MITRE ATLAS 2026.09 / technique reference
AML.T0111
AI Supply Chain Reputation Inflation
MITRE source definition
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.
Source modified 2026-05-27. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.
Parent, sub-techniques and ATT&CK references
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Source-backed defensive context
MITRE mitigations
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MITRE case studies
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Simulation and telemetry boundary
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For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.
Provenance and attribution
Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0
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