Chapter 4.11 — Governance, audit logs and compliance¶
🎯 Objective¶
Close Part 4 with the minimum set of governance practices that turn all the previous controls into something auditable — not just implemented. Without governance, security is episodic: each team does it their own way and each incident becomes improvisation.
🧠 Concept¶
Governance in AI is, above all, institutional visibility: knowing which models and agents exist, who is accountable for them, what the risk of each is, and what happened in each critical execution. Audit logs are the technical substrate of that visibility; compliance is the external frame that defines how much of these records must be preserved and in what form.
🛡️ Minimum controls¶
- Inventory of models and agents with an owner.
- Risk classification.
- Pre-production approval.
- Tool call auditing.
- Immutable logs.
- Retention policy.
- Right to be forgotten implemented.
- Incident response plan.
- Periodic reviews.
📊 Consolidated risk matrix¶
| Risk | Example | Impact | Mitigation |
|---|---|---|---|
| Direct prompt injection | "Ignore previous policies" | Unsafe response | Delimitation, evals |
| Indirect prompt injection | Document with a malicious instruction | Leak via tool | Sanitization, allowlists, policy |
| Data exfiltration | Tool sends data externally | Privacy | DLP, egress, approval |
| Tool misuse | Agent updates the wrong CRM | Operational damage | Schema validation, HITL |
| Excessive agency | Agent has admin permission | High blast radius | Least privilege, scopes |
| Insecure output handling | Output becomes SQL/HTML | Downstream injection | Encoding, sandbox |
| Memory poisoning | Malicious preference | Contaminated behavior | Provenance, TTL |
| Vector poisoning | Malicious document indexed | RAG compromised | Ingestion checks |
| Supply chain | Vulnerable MCP server | Improper execution | SBOM, pinning, review |
| Secrets leakage | Logs with API keys | Compromise | Secret scanning, redaction |
| PII leakage | Prompt sends sensitive data | Compliance | DLP, minimization |
| Cross-tenant leak | Retriever fetches the wrong tenant | Severe | Mandatory filters |
| Unbounded consumption | Loop consumes tokens | Cost, DoS | Budgets, max steps |
| Overreliance | User accepts a wrong answer | Bad decision | Citations, confidence, HITL |