MITRE ATLAS 2026.09 / technique reference
AML.T0007
Discover AI Artifacts
MITRE source definition
Adversaries may search private sources to identify AI learning artifacts that exist on the system and gather information about them. These artifacts can include the software stack used to train and deploy models, training and testing data management systems, container registries, software repositories, and model zoos.
This information can be used to identify targets for further collection, exfiltration, or disruption, and to tailor and improve attacks.
Source modified 2026-05-27. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.
Parent, sub-techniques and ATT&CK references
No explicit relationship in this pinned source.
Source-backed defensive context
MITRE mitigations
MITRE case studies
- AML.CS0027 Organization Confusion on Hugging Face · Exercise
- AML.CS0028 AI Model Tampering via Supply Chain Attack · Exercise
- AML.CS0058 Google Photos AI Model Extraction · Exercise
These are explicit source relationships, not independently reproduced incidents or validated detection coverage.
Simulation and telemetry boundary
This is a technique reference page, not a runnable simulation. No ATLAS-specific telemetry mapping, local attack execution or detector validation is asserted. MITRE maturity describes its source evidence, not a 1200km lab result.
For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.
Provenance and attribution
Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0
Copyright 2021-2026 MITRE. Source text and explicit relationships are retained; navigation, formatting and local links are provided by 1200km.
No explicit relationship in this pinned source.