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agentic-security-audit

Audit AI agent configurations and LLM integrations for OWASP Top 10 security risks.

3|5|Updated Jan 8, 2026
Search Tags:#llm#mcp#ai-security#prompt-injection#owasp-top-10#agent-audit
One-click install
npx skills add https://github.com/sparkfabrik/sf-awesome-copilot --skill agentic-security-audit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-security-audit
Source: https://github.com/sparkfabrik/sf-awesome-copilot/tree/main/skills/system/agentic-security-audit
Command: npx skills add https://github.com/sparkfabrik/sf-awesome-copilot --skill agentic-security-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Audits AI agent configurations, instruction files, and LLM integration for security risks aligned with the OWASP Top 10 for Agentic Applications (2026). It helps identify insecure patterns, review MCP/tool configurations, and enforce trust boundaries across agentic stacks.

Core Features & Use Cases

  • Discover AI instruction files, MCP configurations, tool definitions, and inter-agent communication points.
  • Assess integration boundaries and risk patterns, mapping findings to ASI01–ASI10 with actionable remediation guidance.
  • Complement the code-security audit skill by auditing the AI-integration layer (prompts, tools, and data flows) rather than application code.

Quick Start

Provide an initial audit scope and run Phase 1 discovery to locate AI instruction files, MCP configurations, and inter-agent tools.

Frequently Asked Questions about agentic-security-audit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit AI agent configurations for OWASP Top 10 security risks?▼

AI prompt injection risks are identified by assessing integration boundaries and risk patterns within LLM instruction files and inter-agent communication points. The audit maps findings to OWASP ASI01–ASI10 categories with actionable remediation guidance.

What's the best way to review MCP configurations for insecure patterns in LLM integrations?▼

Auditing LLM integrations requires providing an initial audit scope for the discovery phase to locate AI instruction files, MCP configurations, and inter-agent tools. This discovers agentic components before the review phase assesses their security risks and trust boundaries.

Does this agentic security audit check application code or only AI integration layers?▼

This agentic security audit checks the AI-integration layer, reviewing prompts, tools, and data flows rather than application code. It complements code-security audit skills by focusing entirely on trust boundaries and insecure patterns across agentic components.

Why do I need a dedicated security audit for AI agents and LLM tools instead of standard code scanning?▼

A dedicated security audit is needed because standard code scanning does not evaluate AI instruction files, MCP configurations, or prompt injection risks. Auditing the agentic layer enforces trust boundaries and maps vulnerabilities specific to LLM integrations using the OWASP Top 10.

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