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.pyimplements secure coding practices, such as usingyaml.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