In this episode we discuss the critical security flaw of indirect prompt injection in generative AI (GenAI) systems. Our guests explain how attackers can manipulate these systems by inserting malicious instructions into the data they access, such as emails and documents. This can lead to various issues, including disinformation, phishing attacks and denial of service. They also emphasize the importance of data hygiene, user training and technical safeguards to mitigate these risks, and they further discuss how the integration of large language models (LLMs) into organizational systems increases the attack surface. In summary RAG is vulnerable unless you take strong mitigating actions.
00:00 Introduction
01:48 Understanding RAG and it’s vulnerabilities
04:42 The significance of Indirect Prompt Injection
07:28 Attack vectors and real-world implications
10:04 Mitigation strategies for indirect prompt injection
12:45 The future of AI security and agentic processes
28:27 The risks and rewards of agentic design
33:50 Navigating phishing in AI systems
35:53 The role of public policy in AI safety
41:55 Automating risk analysis in AI
44:44 Future research directions in AI risks
48:08 Reinforcement learning agents and automation
48:53 AI in cybersecurity: attacking and defending
50:21 The ethics and risks of AI technology
52:51 The lightning Round
1:01:53 Outro
Music: "Fire" by crimson.
