explore-ml-data
Pass
Audited by Gen Agent Trust Hub on Jun 13, 2026
Risk Level: SAFECOMMAND_EXECUTIONEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTION
Full Analysis
- [COMMAND_EXECUTION]: The skill executes a Python script (
data/eda.py) using a shared runner located at.agents/skills/audit-ml-pipeline/scripts/run_cells.py. This relies on an external script for core execution logic. - [REMOTE_CODE_EXECUTION]: The skill generates and executes Python code at runtime. It populates
data/eda.pyfrom a template, substituting user-defined paths and data-loading logic, and executes it to generate analysis artifacts. This behavior is restricted to the generated script and intended for its primary function. - [EXTERNAL_DOWNLOADS]: The skill may trigger the installation of the
ipythonpackage via thepython-env-managerskill if it is not present in the environment, which is required for the execution runner to function. - [PROMPT_INJECTION]: The skill has an indirect prompt injection surface as it ingests untrusted user data files and uses the analysis results to generate a narrative report. Evidence chain: 1. Ingestion points: Raw data files located via user-provided paths or workspace scanning. 2. Boundary markers: No explicit boundary markers for raw data content; execution output is parsed via JSON. 3. Capability inventory: File-write (project deliverables), file-read, and shell execution (bash/pixi). 4. Sanitization: No explicit sanitization of data values before processing through skrub's profiling tools.
Audit Metadata