DevOps & Infrastructure
Detecting Data And Model Poisoning
Identify poisoned training data and backdoored ML models across the pipeline using IBM's Adversarial Robustness Toolbox (activation clustering, spectral signatures, trigger reconstruction), Cleanlab for label-quality issues, and supply-chain checks like weight-hash verification and safetensors enforcement. Use before training or deploying on third-party/user-contributed data or downloaded checkpoints, during ML supply-chain reviews, or when investigating model misbehavior tied to specific inputs (suspected backdoor trigger).
- Publisher / source
- Cybersecurity Skills (Community)
- Upstream record
- mukul975/Anthropic-Cybersecurity-Skills
- Version
- Version 3
- Published
- Publication review
- Approved for publication
- Content fingerprint
be0338898f0fdcc1567905dece3b9479090463d18859de732677163c15f538d2