alterlab-scikit-learn

Pass

Audited by Gen Agent Trust Hub on Apr 12, 2026

Risk Level: SAFE
Full Analysis
  • [DYNAMIC_EXECUTION]: The reference documentation includes standard examples of model persistence using the pickle and joblib libraries. While common in machine learning, these methods involve data deserialization and should only be used with trusted files to prevent unauthorized code execution.
  • [EXTERNAL_DOWNLOADS]: The skill provides instructions for installing well-known machine learning packages such as scikit-learn, pandas, and numpy from official registries.
  • [INDIRECT_PROMPT_INJECTION]: The skill defines a surface for processing external data (e.g., CSV ingestion in SKILL.md). 1. Ingestion point: SKILL.md. 2. Boundary markers: Absent. 3. Capability inventory: File system writes for saving plot images in scripts/clustering_analysis.py. 4. Sanitization: Absent. As these are standard examples, the risk is negligible.
Audit Metadata
Risk Level
SAFE
Analyzed
Apr 12, 2026, 12:46 AM
Security Audit — agent-trust-hub — alterlab-scikit-learn