scikit-survival-analysis
Pass
Audited by Gen Agent Trust Hub on Oct 11, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill facilitates the ingestion of external data from files such as survival_data.csv and survival_data.arff. This represents a potential indirect prompt injection surface if the contents of these files are untrusted and contain instructions intended to influence the agent's behavior.
- Ingestion points: Identified in
references/data_competing_risks.mdthrough methods likepd.read_csvandsksurv.io.loadarff. - Boundary markers: No explicit delimiters or warnings to ignore embedded instructions within data files are present.
- Capability inventory: The skill enables file system writes (via
matplotlibplot saving) and package installation. - Sanitization: No specific data sanitization or validation routines are described for the content of processed files.
- [EXTERNAL_DOWNLOADS]: The documentation includes instructions for installing various Python libraries.
- Evidence:
pip install scikit-survival scikit-learn pandas numpy matplotlib. - Context: These are widely recognized and standard packages in the Python data science ecosystem.
Audit Metadata