python-aurora
Pass
Audited by Gen Agent Trust Hub on Sep 24, 2026
Risk Level: SAFE
Full Analysis
- Secure Authentication Flow: The skill implements a robust authentication pattern using Vercel OIDC tokens and AWS STS to assume IAM roles. This approach provides temporary, scoped credentials and avoids the risks associated with hardcoded secrets or long-lived API keys.
- SQL Injection Mitigation: The instructions and examples explicitly mandate the use of parameterized query syntax ($1, $2) and forbid the use of f-strings for SQL generation. This is a critical security practice that prevents SQL injection vulnerabilities when handling user-provided data.
- Encrypted Database Connections: The guidelines require enabling SSL (ssl='require') for all database connections, ensuring that sensitive data transmitted between the application and the Aurora cluster is encrypted in transit.
- Trusted Dependencies: The skill utilizes well-known, industry-standard libraries such as
boto3(AWS SDK) andasyncpg(PostgreSQL driver), alongside the officialvercelSDK. These resources are appropriate and expected for the skill's stated purpose.
Audit Metadata