The video showcases a newly developed AI red teaming tool that leverages OpenRouter to test multiple AI models like Gemini and Grok for vulnerabilities by sending jailbreak and harmful prompts, logging their responses to evaluate safety mechanisms. It also features an AI-powered payload generator for creating novel attack vectors, highlighting the tool’s potential for automated discovery of AI weaknesses while emphasizing responsible, research-focused use and ongoing development.
In this video, the creator introduces an AI red team tool they developed over the weekend, which is a fork of an existing open-source project called OpenCode. The tool leverages OpenRouter to access various AI models, allowing users to test and experiment with different AI systems. The main purpose of the tool is to perform red teaming on AI models by sending them potentially harmful or jailbreak prompts to evaluate their safety mechanisms. The creator demonstrates different testing modes such as single model tests, batch tests, and specialized attack techniques like “god mode” and “response format attacks.”
The video showcases how the tool can send crafted payloads to models like Gemini 2.0 Flash and Grok 3, observing their responses to potentially dangerous queries. For instance, Gemini 2.0 Flash successfully blocks a harmful request, while Grok 3 and Grok 4 models are shown to be vulnerable, providing detailed instructions on creating dangerous substances. The tool logs all interactions, enabling users to review responses and identify which models are susceptible to jailbreaks or prompt injections. Batch testing allows simultaneous evaluation of multiple models, saving time and providing comparative insights into their vulnerabilities.
Another feature demonstrated is the payload generator, which uses AI models like GPT-5 to create novel attack vectors automatically. This function attempts to generate new jailbreak prompts or payloads that can be tested against other models. The creator experiments with generating both string and code-based payloads, such as instructions for creating polymorphic viruses, to see if these can bypass AI safety filters. Although some generated payloads do not always work perfectly, this feature highlights the potential for automated discovery of new vulnerabilities in AI systems.
The creator also experiments with creative uses of the tool, such as generating detailed system prompts for image generation models like Grok 3 Magic Card. While this is more for fun and exploration, it demonstrates the flexibility of the tool beyond just security testing. The video emphasizes that this is a controlled environment for research and experimentation, not intended for malicious use. The creator plans to continue developing the tool, adding features like auto mode for iterative payload testing and multi-step jailbreak chains to enhance its capabilities.
In conclusion, the video presents a powerful and flexible AI red teaming tool that allows users to probe the safety and robustness of various AI models. The creator encourages community involvement through contributions and pull requests to improve the tool. They also hint at future content and live streams to further explore AI security challenges. Overall, the tool offers an accessible way for researchers and enthusiasts to experiment with AI vulnerabilities, fostering a deeper understanding of AI safety and prompting further innovation in the field.