1. Map system boundaries
Outcome: All data and authority flows are visible.
Tasks
- →Mark trusted and untrusted inputs
- →Identify secrets
- →Classify tools
Checks
- ✓Write capability is not hidden
Build an AI-system threat model covering abuse cases, controls, security tests, residual risk, and an incident playbook.
Scenario
An AI assistant uses RAG and tools with write access. Define trust boundaries, attack paths, and controls before production launch.
Outcome: All data and authority flows are visible.
Tasks
Checks
Outcome: Threats are linked to real flows.
Tasks
Checks
Outcome: Controls are verifiable.
Tasks
Checks
Outcome: The team can detect, contain, and recover.
Tasks
Checks
Assessment rubric
Data, model, tools, users, secrets, and external systems are fully mapped.
Insufficient
Authority or data flows remain hidden.
Competent
Core boundaries are explicit.
Strong
Data classification, tenant boundaries, and supply-chain lineage are documented.
Evidence required
Threats have preconditions, impact, likelihood, and an owner.
Insufficient
The list is generic and not tied to real flows.
Competent
Threats are contextualized and prioritized.
Strong
Attack trees, chained abuse cases, and residual risk are documented.
Evidence required
Prevent, detect, and respond controls have test evidence.
Insufficient
Controls are declarative only.
Competent
Key controls are verified.
Strong
Automated security evals, policy as code, and a regression gate are implemented.
Evidence required
Kill switch, containment, rollback, and postmortem procedures are verified.
Insufficient
The response plan has not been tested.
Competent
The drill is complete with evidence.
Strong
Timed recovery metrics and automated containment are implemented.
Evidence required