external authority — hashes stored alongside evidence.SHA-256 + git history for tamper visibility. True proofing requires RFC 3161 TSA.HIGH

Transparency Over False Confidence

These risks are documented because honest disclosure builds trust. Every assessment that claims zero irreducible risk is hiding something. These four are architectural — they apply to any Claude Code deployment. Defense-in-depth ensures no single risk is catastrophic.

Ready for Deployment

54Risks analyzed across 4 phases
41Controls deployed & tested
513Hook+script tests (3,014 total)
33Governance documents deployed
16Regulatory frameworks mapped
9SAST+DAST scan stages

For the CISO

41 security controls, 9-stage SAST+DAST, fail-closed gates, IR playbook, full adversarial validation. Every hook tested, every control deployed.

For the CCO

Evidence-first compliance across all regulatory obligations. CDD evidence at every phase. 16 frameworks mapped. The evidence chain maps to whatever framework your customers operate under — not just AI regulations.

For the AI Governance Board

ISO 42001 AIMS mapped. EU AI Act classification complete. Ethics charter, model validation, training curriculum, DPIA, AI system card.

Verdict: Ready for Deployment

The same governance architecture that secures Claude Code adoption will secure every AI workload and every regulated solution built on this platform. A financial services customer gets SOC 2 + DORA + SR 11-7 evidence. A healthcare customer gets HIPAA + FDA evidence. A government customer gets FedRAMP + NIST evidence. All from the same workflow, the same controls, the same evidence chain.

This is not a compliance project bolted onto a development tool. This is governance-as-code built into the platform from day one.

The technical foundation is the strongest available. The governance layer is complete. Evidence-first compliance is operational. We are ready for immediate pilot deployment.

Document Information
DocumentAI Governance & Security Assessment
SubjectBlaze Platform — Governance-as-Code for Regulated Enterprises
Methodology4-phase: Standard Risk + Adversarial Review + Synthetic CISO + Adversarial Challenge
Supersedesclaude-code-max-risk-analysis.html, ciso-readiness-assessment.html
ClassificationInternal — Security & Compliance Leadership
DateApril 2026

54 Risks Analyzed

45 risks from initial systematic analysis + 9 discovered by adversarial 4-agent review (security, architecture, critical thinking, test coverage agents).

Risk Categories

Command Execution (3)Shell commands, destructive actions, stuck loops
Credential Protection (4).env exposure, SSH keys, API keys in code, env var leakage
Data Classification (4)PII/PHI/PCI in context, base64 bypass, credential file Read
MCP Security (7)SSRF, command injection, schema poisoning, tool shadowing, credential relay, DNS exfil, prompt injection
Access Control (5)Authentication, offboarding, domain boundaries, multi-tenant, MCP connections
Change Management (6)Unreviewed merges, SDLC bypass, coverage gaps, evidence gaps, non-compliant patterns
Audit Trail (5)Granularity, tampering, MCP opacity, bypass logging, evidence integrity
Data Sovereignty (7)Retention, residency, cross-border, training contamination, VPC endpoints
Model Governance (4)Behavior drift, context exhaustion, hook timeouts, config tampering
Architecture (3)Same-principal trust, worktree isolation, token cost attacks
Other (6)Shadow AI, code quality, human error, segregation of duties, network exposure, policy drift

41 Controls Deployed

Every control is a deployed, tested, executable artifact — not a policy document.

Control Types

TypeCountExamples
PreToolUse (Blocking)22data-classification-gate, block-destructive-commands, pre-edit-validation, mcp-security-gate
SessionStart6identity-enforcement-gate, project-integrity-scanner, privacy-settings-gate
PostToolUse9mcp-data-flow-logger, bypass-audit-logger, stuck-detector
Other4pre-compact-snapshot, post-compact-restore, session-end, notification

33 Governance Documents

Written, reviewed, and filed before any CISO meeting.

Key Documents

16 Regulatory Frameworks Mapped

Each framework mapped to 21 deployed controls via governance-bridge. Machine-readable for automated reporting.

FrameworkIndustry
SOC 2 Type IICross-industry
GDPREU data protection
HIPAAHealthcare
ISO 27001Information security
NIST 800-53Government
FedRAMPGovernment cloud
PCI DSSPayment card
CCPACalifornia privacy
EU AI ActEU AI regulation
OWASP Top 10Application security
ISO 42001AI management systems
DORAEU financial services
SR 11-7US banking
ISO 23894AI risk management
NIST AI 600-1GenAI risk profile
NIST AI RMFAI risk management

Extensible: new frameworks added by mapping controls to requirements.

9-Stage SAST+DAST Battery

SAST (6)

DAST (3)

Evidence-First Compliance (CDD)

Compliance-Driven Development produces structured evidence at every SDLC phase.

How It Works

The same evidence chain satisfies SOC 2 for one customer, HIPAA for another, and DORA + EU AI Act for a third.

Demand 1: Data Classification & DLP

Dr. Chen: "Show me exactly where code and prompts go."

Demand 2: Access Control

Dr. Chen: "Who can use this tool?"

Demand 3: Audit Trail

Dr. Chen: "Every AI action must be logged."

Demand 4: Third-Party Risk

Dr. Chen: "I need a vendor assessment."

Demand 5: Incident Response

Dr. Chen: "What happens when the AI goes wrong?"

Demand 6: Change Management

Dr. Chen: "How are changes reviewed?"

Demand 7: Model Governance

Dr. Chen: "What if the model changes behavior?"

Demand 8: Regulatory Mapping

Dr. Chen: "Prove every control maps to a framework."

Demand 9: Penetration Testing

Dr. Chen: "Show me adversarial validation."

Demand 10: Acceptable Use

Dr. Chen: "What can employees do?"

41 Enforcement Hooks

CategoryCountKey Hooks
Data Classification3data-classification-gate, privacy-settings-gate, .env blocker
Identity & Access3identity-enforcement-gate, domain allowlist, revoked-users
MCP Security4mcp-security-gate (60+ patterns), allowlist, data flow logger
Code Integrity5pre-edit-validation, block-destructive-commands, canonical sync
SDLC Gates8Phase transitions, TDD, BDD, CDD enforcement
Audit5Data flow logger, bypass audit, stuck-detector, policy-change, integrity-scanner
Scanning6semgrep, bandit, eslint-security, truffleHog, pip-audit, npm-audit
Supply Chain3Dependency pinning, supply-chain-baseline, SBOM
Other4Context compaction, session lifecycle, worktree, branch naming

513 Hook+Script Tests

37 suites, 0 failures. 3,014 total platform tests. Meta-regression ensures every hook has a test file.

9-Stage SAST+DAST

6 SAST + 3 DAST. Deterministic results. Burp Suite equivalence via open-source portfolio. Any finding blocks merge.

4 Security YAML Configs

Code Audit

98 findings, 12 categories. 20 CRITICAL+HIGH remediated. 12 agents, 4 squads.

Adversarial Assessments

2 red team assessments. 8 attack vectors: IAM, network, K8s, auth, supply chain, data, monitoring, pentesting.

12-File SHA-256 Integrity Baseline

project-integrity-scanner.js detects config tampering before hooks execute.

21 Controls x 16 Frameworks

governance-bridge skill. Machine-readable. Extensible to any new framework.

Canary Token Detection

Canarytokens deployed as honey credentials and tripwire files. Near-zero false positive rate.