Injection Vulnerability Awareness

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Provides domain-specific guidance on recognizing and fixing the most common security flaws often found in AI-generated code. It explains why AI models default to insecure patterns like string concatenation and provides clear, production-ready alternatives using parameterized queries, secure process spawning, and proper output encoding. This skill is essential for developers auditing AI-assisted work to prevent critical breaches, data exfiltration, and unauthorized system access by implementing robust input validation and modern security headers.

Características Principales

• Offers checklists for recognizing 'red flag' patterns in generated snippets.
• 1 GitHub stars
• Outlines real-world attack scenarios and their potential business impact.
• Analyzes AI-specific causes for SQL, command, and XSS injection flaws.
• Provides side-by-side comparisons of vulnerable and secure code implementations.
• Includes framework-specific security patterns for Convex and Next.js.

Casos de Uso

• Reviewing and securing database query logic generated by AI assistants.
• Replacing dangerous shell execution calls with secure argument-based alternatives.
• Implementing robust HTML escaping and Content Security Policies in web applications.