hunt-llm-ai

Detect prompt injection and agentic tool misuse against OWASP ASI standards.

13|2|Updated Jun 1, 2026
One-click install
npx skills add https://github.com/pdparchitect/rook --skill hunt-llm-ai-pdparchitect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hunt-llm-ai
Source: https://github.com/pdparchitect/rook/tree/main/skills/hunt-llm-ai
Command: npx skills add https://github.com/pdparchitect/rook --skill hunt-llm-ai-pdparchitect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the critical security gaps in LLM-backed applications, such as prompt injection, unauthorized data access, and agentic tool misuse, which are often overlooked in standard security audits.

Core Features & Use Cases

  • Vulnerability Hunting: Detects prompt injection chains, indirect injection via documents, and ASCII smuggling.
  • Agentic Security Analysis: Evaluates AI agents against the OWASP ASI 2026 framework, including goal hijacking and tool misuse.
  • Use Case: Use this skill to audit a customer support chatbot that has access to internal databases to ensure it cannot be manipulated into revealing private user data or executing unauthorized actions.

Quick Start

Use the hunt-llm-ai skill to audit the target chatbot endpoint for prompt injection and IDOR vulnerabilities.

Frequently Asked Questions about hunt-llm-ai

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

FAQPage Schema
How do I audit an LLM chatbot for prompt injection and data exfiltration vulnerabilities?

To audit an LLM chatbot for prompt injection and data exfiltration, you systematically test model inputs and tool-use interfaces. This identifies injection chains and verifies potential impact against OWASP ASI security standards.

What is indirect prompt injection in RAG endpoints and how is it detected?

Indirect prompt injection in RAG endpoints occurs when malicious instructions are hidden in retrieved documents. It is detected by testing model inputs for document-based injection chains and ASCII smuggling techniques.

How do I test autonomous AI agents for agentic tool misuse and privilege escalation?

To test autonomous AI agents for agentic tool misuse and privilege escalation, evaluate the system against the OWASP ASI 2026 framework. This verifies goal hijacking vulnerabilities and unauthorized tool execution.

Does this security audit evaluate systems against the OWASP ASI standard?

Yes, this security audit evaluates AI agents against the OWASP ASI 2026 framework. It systematically tests chatbots, RAG endpoints, and autonomous agents to verify security vulnerabilities and potential impact.

What is the best way to secure a customer support chatbot with internal database access?

The best way to secure a customer support chatbot with internal database access is auditing its endpoints for prompt injection and IDOR vulnerabilities. This ensures it cannot be manipulated into revealing private user data.