skills/opensensenova/sensenova-skills/statistical-distribution-and-outlier-analysis/Gen Agent Trust Hub
statistical-distribution-and-outlier-analysis
Pass
Audited by Gen Agent Trust Hub on Jul 3, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill implements a legitimate workflow for data science, involving data ingestion, statistical calculation, and report generation using standard libraries like pandas and matplotlib. No malicious patterns such as credential harvesting, obfuscation, or unauthorized network calls were detected.
- [SAFE]: File system access is limited to the local environment. The skill reads 'input_data.xlsx' and generates output files for the user. There is no evidence of unauthorized data exfiltration or access to sensitive system directories.
- [PROMPT_INJECTION]: The skill possesses a surface for indirect prompt injection as it processes data from an external file ('input_data.xlsx' in Step 1). 1. Ingestion points: 'input_data.xlsx'. 2. Boundary markers: Absent. 3. Capability inventory: File-write operations (generating PNG and CSV reports in Steps 2, 5, and 6). 4. Sanitization: The risk is mitigated by the script's use of strict numeric type-checking and specific regular expression patterns, which treat the ingested data as raw values for calculation rather than instructions for the agent.
Audit Metadata