mlflow
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFECOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [COMMAND_EXECUTION]: The skill provides instructions for executing system commands, including package management (
pip install), starting web interfaces (mlflow ui), serving models locally (mlflow models serve), and programmatically retrieving version control metadata viasubprocess.check_outputfor lineage tracking. - [INDIRECT_PROMPT_INJECTION]: The skill exposes an attack surface for indirect prompt injection by ingesting data from external MLflow tracking servers and model registries.
- Ingestion points: External data is retrieved via
MlflowClientsearch methods andmlflow.pyfunc.load_model(documented inSKILL.mdandreferences/model-registry.md). - Boundary markers: The provided code examples do not include explicit delimiters or instructions to ignore potential injections within experiment metadata.
- Capability inventory: The skill includes capabilities to execute shell commands, perform network requests via
requestsandboto3, and write files to the local file system. - Sanitization: The code samples do not demonstrate sanitization or validation of metadata retrieved from the tracking server.
Audit Metadata