AI Red Teaming in 2024 and Beyond

Host Caleb Sima and Ashish Rajan caught up with experts Daniel Miessler (Unsupervised Learning), Joseph Thacker (Principal AI Engineer, AppOmni) to talk about the true vulnerabilities of AI applications, how prompt injection is evolving, new attack vectors through images, audio, and video and predictions for AI-powered hacking and its implications for enterprise security. Whether you're a red teamer, a blue teamer, or simply curious about AI's impact on cybersecurity, this episode is packed with expert insights, practical advice, and future forecasts. Don’t miss out on understanding how attackers leverage AI to exploit vulnerabilities—and how defenders can stay ahead. Questions asked: (00:00) Introduction (02:11) A bit about Daniel Miessler (02:22) A bit about Rez0 (03:02) Intersection of Red Team and AI (07:06) Is red teaming AI different? (09:42) Humans or AI: Better at Prompt Injection? (13:32) What is a security vulnerability for a LLM? (14:55) Jailbreaking vs Prompt Injecting LLMs (24:17) Whats new for Red Teaming with AI? (25:58) Prompt injection in Multimodal Models (27:50) How Vulnerable are AI Models? (29:07) Is Prompt Injection the only real threat? (31:01) Predictions on how prompt injection will be stored or used (32:45) What’s changed in the Bug Bounty Toolkit? (35:35) How would internal red teams change? (36:53) What can enterprises do to protect themselves? (41:43) Where to start in this space? (47:53) What are our guests most excited about in AI? Resources Daniel's Webpage - Unsupervised Learning Joseph's Website

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