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.

4 in Collection · 101 total

IDTitleSummary
AML.T0035AI Artifact CollectionAdversaries may collect AI artifacts for [Exfiltration](/tactics/AML.TA0010) or for use in [AI Attack Staging](/tactics/AML.TA0001). AI artifacts include model…
AML.T0036Data from Information RepositoriesAdversaries may leverage information repositories to mine valuable information. Information repositories are tools that allow for storage of information, typic…
AML.T0037Data from Local SystemAdversaries may search local system sources, such as file systems and configuration files or local databases, to find files of interest and sensitive data prio…
AML.T0085Data from AI ServicesAdversaries may use their access to a victim organization's AI-enabled services to collect proprietary or otherwise sensitive information. As organizations ado…
Sourced from MITRE ATLAS. Curated by Adam Lundqvist, Founder at SQUR.
MITRE ATLAS adversarial ML techniques — by tactic | SQUR Knowledge Base