AI Agent Security Audit

Comprehensive security auditing for AI agent deployments. Detects vulnerabilities across prompt handling, tool permissions, skill behavior, credential management, and runtime operations.

Usage

Invoke with a target agent configuration path or skill directory to scan:

audit: scan /path/to/agent/config
audit: review installed skills
audit: monitor runtime behavior for 30 minutes

Execution Flow

1. Configuration Audit — Parse agent config YAML, enumerate permissions, identify over-privileged tool access
2. Prompt Injection Test — Run 12 injection patterns (DAN, encoding bypass, role confusion, token smuggling) and score resilience
3. Skill Scan — Analyze each installed skill's SKILL.md for suspicious patterns (eval(), shell_exec, credential references, network requests)
4. Credential Hygiene — Scan workspace for hardcoded tokens, API keys, private keys in plaintext files
5. Runtime Monitor — Observe agent behavior for N minutes, flag any unexpected tool calls, network connections, or file access patterns
6. Generate Report — Risk score 0-100, criticality matrix, prioritized remediation steps

Output Format

# Security Audit Report
- **Audit Date**: YYYY-MM-DD HH:MM
- **Audit Scope**: [target]
- **Overall Risk Score**: 67/100 (MEDIUM)

## Critical Findings (2)
- [CRITICAL] Unrestricted shell_executor access allows arbitrary command execution
- [CRITICAL] Skill "data-export" sends data to external endpoint without user consent

## High Findings (3)
- ...

## Recommendations
1. Add allowlist for shell_executor commands
2. Sandbox "data-export" skill network calls
3. ...

Notes

• Requires read access to agent config directory and installed skills path
• Runtime monitoring requires agent process access
• All findings include file paths and line numbers for traceability
• Recommended for any production agent deployment, especially those handling user data or financial operations