ml-ops-engineer

Pass

Audited by Gen Agent Trust Hub on Mar 13, 2026

Risk Level: SAFEPROMPT_INJECTIONREMOTE_CODE_EXECUTION
Full Analysis
  • [INDIRECT_PROMPT_INJECTION]: The skill implements several data ingestion points that could serve as surfaces for indirect prompt injection if the processed data is passed to an LLM.
  • Ingestion points: External data is ingested via the FastAPI /predict endpoint, pd.read_csv in batch processing, and pd.read_parquet in Kubeflow components (SKILL.md).
  • Boundary markers: No delimiters or 'ignore embedded instructions' warnings are present in the provided code templates.
  • Capability inventory: The skill patterns include file system access (read/write Parquet/CSV), network operations (FastAPI server), and model execution.
  • Sanitization: No explicit sanitization or validation of the content within the ingested data is shown in the examples.
  • [DYNAMIC_EXECUTION]: The skill demonstrates patterns for loading machine learning models using mlflow.pyfunc.load_model and xgboost.load_model. In a production environment, loading serialized models (such as those using pickle) from untrusted storage locations can lead to arbitrary code execution during deserialization.
Audit Metadata
Risk Level
SAFE
Analyzed
Mar 13, 2026, 01:20 AM