OWASP LLM AI Checklist

While the OWASP LLM Top 10 raises awareness about vulnerabilities, this comprehensive checklist gives you the concrete steps and controls to mitigate them. You can use it as the full-spectrum blueprint for turning a high-level security strategy into a practical reality.

Who is Behind It?

The OWASP LLM AI Checklist was created by the same global, community-driven organization as the OWASP Top 10: the Open Worldwide Application Security Project (OWASP). This volunteer-led foundation leverages the collective expertise of hundreds of security professionals to provide free, open-source resources. The checklist's credibility comes from its collaborative, real-world approach, making it an authoritative source for anyone concerned with AI security.

Its Purpose: A Practical Guide

The purpose of the OWASP LLM AI Checklist is to provide a standardized, actionable guide for security, engineering, and governance teams. It brings structure to the messy problem of deploying large language models without opening the door to security, privacy, and legal headaches. 

The checklist covers a wide array of considerations, from initial governance to technical implementation, ensuring every aspect of an AI system is planned for and secured. Its goal is to shift organizations from a reactive to a proactive and structured approach to AI security.

How to Use It

The checklist is designed to be used throughout the entire lifecycle of an AI system, from initial planning to ongoing maintenance. It's not just for a single team but for a cross-functional group including business leaders, engineers, and legal and compliance officers.

You can use the checklist to:

  1. Establish Governance: Define clear roles, responsibilities, and an overall risk appetite for your AI initiatives.
  2. Inventory AI Assets: Create a catalog of all AI systems and their components, so you can't be surprised by "shadow AI" in your organization.
  3. Threat Model: Proactively identify and address security risks before you even start building, helping to prevent costly mistakes.
  4. Secure the Pipeline: Implement robust controls for the entire AI pipeline, from data ingestion to model deployment, protecting against risks like training data poisoning.
  5. Test and Validate: Use the checklist's guidance to perform specialized testing, including adversarial testing and red teaming, to ensure your AI is resilient against attacks.

The document is organized into more than a dozen distinct focus areas, each with a series of detailed questions and best practices. 

Why You Need It

In a fast-moving world of AI, there's a false sense of security that AI tools are "just APIs." But large language models learn from what you give them, remember what they shouldn't, and generate outputs you can't always predict. 

This turns even simple use cases into major risk vectors. The OWASP LLM AI Checklist is the bridge between technical risk and organizational accountability. It empowers you to make informed decisions and build AI that is not only powerful but also trustworthy. 

By adopting this checklist, you are ensuring that your ambition is matched by your due diligence, building a secure, ethical, and resilient AI-first organization.