The report also shares lessons learned from the AI Red Team's work, emphasizing the need for AI subject matter expertise in addressing complex attacks on AI systems. It also highlights the importance of incorporating red teaming into work feeds to fuel research and product development efforts, and the effectiveness of traditional security controls in mitigating risk. Google recommends regular red team exercises for all organizations to help secure critical AI deployments in large public systems.
Key takeaways:
- Google's AI Red Team is a group of hackers that simulate various adversaries to test the security of AI systems. They use tactics, techniques, and procedures (TTPs) to test system defenses and identify opportunities to improve safety.
- The report discusses three main areas: the importance of red teaming in the context of AI systems, the types of attacks AI red teams simulate, and the lessons learned from their work.
- Some of the common types of red team attacks on AI systems include prompt attacks, training data extraction, backdooring the model, adversarial examples, data poisoning, and exfiltration.
- Google recommends that every organization conduct regular red team exercises to help secure critical AI deployments in large public systems. They believe that incorporating red teaming into work feeds can help fuel research and product development efforts.