Who is MITRE ATLAS intended for and how can its content be used?

Updated

MITRE ATLAS™ is intended for anyone who needs a structured way to reason about threats to AI systems: AI developers, security teams, risk and compliance staff, and researchers. Its content is best used as a shared reference for threat modeling, red-team planning, security training, and risk discussions—not as a certification or a substitute for system-specific testing. When you quote it, cite MITRE ATLAS as the source and note the version or access date, since the knowledge base is updated over time.

Who each audience gets from ATLAS

Audience Typical use What to watch
AI developers / ML engineers Map design and deployment risks to known tactics and techniques; prioritize hardening work Techniques describe attacker behavior, not fixes—pair with your own controls
Security teams (blue/red) Build threat models and red-team scenarios for AI components Validate relevance to your model type, data, and deployment
Risk, compliance, and governance Frame AI risk discussions and document threat coverage ATLAS is a knowledge base, not a regulatory standard
Researchers and trainers Use as a common vocabulary in courses and exercises Check version/date so training matches current content

How the content is meant to be used

ATLAS organizes threat knowledge around tactics (the attacker's goal) and techniques (how the goal is achieved), with case studies of real-world AI incidents. That structure supports four common workflows:

  • Threat modeling: walk the tactics to identify which apply to your system, then note the techniques that matter.
  • Red-team and tabletop exercises: turn techniques into test scenarios and discussion prompts.
  • Training: use tactics and case studies to teach AI-specific attack patterns.
  • Risk and compliance discussion: use shared terminology so technical and governance teams describe the same threat consistently.

Citing and reusing content

  • Attribute the material to MITRE ATLAS and link to the specific entry you used.
  • Record the version or the date you accessed it, because entries and case studies change.
  • Quote technique descriptions accurately rather than paraphrasing them into your own control claims.
  • Keep ATLAS material distinct from your internal findings so readers can tell source from analysis.

Common pitfalls

  • Treating ATLAS as a checklist that guarantees coverage; it is a reference to reason from.
  • Assuming every technique applies to every AI system—filter by your architecture and use case.
  • Citing an entry without a date, so a later reader cannot tell which version you used.
  • Presenting ATLAS as a compliance certification; it supports risk discussion, not attestation.

For a first pass, start with the tactics overview, select the techniques relevant to your system, and record your selections with the ATLAS version you used.