mlops
Pass
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: SAFE
Full Analysis
- [DATA_EXPOSURE] (SAFE): No hardcoded credentials or sensitive file paths were detected. Examples correctly demonstrate the use of environment variables and secrets for sensitive URIs.
- [REMOTE_CODE_EXECUTION] (SAFE): While the skill mentions model loading (
mlflow.sklearn.load_model), which involves deserialization, this is an industry-standard practice for MLOps and is presented as part of the primary skill purpose. The skill does not execute code from untrusted external sources. - [COMMAND_EXECUTION] (SAFE): The provided scripts (
validate.py) perform local file system checks and YAML validation usingyaml.safe_load(). No arbitrary command execution was found. - [PROMPT_INJECTION] (SAFE): No instructions attempting to override agent behavior or bypass safety filters were detected in the markdown or metadata.
Audit Metadata