Secure Your Agent Configuration Layer

Prompt injection is the leading attack vector against AI agents. While traditional security tools scan your application code, they completely miss vulnerabilities hidden within your SKILL.md files, system prompts, and agent configurations. This specialized auditor fills that gap by analyzing the prompt/agent configuration layer where injection attacks, secret leakage, and tool abuse originate.

Advanced Threat Detection

The auditor scans for five critical risk categories using pattern-matching logic optimized for LLM instructions:

• Direct & Indirect Injection: Detects unsanitized shell execution, system prompt override patterns, and unsafe template rendering.
• Secret Exposure: Flags hardcoded API keys, tokens, and environment variable leaks within prompt text.
• Overly Permissive Access: Identifies unrestricted filesystem access, missing domain allowlists for web tools, and unbounded recursion loops.
• Data Exfiltration: Roots out unauthorized web POST capabilities and unsafe file upload patterns.

Why Developers Need This

Prompting an AI yourself to "find security holes" is unreliable and lacks a structured framework. This skill provides a reproducible, severity-scored report with specific line references and actionable remediation steps. It supports major agent frameworks including Claude Code, Cursor, and GitHub Copilot, ensuring your custom skills are production-ready and compliant with security standards like OWASP LLM Top 10.