The thinking behind AI security review.
Threat models, governance evidence, and the decisions that hold up under scrutiny. Written for security architects and the committees they report to.
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Threat modeling, governance evidence, and what AI Committees actually need — written for security architects and AI governance leads. No cadence promises.
Why SOC 2 is not AI assurance
SOC 2 covers infrastructure and process. It says nothing about model behaviour, training data, or edge cases. AI assurance needs different evidence.
Building an AI management system (AIMS) from scratch
An AI management system is governance infrastructure: policies, procedures, roles, records for defensible AI decisions at scale. How to build one.
Vetting third-party MCP servers before you connect them
Every third-party MCP server extends your agent's attack surface. The vetting process: source review, manifest audit, permission scope, and evidence.
RAG PII Leakage — 3 Retrieval Paths That Expose Data
RAG over internal corpora frequently exposes personal data never intended to be queryable. The most common data-protection finding in RAG security reviews.
EU AI Act vs GDPR — where they overlap for AI systems
GDPR and the EU AI Act overlap heavily for AI processing personal data. Where obligations are additive, and which review artefacts satisfy both.
Security review for multi-agent systems
When agents orchestrate agents, single-agent trust assumptions multiply. Covers inter-agent trust, capability delegation, and blast-radius containment.
LLM supply-chain risk — models, weights, and dependencies
LLM supply chains span models, datasets, inference providers, and plugins. Map the attack surface and review questions for each layer.
Scoping an AI security review without boiling the ocean
Scope an AI security review to the decision you need: the system, the deployment context, and the pass/fail threshold.
The restricted-pilot pattern for risky AI systems
A restricted pilot is a formal disposition: defined scope, named controls, explicit re-review triggers. How to write one that holds.
AI subprocessor risk in your vendor chain
When a vendor's AI runs on a third-party model provider, that provider is a subprocessor. Retention, training, and transfer risks your DPA missed.
AI risk assessment under ISO 42001
ISO 42001 requires a documented AI risk assessment. What it must cover, how it differs from IT risk assessments, and what complete looks like.
Transport security for MCP servers
MCP runs over HTTP/SSE or stdio — each with distinct security requirements. Covers TLS, mutual auth, and transport review questions.
Free resources
Practical templates for every framework covered here.
AI Security Review Template
Full review pack with threat model, controls, and evidence grading.
OWASP Agentic Top 10 Controls
Each risk mapped to required controls and lifecycle gates.
AI Risk Disposition Memo
Clearance decision template with rationale and sign-off log.
AI Go-Live Security Checklist
Production gate checklist for security architects and CISOs.