security

Scanning source code for prompt injection vulnerabilities requires analyzing prompts and configuration files to detect malicious injection points. This Skill identifies insecure output handling and enforces AI system compliance by providing attack scenarios and severity levels to prioritize fixes.

Detecting hardcoded secrets and API key exposure involves analyzing source code to identify sensitive data leaks. This Skill uncovers exposed credentials in AI systems, provides impact analysis for potential data breaches, and recommends best practices to mitigate risks.

Assessing supply chain risks involves analyzing dependencies to identify insecure components in your AI system. This Skill detects supply chain vulnerabilities, evaluates attack scenarios, and provides severity levels to ensure your application remains resilient against potential exploits.

Auditing configuration files for security flaws and data leaks is supported by analyzing system configurations to detect vulnerabilities. This Skill identifies insecure settings, hardcoded secrets, and data exposure points, ensuring AI systems comply with security standards and prevent breaches.

The security review process works with plain language commands like asking the AI to review code for vulnerabilities. It analyzes source code, configuration files, and prompts without requiring specialized syntax, making security auditing accessible to developers and reviewers.

A vulnerability assessment is needed when your LLM application uses API keys, processes sensitive data, or integrates external dependencies. Run this Skill to uncover security flaws like injection points and secret exposure before deployment to prevent potential exploits and data breaches.