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2 reports

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AI Supply Chain Compromise: Models Lack Bill of Materials

ATLAS OWASP MEDIUM ▲ 6.2 Dark Reading May 25, 2026

As AI systems proliferate across enterprise environments, the lack of standardised AI Bills of Materials (AI BOMs) leaves organisations blind to the components, training data, and dependencies embedded in deployed models. The article examines whether 2026 marks a turning point for AI BOM adoption as a risk management practice. Without visibility into AI supply chains, organisations remain exposed to hidden vulnerabilities including poisoned models, compromised dependencies, and undisclosed third-party components.

litellm Supply Chain Attack: PyPI .pth File Injection

ATLAS OWASP HIGH ▲ 8.2 Schneier on Security Apr 13, 2026

A malicious supply chain attack was discovered in litellm version 1.82.8, a widely-used Python library that serves as a unified interface for interacting with large language model APIs. The compromised package contained a hidden .pth file executing arbitrary code on every Python interpreter startup, meaning any developer or AI system relying on litellm could be silently compromised without triggering an explicit import. Given litellm's central role in LLM-powered application stacks, this attack vector poses significant risk to AI pipeline integrity, credential theft, and downstream model infrastructure.

AI Supply Chain Compromise: Models Lack Bill of Materials

litellm Supply Chain Attack: PyPI .pth File Injection

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