ATLASAML.T0109
ATLAS index
AML.T0109

AI Supply Chain Rug Pull

Adversaries may publish legitimate AI components or software, gain user adoption, then push an update with a malicious variant, leading to AI Supply Chain Compromise. More scrutiny is often placed on a supply chain dependency when it is first being considered for inclusion in an AI system. Performing a rug pull may all

Framework
MITRE ATLAS
Maturity
Realized
Platforms
Predictive AI, Generative AI, Agentic AI
Release
2026.05

Overview

Adversaries may publish legitimate AI components or software, gain user adoption, then push an update with a malicious variant, leading to AI Supply Chain Compromise. More scrutiny is often placed on a supply chain dependency when it is first being considered for inclusion in an AI system. Performing a rug pull may allow adversaries to bypass these defenses and be more likely to achieve Initial Access.

Adversaries may publish malicious AI components via Publish Poisoned Models, Publish Poisoned Datasets, or Publish Poisoned AI Agent Tool.

Adversaries may use other techniques (See AI Supply Chain Reputation Inflation) to gain user trust and increase adoption before performing the rug pull.

Sources

  1. MITRE ATLAS AML.T0109: AI Supply Chain Rug Pull — MITRE