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.

7 in Initial Access · 101 total

IDTitleSummary
AML.T0010AI Supply Chain CompromiseAdversaries may gain initial access to a system by compromising the unique portions of the AI supply chain. This could include [Hardware](/techniques/AML.T0010…
AML.T0012Valid AccountsAdversaries may obtain and abuse credentials of existing accounts as a means of gaining Initial Access. Credentials may take the form of usernames and password…
AML.T0015Evade AI ModelAdversaries can [Craft Adversarial Data](/techniques/AML.T0043) that prevents an AI model from correctly identifying the contents of the data or [Generate Deep…
AML.T0049Exploit Public-Facing ApplicationAdversaries may attempt to take advantage of a weakness in an Internet-facing computer or program using software, data, or commands in order to cause unintende…
AML.T0052PhishingAdversaries may send phishing messages to gain access to victim systems. All forms of phishing are electronically delivered social engineering. Phishing can be…
AML.T0078Drive-by CompromiseAdversaries may gain access to an AI system through a user visiting a website over the normal course of browsing, or an AI agent retrieving information from th…
AML.T0093Prompt Infiltration via Public-Facing ApplicationAn adversary may introduce malicious prompts into the victim's system via a public-facing application with the intention of it being ingested by an AI at some …
Sourced from MITRE ATLAS. Curated by Adam Lundqvist, Founder at SQUR.