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, andpytorchfor 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