ml-supply-chain
Safeguard articles tagged "ml-supply-chain" — guides, analysis, and best practices for software supply chain and application security.
20 articles
OpenSSF Model Signing v1.0: Sigstore for ML
OpenSSF launched Model Signing v1.0 in April 2025 with Sigstore integration. NVIDIA NGC adopted it the same month. We explain what it signs, how to verify, and where the gaps are.
nullifAI: Broken Pickles and the Hugging Face Detection Gap
ReversingLabs disclosed two malicious Hugging Face models that evaded Picklescan by using broken 7z-packed PyTorch archives. We unpack the technique.
Hugging Face Token Exposure 2024 Analysis
Researchers found thousands of valid Hugging Face API tokens in public code and models. Analysis of the 2024 exposures and what they mean for ML supply chain.
AI Supply Chain Attacks: Emerging Threats in Model and Data Pipelines
As organizations adopt AI at scale, the AI/ML supply chain is becoming a new attack surface. From poisoned models to compromised training data, the threats are real and growing.
What is Training Data Poisoning
Training data poisoning corrupts an ML model's training data to plant hidden backdoors. Learn how it works, real incidents, and how to detect it.
What is Adversarial Machine Learning
Adversarial machine learning exploits model decision boundaries via evasion, poisoning, extraction, and inference attacks -- here's how it works and how to defend against it.
Hugging Face's Guardian-Plus-Picklescan Stack: How the Model Hub Scanning Posture Evolved Through 2025-2026
Following NullifAI and the broken-pickle bypass campaigns, Hugging Face layered Protect AI's Guardian on top of Picklescan, ClamAV, and secrets scanning across 1.5 million public models. Here is the defender view of the new pipeline.
Detecting Model Supply Chain Poisoning in 2026
Poisoning attacks against the model supply chain have moved from research to incident reports. What detection looks like when the attack surface includes weights.
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