ml-classical-ml

Pass

Audited by Gen Agent Trust Hub on Jul 8, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill defines supervised and unsupervised learning pipelines using standard scikit-learn patterns such as Pipelines and ColumnTransformers.
  • [SAFE]: It provides legitimate implementation examples for hyperparameter optimization using GridSearchCV, RandomizedSearchCV, and Optuna.
  • [SAFE]: Security considerations documented in the skill appropriately address PII handling, model robustness, and serialized artifact security.
  • [SAFE]: All identified dependencies are well-known, established machine learning and data science libraries, including scikit-learn, XGBoost, and LightGBM.
  • [SAFE]: The extensive reference documentation, while containing repetitive boilerplate content across many files, does not contain hidden malicious instructions or obfuscated code.
Audit Metadata
Risk Level
SAFE
Analyzed
Jul 8, 2026, 12:24 PM
Security Audit — agent-trust-hub — ml-classical-ml