loom-data-validation
Pass
Audited by Gen Agent Trust Hub on Apr 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as an educational and structural guide for implementing data validation and sanitization logic.
- [SAFE]: The provided code snippets demonstrate industry-standard security practices, such as context-aware output encoding and whitelist-based input sanitization.
- [SAFE]: Implementation of path traversal prevention using
path.resolveand base path verification is a documented security best practice. - [SAFE]: All referenced third-party libraries (Zod, Pydantic, Ajv, DOMPurify, Great Expectations) are widely-used, reputable packages within the security and development communities.
- [SAFE]: SQL sanitization examples are accompanied by explicit warnings to prioritize parameterized queries, demonstrating a security-first approach.
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