The OWASP Top 10 for LLM and Generative AI project , genai.owasp.org, team is thrilled to unveil the Gen AI Red Teaming Guide which provides a practical approach to evaluating LLM and Generative AI vulnerabilities—a new resource from our Red Teaming Initiative.
As Generative AI technologies like the Large Language Models (LLMs) evolve at breakneck speed, the security and ethical challenges they introduce are just as dynamic. Our guide aims to close this gap by offering a structured, risk-based methodology for assessing these AI systems and applications in real-world scenarios—covering everything from model-level vulnerabilities and prompt injection to system integration pitfalls and best practices for ensuring trustworthy AI deployments.
What You’ll Find Inside
- Holistic Focus: Coverage spans from model-level vulnerabilities (toxicity, bias) to system-level pitfalls (API misuse, data exposure).
- Cross-Functional Insights: Because AI security demands collaboration across data science, cybersecurity, ethics, and legal teams, we’ve included best practices that speak to each role.
- Blueprint & Techniques: Actionable steps and testing frameworks you can adapt to suit your organization’s unique threat landscape, covering everything from agentic AI challenges to continuous monitoring.
- Best Practices: Learn how mature organizations integrate cross-functional teams (Security, AI/ML, Legal, etc.) to tackle everything from compliance and incident response to bias and toxicity detection.
How to Use This Guide
- Start with the Quick Start Guide
Get a high-level grasp of what GenAI Red Teaming entails—perfect for newcomers or anyone looking for a step-by-step introduction. - Explore the Threat Modeling & Risks Section
Identify the threats most relevant to your use case. Focus on issues like prompt injection if you run a public chatbot, or data leakage if you handle sensitive IP. - Dive into the Blueprint & Techniques
Once you know your specific risks, use our recommended test categories to see how your AI systems hold up. - Consult Best Practices & Continuous Monitoring
Learn how to integrate findings into your organization’s larger security posture. This guide emphasizes continual oversight—no AI model is ever truly “done” or “secure.” - Customize & Evolve
Every environment is different. We encourage you to adapt our checklists, frameworks, and references to fit your specific needs—and share your experiences so we can improve together.
Your Feedback Matters
This is just the beginning. We’re aiming to refine this guide through community input—especially yours. By sharing your real-world experiences, pain points, and success stories, you’ll help us shape a resource that meets the evolving needs of AI security practitioners.
- Structure & Organization: Does the overall framework make sense? Any sections that feel redundant or missing?
- Gaps & Omissions: Are there critical risks not addressed? Features or attack vectors we overlooked.
- Future Directions: What specific challenges are you facing? Where should we focus our next research and guidance
Get Involved
We welcome your thoughts and suggestions. Join the OWASP Top 10 for LLM and Generative AI Community. Request an OWASP slack invitation OWASP slack invitation
, join the OWASP Slack workspace, and add the working group’s channel #team-llm-redteam.
Our goal is to build a living, community-driven playbook that helps everyone—from cybersecurity pros to AI/ML engineers—safely harness the benefits of Generative AI.
Dive in, explore the quick wins in our Quick Start Guide, and then roll up your sleeves with in-depth content on threat modeling, agentic vulnerabilities, and more. Let’s work together to keep AI systems secure, transparent, and aligned with our collective values. We look forward to your contributions and insights as we shape the future of GenAI Red Teaming!
