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.
6 in Execution · 101 total
| ID | Title | Summary |
|---|---|---|
| AML.T0011 | User Execution | An adversary may rely upon specific actions by a user in order to gain execution. Users may inadvertently execute unsafe code introduced via [AI Supply Chain C… |
| AML.T0050 | Command and Scripting Interpreter | Adversaries may abuse command and script interpreters to execute commands, scripts, or binaries. These interfaces and languages provide ways of interacting wit… |
| AML.T0051 | LLM Prompt Injection | An adversary may craft malicious prompts as inputs to an LLM that cause the LLM to act in unintended ways. These "prompt injections" are often designed to caus… |
| AML.T0053 | AI Agent Tool Invocation | Adversaries may use their access to an AI agent to invoke tools the agent has access to. LLMs are often connected to other services or resources via tools to i… |
| AML.T0100 | AI Agent Clickbait | Adversaries may craft deceptive web content designed to bait Computer-Using AI agents or AI web browsers into taking unintended actions, such as clicking butto… |
| AML.T0103 | Deploy AI Agent | Adversaries may launch AI agents in the victim's environment to execute actions on their behalf. AI agents may have access to a wide range of tools and data so… |