xgb-tuning
Pass
Audited by Gen Agent Trust Hub on Jun 29, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill implements hyperparameter tuning using standard, well-known machine learning libraries including XGBoost, Optuna, Scikit-learn, and Pandas.
- [SAFE]: Data access is limited to reading CSV and Parquet files provided via the
--data_pathargument. No unauthorized file system access or sensitive path traversal was detected. - [SAFE]: All operations are local; no network requests or data exfiltration patterns were found in the analyzed scripts.
- [SAFE]: The code uses standard 'vendoring' practices to manage internal dependencies, adding local paths to
sys.pathto ensure module availability. - [SAFE]: Model saving and loading use standard XGBoost and JSON serialization methods for metadata, which do not pose a high security risk in this context.
Audit Metadata