101 indexed
ATLASATLAS adversarial ML techniques
101 MITRE ATLAS top-level techniques covering the adversarial-ML attack surface, grouped by tactic. Authored by Adam Lundqvist.
8 in Reconnaissance · 101 total
| ID | Title | Summary |
|---|---|---|
| AML.T0000 | Search Open Technical Databases | Adversaries may search for publicly available research and technical documentation to learn how and where AI is used within a victim organization. The adversar… |
| AML.T0001 | Search Open AI Vulnerability Analysis | Much like the [Search Open Technical Databases](/techniques/AML.T0000), there is often ample research available on the vulnerabilities of common AI models. Onc… |
| AML.T0003 | Search Victim-Owned Websites | Adversaries may search websites owned by the victim for information that can be used during targeting. Victim-owned websites may contain technical details abou… |
| AML.T0004 | Search Application Repositories | Adversaries may search open application repositories during targeting. Examples of these include Google Play, the iOS App store, the macOS App Store, and the M… |
| AML.T0006 | Active Scanning | An adversary may probe or scan the victim system to gather information for targeting. This is distinct from other reconnaissance techniques that do not involve… |
| AML.T0064 | Gather RAG-Indexed Targets | Adversaries may identify data sources used in retrieval augmented generation (RAG) systems for targeting purposes. By pinpointing these sources, attackers can … |
| AML.T0087 | Gather Victim Identity Information | Adversaries may gather information about the victim's identity that can be used during targeting. Information about identities may include a variety of details… |
| AML.T0095 | Search Open Websites/Domains | Adversaries may search public websites and/or domains for information about victims that can be used during targeting. Information about victims may be availab… |