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.

9 in Discovery · 101 total

IDTitleSummary
AML.T0007Discover AI ArtifactsAdversaries may search private sources to identify AI learning artifacts that exist on the system and gather information about them. These artifacts can includ…
AML.T0013Discover AI Model OntologyAdversaries may discover the ontology of an AI model's output space, for example, the types of objects a model can detect. The adversary may discovery the onto…
AML.T0014Discover AI Model FamilyAdversaries may discover the general family of model. General information about the model may be revealed in documentation, or the adversary may use carefully …
AML.T0062Discover LLM HallucinationsAdversaries may prompt large language models and identify hallucinated entities. They may request software packages, commands, URLs, organization names, or e-m…
AML.T0063Discover AI Model OutputsAdversaries may discover model outputs, such as class scores, whose presence is not required for the system to function and are not intended for use by the end…
AML.T0069Discover LLM System InformationThe adversary is trying to discover something about the large language model's (LLM) system information. This may be found in a configuration file containing t…
AML.T0075Cloud Service DiscoveryAdversaries may attempt to enumerate the cloud services running on a system after gaining access. These methods can differ from platform-as-a-service (PaaS), t…
AML.T0084Discover AI Agent ConfigurationAdversaries may attempt to discover configuration information for AI agents present on the victim's system. Agent configurations can include tools or services …
AML.T0089Process DiscoveryAdversaries may attempt to get information about processes running on a system. Once obtained, this information could be used to gain an understanding of commo…
Sourced from MITRE ATLAS. Curated by Adam Lundqvist, Founder at SQUR.
MITRE ATLAS adversarial ML techniques — by tactic | SQUR Knowledge Base