llm-risk-assess

Assess LLM application security risks using the OWASP Top 10 for LLMs 2025.

Updated Mar 24, 2023

Search Tags:#security #owasp #llm #risk-assessment #threat-modeling #red-team #prompt-injection

Ready to run

npx skills add https://github.com/j4hr3n/dotfiles --skill llm-risk-assess-j4hr3n

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: llm-risk-assess
Source: https://github.com/j4hr3n/dotfiles/tree/main/configs/claude-code/skills/llm-risk-assess
Command: npx skills add https://github.com/j4hr3n/dotfiles --skill llm-risk-assess-j4hr3n

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify and mitigate security risks in LLM-based applications by applying a structured OWASP Top 10 for LLMs (2025) assessment.

Core Features & Use Cases

Threat modeling and architecture mapping for LLM pipelines, RAG components, and plugin integrations.
Automated security testing including prompt-injection probes, secret scanning, and vector database checks.
Red Team testing and remediation planning with concrete evidence and risk-based mitigations.
Real-world use cases include chatbots, AI agents, and RAG-powered applications in production environments.

Quick Start

Run the LLM risk assessment on your RAG-enabled chatbot to surface prompt-injection and data-disclosure risks.

Frequently Asked Questions about llm-risk-assess

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

FAQPage Schema

How do I assess LLM application security risks using OWASP Top 10?▼

Threat modeling for RAG pipelines involves mapping data flows and integrations to identify security risks. This Skill applies the OWASP Top 10 for LLMs to evaluate vector database checks, plugin integrations, and data-disclosure paths within your retrieval pipeline.

Can I run automated prompt-injection testing on my LLM chatbot?▼

This Skill handles LLM threat modeling across chatbots, AI agents, and RAG-powered applications. It maps pipeline architectures and plugin integrations to identify security risks, providing repeatable artifacts like threat models and risk-based remediation guidance.

What is the best way to perform red-team testing on AI agents?▼

Red-team testing for LLM applications produces structured artifacts including threat models, automated test results, and remediation checklists. These outputs provide concrete evidence of security risks and deliver risk-based mitigations for chatbot and RAG pipeline vulnerabilities.

Does OWASP LLM risk assessment cover vector database security checks?▼

OWASP LLM risk assessment covers vector database security checks as part of its automated testing suite. It evaluates your RAG components to surface data-disclosure risks and identify vulnerabilities within the vector database integrations of your LLM pipeline.