llm-risk-assess
Comprehensive LLM security assessment against OWASP Top 10 for LLM Applications 2025. Use when reviewing LLM-integrated applications, RAG pipelines, chatbots, AI agents, or GenAI features. Covers prompt injection, data poisoning, supply chain, excessive agency, and more with real-world attack scenarios and testing methodologies.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owasp/secure-agent-playbook --skill llm-risk-assess- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads llm-risk-assess automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
LLM Risk Assessment (2025)
Comprehensive evaluation of LLM applications against OWASP Top 10 for LLM Applications 2025. Follow the detailed procedure in plays/llm-risk-assess.md.
Steps
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Architecture & Threat Modeling
- Map LLM provider (OpenAI, Anthropic, local models)
- Document data flows: user input → preprocessing → prompt construction → LLM → output processing → actions
- Identify RAG components, tool integrations, memory systems
- Define trust boundaries and attack surfaces
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Automated Security Testing
- Run prompt injection probes (Garak, Giskard, custom scripts)
- Test output handling vulnerabilities
- Scan for secrets in prompts and configurations
- Validate vector database security
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Assess All 10 OWASP LLM 2025 Risks with attack scenarios:
- LLM01 Prompt Injection — Direct/indirect injection, jailbreaks, goal hijacking, delimiter bypasses
- LLM02 Sensitive Information Disclosure — Training data leakage, PII exposure, system info extraction, memorized secrets
- LLM03 Supply Chain — Model poisoning, malicious dependencies, insecure plugins, provenance issues
- LLM04 Data and Model Poisoning — Training data poisoning, RAG poisoning, embedding manipulation
- LLM05 Improper Output Handling — XSS, command injection, SQLi, path traversal via LLM outputs
- LLM06 Excessive Agency — Unauthorized tool calls, permission escalation, dangerous action chains
- LLM07 System Prompt Leakage — Prompt extraction attacks, secret disclosure, instruction reverse engineering
- LLM08 Vector and Embedding Weaknesses — Adversarial embeddings, retrieval poisoning, similarity attacks
- LLM09 Misinformation — Hallucinations, authoritative presentation, grounding failures, harmful domains
- LLM10 Unbounded Consumption — Token exhaustion, cost attacks, resource exhaustion, DoS
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Red Team Testing
- Attempt real-world attack scenarios
- Test defense bypasses and evasion techniques
- Validate guardrails and safety controls
Output
Comprehensive LLM security report:
- Architecture diagram with trust boundaries
- Risk matrix (all 10 categories with severity/status)
- Detailed findings with proof-of-concept examples
- Red team test results and bypass techniques
- Remediation roadmap with code examples
- Defense validation checklist
OWASP References
- OWASP Top 10 for LLM Applications 2025
- OWASP AI Exchange (owaspai.org)
- OWASP AI Testing Guide
- OWASP Cheat Sheet: Prompt Injection Prevention
- OWASP Prompt Injection Taxonomy (Arcanum)
FAQ
What does the llm-risk-assess skill do?
Comprehensive LLM security assessment against OWASP Top 10 for LLM Applications 2025. Use when reviewing LLM-integrated applications, RAG pipelines, chatbots, AI agents, or GenAI features. Covers prompt injection, data poisoning, supply chain, excessive agency, and more with real-world attack scenarios and testing methodologies.
How do I install llm-risk-assess?
Run npx skills add https://github.com/owasp/secure-agent-playbook --skill llm-risk-assess in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/llm-risk-assess/ (personal) or .claude/skills/llm-risk-assess/ (project).
Which AI agents can use llm-risk-assess?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is llm-risk-assess safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains llm-risk-assess?
It is published by owasp in owasp/secure-agent-playbook. It has 155 recorded installs.
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