Garak

garak is your open-source solution for assessing Large Language Model (LLM) security. It acts as a vulnerability scanner, helping you evaluate the security posture of your LLM models or systems. The tool provides a comprehensive suite of dozens of plugins and thousands of prompts designed to probe for weaknesses. You can use garak to proactively identify potential security risks before they are exploited. Its primary goal is to raise the standard for LLM security, making robust security practices accessible to everyone. The software is actively maintained by NVIDIA and a community of contributors, ensuring it stays current with emerging threats.

Getting started with garak is straightforward. You can easily install it and find extensive support through its user guide and reference documentation. The command-line interface is designed to be user-friendly. For community support and discussions, the garak Discord server is active, and GitHub issues receive prompt attention. NVIDIA also provides an email contact for further assistance. Many organizations have successfully integrated garak into their development workflows, and it is frequently cited as an industry standard in independent reviews. You should consider incorporating garak into your LLM security strategy.

The project is backed by NVIDIA, reflecting its importance in the AI security space. As a research-driven initiative, it continues to evolve. The content provided on the website is available under the Apache 2.0 License, promoting open access and collaboration. By using garak, you contribute to a more secure AI ecosystem. You gain the ability to test your LLMs against a wide array of known vulnerabilities, ensuring better protection against prompt injection, data leakage, and other common LLM exploits. This proactive approach is essential for building trust and reliability in AI applications.