python-ml-predictive

Pass

Audited by Gen Agent Trust Hub on May 14, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill demonstrates high security standards for machine learning integration, specifically advocating for strict input validation via Pydantic to prevent malformed data from reaching models.
  • [SAFE]: Artifact management practices follow industry standards by recommending model storage in secure object stores (S3/GCS) rather than version control, and using environment variables for access.
  • [SAFE]: The use of scikit-learn Pipelines ensures that data preprocessing is encapsulated and consistent between training and inference, which is a key defense against data leakage and logic errors.
  • [SAFE]: Documentation includes considerations for data protection regulations (e.g., Uganda DPPA, Kenya DPA), highlighting privacy-conscious implementation.
Audit Metadata
Risk Level
SAFE
Analyzed
May 14, 2026, 11:16 AM
Security Audit — agent-trust-hub — python-ml-predictive