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 your existing threat modeling tool doesn't model agents
STRIDE, attack trees, and most commercial threat modeling tools were designed for deterministic software. Agentic AI has five properties those tools cannot represent — and each one is an attack surface.
Assessing third-party AI vendors — the questions procurement skips
Third-party AI vendor assessments typically cover data processing agreements and SOC 2. They miss model governance, incident notification for model updates, and the evidence required to re-assess when the vendor changes the underlying model.
A worked example: AI Risk Disposition for a Copilot Studio procurement agent
Every section of the disposition filled in with real content — decision, rationale, required controls, residual risk acceptance, evidence gaps, re-assessment triggers, and sign-off log. The same system used in the Drel demo dossier.
Threat modeling an MCP server — the parts AppSec tools miss
MCP servers have four distinct attack surfaces: transport, tool surface, prompt context injection, and auth boundary. Traditional threat modeling tools model the first and miss the other three. Here is the full threat model with controls.
EU AI Act Article 9 risk management — what evidence is required
Article 9 of the EU AI Act requires a risk management system for high-risk AI. This piece translates each of its six requirements into specific evidence artefacts — what an auditor will ask for, and the gaps that appear most often when organisations try to produce it.
OWASP Agentic Top 10 mapped to required controls
The OWASP Agentic Top 10 names the threats. This piece maps each one to the controls that close it, the lifecycle gate where each control must be in place, and the evidence required to verify it — so your AI Committee has a working checklist, not just a threat list.
What an AI Risk Disposition actually contains
AI Committees keep approving systems they can't defend later. The Risk Disposition memo is the artifact that fixes this — here is what goes into one, section by section, with examples from a real assessed system.
What an agentic AI audit trail must capture
Auditing an agentic AI system after an incident requires a different evidence set than auditing a deterministic system. The audit trail must capture not just what happened, but what the model decided and why — and most implementations miss the latter.
LLM red-teaming for a security review
Red-teaming an LLM application is not the same as penetration testing it. This piece covers the distinct techniques — goal hijacking, jailbreaking, indirect injection, and exfiltration chains — and how to document findings for a security review.
Presenting AI risk to leadership without the 40-slide deck
Most AI risk presentations to leadership are too long, too technical, and too focused on the threats rather than the decision. This piece defines the structure that gets a governance decision out of a leadership meeting.
Five mistakes that make an AI security review undefensible
Most AI security reviews fail not because they miss threats, but because they miss the structure that makes a decision defensible. These five mistakes appear in almost every review we have examined.
The security terms an AI vendor contract needs
Standard vendor contracts cover SLAs, data processing, and confidentiality. AI vendor contracts need additional terms: model-change notification, training data restrictions, incident notification, and re-assessment rights. This piece defines the clause language.
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.