ml-anomaly-detection

Pass

Audited by Gen Agent Trust Hub on Jun 29, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill is a well-structured implementation of anomaly detection techniques. It uses standard, well-known libraries such as scikit-learn, scipy, numpy, tensorflow, and pytorch for its operations.
  • [SAFE]: Data processing logic (Z-score, IQR, Isolation Forest, Autoencoders) is implemented using standard mathematical and ML patterns. There is no evidence of unsafe data handling or exfiltration.
  • [SAFE]: The skill provides extensive documentation on architecture, decision trees, and evaluation metrics, focusing on legitimate data science workflows.
  • [SAFE]: No obfuscation, prompt injection, or persistence mechanisms were detected. The use of remote resources is limited to standard package imports.
Audit Metadata
Risk Level
SAFE
Analyzed
Jun 29, 2026, 08:47 PM
Security Audit — agent-trust-hub — ml-anomaly-detection