GenAI red teaming is a critical strategy for organizations seeking to enhance the security of GenAI systems. This process involves evaluating security and responsible AI risks to ensure the safe and ethical use of AI technology.


Red teaming GenAI systems is a complex and unique process that differs significantly from traditional AI systems or software [2]. GenAI red teams must assess security and responsible AI risks [1], such as fairness issues and inaccurate content generation [1]. GenAI systems are more probabilistic than traditional software [1], with multiple layers of non-determinism leading to diverse outputs [1]. Red teams must consider the probabilistic nature of GenAI systems and explore potential security risks and responsible AI failures simultaneously. The architecture of GenAI systems varies widely [1], making manual red-team probing challenging. Best practices for GenAI red teaming include using automation frameworks like PyRIT to enhance red teamers’ expertise [2], automate tasks, and identify blind spots.


Sharing GenAI red teaming resources across industries can promote responsible innovation with the latest AI advancements. By addressing security and responsible AI risks, organizations can leverage GenAI technology effectively and ethically. As GenAI systems continue to evolve, ongoing red teaming efforts will be essential to safeguard against potential risks and ensure the responsible use of AI technology.