machine-learning

Pass

Audited by Gen Agent Trust Hub on Oct 8, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill uses established, well-known Python libraries for all machine learning tasks, including scikit-learn, XGBoost, and SHAP. All code examples adhere to standard data science best practices for training, cross-validation, and model evaluation.
  • [SAFE]: No indicators of command execution, privilege escalation, or persistence were found. The skill operates within expected file system boundaries by reading local CSV data and writing joblib-serialized models to a local directory.
  • [SAFE]: The utility script scripts/validate.py implements secure coding practices, such as using yaml.safe_load() to parse configuration files, which prevents unsafe deserialization attacks.
  • [SAFE]: All identified dependencies are reputable, industry-standard packages available on the official Python Package Index (PyPI).
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 8, 2026, 10:28 PM