The OWASP ML Security Top 10 highlights attacks like input manipulation, data poisoning, model theft and insecure supply chains. What good looks like Dataset integrity: provenance checks, hash manifests, and differential privacy for sensitive features. Model artifact security: signed models, SBOMs for training pipelines, and private registries. Robustness testing: adversarial evals, drift detection, and red-team…
