skills.rest
Skobyn
SkobynCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

hunt-llm-ai

Detect security vulnerabilities in LLM/AI applications by analyzing prompt handling and data exfiltration channels.

Updated Jun 24, 2026
Search Tags:#AI security#LLM#prompt injection#data exfiltration#security vulnerability
One-click install
npx skills add https://github.com/Skobyn/talon --skill hunt-llm-ai-skobyn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hunt-llm-ai
Source: https://github.com/Skobyn/talon/tree/main/skills/hunt-llm-ai
Command: npx skills add https://github.com/Skobyn/talon --skill hunt-llm-ai-skobyn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill identifies and mitigates security vulnerabilities within LLM/AI applications, including prompt injection, indirect injection, and exfiltration risks.

Core Features & Use Cases

  • LLM Bug Hunting: Identifies bugs such as prompt injection, ASCII smuggling, and tool-use exfiltration.
  • Detection of Security Risks: Monitors for OOB callbacks, verbatim-reproducible system-prompt leaks, and cross-tenant data leaks.
  • Use Case: For a company using a chatbot, this Skill can detect vulnerabilities that could lead to data breaches or unauthorized actions.

Quick Start

Run the 'hunt-llm-ai' skill to scan your AI-powered chatbot for common security 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 detect prompt injection vulnerabilities in my LLM application?▼

Detect prompt injection vulnerabilities in your LLM application by analyzing prompt handling for indirect injection and ASCII smuggling. This prevents malicious inputs from manipulating model behavior or triggering unauthorized actions.

What is an LLM data exfiltration channel and how does it work?▼

An LLM data exfiltration channel is a pathway where sensitive information leaks through tool-use or OOB callbacks. It works by exploiting AI architecture to send user data to unauthorized external endpoints.

How do I scan my AI chatbot for cross-tenant data leaks?▼

Scan your AI chatbot for cross-tenant data leaks by analyzing cross-tenant data handling protocols. This detects vulnerabilities where one tenant's data becomes accessible to another through shared model contexts.

Does my AI security team need specific protocols to prevent system-prompt leaks?▼

Preventing system-prompt leaks requires understanding AI architecture and security protocols to monitor for verbatim-reproducible leaks. Your team needs this security protocol knowledge to ensure LLMs do not compromise system integrity.

What is the best way to secure LLM tool-use against security vulnerabilities?▼

Secure LLM tool-use against security vulnerabilities by analyzing data exfiltration channels and prompt handling. This approach mitigates tool-use exfiltration and prevents bugs that compromise user data or system integrity.

Related Skills

Explore More Software Engineering Skills→
popo0407popo0407

security

Enforce security and compliance policies for software development and data handling.

Community
Intermediate
dreadnodedreadnode
11

url-prompt-injection

Detect cross-site prompt injection vulnerabilities in AI chatbot web interfaces.

Official
Intermediate
barrydobsonbarrydobson

devops

Advocate DevOps principles including CI/CD, IaC, automated testing, monitoring, and security scanning for delivery pipelines.

Community
Intermediate
h4vzzh4vzz
33

static-application-security-testing

Scan source code for security vulnerabilities and generate SARIF reports.

Community
Advanced