python-data-analytics
Pass
Audited by Gen Agent Trust Hub on May 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides comprehensive documentation and implementation patterns for data science workflows using standard, well-known libraries such as Pandas, Polars, SQLAlchemy, and Scipy.
- [SAFE]: It enforces security best practices for database interactions, specifically requiring the use of bound parameters in SQL queries (
:tenant_id) to mitigate SQL injection risks. - [SAFE]: The skill includes a 'Tenant isolation checklist' that mandates filtering data at the database level and includes assertions in Python to prevent cross-tenant data leakage, which is a critical security control for SaaS environments.
- [SAFE]: No malicious patterns, such as prompt injection, obfuscation, unauthorized network exfiltration, or persistence mechanisms, were found across any of the analyzed files.
- [SAFE]: External dependencies referenced (e.g., OR-Tools, Ruptures, OSMnx) are reputable, specialized packages for optimization, changepoint detection, and geospatial analysis respectively.
Audit Metadata