MITRE ATLAS
Adversarial Threat Landscape for Artificial-Intelligence Systems
MITRE’s knowledge base of tactics and techniques used against AI-enabled systems, modeled on ATT&CK and supported by case studies; technique IDs look like AML.T0051, LLM Prompt Injection.
- Also called
- ATLAS
- Defined in
- MITRE ATLAS
Covered in
Build evaluations around prohibited outcomes
Test the application’s actual security boundaries, preserve legitimate tasks and distinguish deterministic enforcement from variable model behavior.
Assess extraction, membership and inference risks
Define what an adversary can observe and measure privacy leakage without confusing a model’s output with proof about its training data.
Red-team LLM applications and agents by their effects
A red-teaming method for LLM features and agents: scope the whole system, map attacks to OWASP and MITRE ATLAS identifiers, score trials from observed effects, report rates with confidence intervals and retest on every model or provider change.
Defend agent memory and context against poisoning (OWASP ASI06)
OWASP ASI06 Memory & Context Poisoning: how an instruction or false fact saved once in agent memory, conversation summaries or a retrieval store steers later sessions, users and agents, and the write, scope, provenance, expiry and recovery controls that contain it.
Practice: Local project: Gate model and provider changes on a versioned red-team corpus