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.

Indirect Prompt Injection: Generative AI’s Greatest Security Flaw | Centre for Emerging Technology and Security

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.