Techniquedefense-evasionATLAS

AML.T0111AI Supply Chain Reputation Inflation

What it is

AI Supply Chain Reputation Inflation is the process of building or leveraging genuinely credible-looking trust signals to increase the perceived legitimacy of AI supply chain components, with the goal of driving adoption of malicious or compromised assets. Adversaries use established developer accounts with a history of legitimate projects and contributions to publish AI models, datasets, packages, and MCP servers that appear trustworthy. They build reputation through real adoption signals such as downloads, GitHub stars, forks, and inclusion in dependency chains, often releasing benign versions before introducing malicious updates via [AI Supply Chain Rug Pull](/techniques/AML.T0109). By relying on authentic history and usage patterns, these components pass both human and automated trust checks, increasing the likelihood they are adopted without scrutiny.

References

  1. https://atlas.mitre.org/techniques/AML.T0111

Related by meaning· 6

Nearest entities by semantic similarity across the cs-graph corpus.

ATLAS
AI Supply Chain Rug Pull
ATLAS
AI Supply Chain Compromise
ATLAS
Impersonation
ATLAS
Publish Poisoned Models
ATLAS
Publish Poisoned Datasets
ATLAS
AI Agent Tool Poisoning
Sourced from MITRE ATLAS — Adversarial Threat Landscape for AI Systems. Curated by Adam Lundqvist, SQUR.