mle
Pass
Audited by Gen Agent Trust Hub on Jun 28, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No malicious patterns, obfuscation, or security vulnerabilities were detected across the analyzed files and code snippets.- [SAFE]: The skill demonstrates security best practices, such as using environment variable placeholders (e.g., '${AWS_ACCESS_KEY_ID}') for secret management in deployment examples and utilizing 'weights_only=True' in 'torch.load' to mitigate risks associated with untrusted model checkpoints.- [EXTERNAL_DOWNLOADS]: External resources and datasets are sourced from well-known and trusted platforms like HuggingFace, OpenML, and official documentation sites, which is standard for machine learning development.- [COMMAND_EXECUTION]: Included shell commands are restricted to standard development tools such as DVC, MLflow, TensorBoard, and Uvicorn, used appropriately for project management, observability, and serving.
Audit Metadata