MITRE ATLAS
MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a knowledge base of adversarial tactics and techniques targeting AI systems, providing a shared taxonomy for AI security testing, threat modeling, and defense.
What MITRE ATLAS Provides
MITRE ATLAS is the AI-specific counterpart to the widely used MITRE ATT&CK framework. Where ATT&CK catalogs adversarial tactics and techniques against traditional systems, ATLAS catalogs the analogous tactics and techniques against AI. Categories include reconnaissance of ML systems, model access, poisoning, evasion, and impact.
Each technique in ATLAS is documented with its description, real-world examples where available, and detection and mitigation guidance. The framework is designed to be used the same way ATT&CK is used, as a common vocabulary that security teams, product teams, and regulators can share.
Why MITRE ATLAS Matters for Enterprise AI Security
MITRE ATLAS gives AI security programs a defensible reference for what they are testing against and defending against. Rather than describing red team exercises or adversarial testing in ad hoc terms, teams can describe them in ATLAS technique IDs, making coverage measurable and comparable.
ATLAS also underpins several enterprise AI security tools and services, which increasingly reference ATLAS coverage as a way of describing their scope.
MITRE ATLAS in Kovrr
Kovrr's AI risk register incorporates ATLAS-mapped adversarial techniques, giving security teams a direct view of which techniques their discovered AI systems are exposed to. This connects threat modeling directly to AIRQ outputs.
How Kovrr Approaches MITRE ATLAS
Kovrr's AI Security and Governance Platform maps discovered AI assets and their attack surfaces against MITRE ATLAS tactics and techniques, making AI security coverage measurable in the same terms the broader security community is standardizing around.
Related Terms
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