Generative AI and Large Language Model (LLM) Prompt Hacking: Exposing Systemic Vulnerabilities of LLMs to Enhance AI Security Through Innovative Red Teaming Competitions | A Conversation with Sander Schulhoff | Redefining CyberSecurity with Sean Martin cover art

Generative AI and Large Language Model (LLM) Prompt Hacking: Exposing Systemic Vulnerabilities of LLMs to Enhance AI Security Through Innovative Red Teaming Competitions | A Conversation with Sander Schulhoff | Redefining CyberSecurity with Sean Martin

Generative AI and Large Language Model (LLM) Prompt Hacking: Exposing Systemic Vulnerabilities of LLMs to Enhance AI Security Through Innovative Red Teaming Competitions | A Conversation with Sander Schulhoff | Redefining CyberSecurity with Sean Martin

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 Guest: Sander Schulhoff, CEO and Co-Founder, Learn Prompting [@learnprompting]On LinkedIn | https://www.linkedin.com/in/sander-schulhoff/____________________________Host: Sean Martin, Co-Founder at ITSPmagazine [@ITSPmagazine] and Host of Redefining CyberSecurity Podcast [@RedefiningCyber]On ITSPmagazine | https://www.itspmagazine.com/sean-martinView This Show's Sponsors___________________________Episode NotesIn this episode of Redefining CyberSecurity, host Sean Martin engages with Sander Schulhoff, CEO and Co-Founder of Learn Prompting and a researcher at the University of Maryland. The discussion focuses on the critical intersection of artificial intelligence (AI) and cybersecurity, particularly the role of prompt engineering in the evolving AI landscape. Schulhoff's extensive work in natural language processing (NLP) and deep reinforcement learning provides a robust foundation for this insightful conversation.Prompt engineering, a vital part of AI research and development, involves creating effective input prompts that guide AI models to produce desired outputs. Schulhoff explains that the diversity of prompt techniques is vast and includes methods like the chain of thought, which helps AI articulate its reasoning steps to solve complex problems. However, the conversation highlights that there are significant security concerns that accompany these techniques.One such concern is the vulnerability of systems when they integrate user-generated prompts with AI models, especially those prompts that can execute code or interact with external databases. Security flaws can arise when these systems are not adequately sandboxed or otherwise protected, as demonstrated by Schulhoff through real-world examples like MathGPT, a tool that was exploited to run arbitrary code by injecting malicious prompts into the AI’s input.Schulhoff's insights into the AI Village at DEF CON underline the community's nascent but growing focus on AI security. He notes an intriguing pattern: many participants in AI-specific red teaming events were beginners, which suggests a gap in traditional red teamer familiarity with AI systems. This gap necessitates targeted education and training, something Schulhoff is actively pursuing through initiatives at Learn Prompting.The discussion also covers the importance of studying and understanding the potential risks posed by AI models in business applications. With AI increasingly integrated into various sectors, including security, the stakes for anticipating and mitigating risks are high. Schulhoff mentions that his team is working on Hack A Prompt, a global prompt injection competition aimed at crowdsourcing diverse attack strategies. This initiative not only helps model developers understand potential vulnerabilities but also furthers the collective knowledge base necessary for building more secure AI systems.As AI continues to intersect with various business processes and applications, the role of security becomes paramount. This episode underscores the need for collaboration between prompt engineers, security professionals, and organizations at large to ensure that AI advancements are accompanied by robust, proactive security measures. By fostering awareness and education, and through collaborative competitions like Hack A Prompt, the community can better prepare for the multifaceted challenges that AI security presents.Top Questions AddressedWhat are the key security concerns associated with prompt engineering?How can organizations ensure the security of AI systems that integrate user-generated prompts?What steps can be taken to bridge the knowledge gap in AI security among traditional security professionals?___________________________SponsorsImperva: https://itspm.ag/imperva277117988LevelBlue: https://itspm.ag/attcybersecurity-3jdk3___________________________Watch this and other videos on ITSPmagazine's YouTube ChannelRedefining CyberSecurity Podcast with Sean Martin, CISSP playlist:📺 https://www.youtube.com/playlist?list=PLnYu0psdcllS9aVGdiakVss9u7xgYDKYqITSPmagazine YouTube Channel:📺 https://www.youtube.com/@itspmagazineBe sure to share and subscribe!___________________________ResourcesThe Prompt Report: A Systematic Survey of Prompting Techniques: https://trigaten.github.io/Prompt_Survey_Site/HackAPrompt competition: https://www.aicrowd.com/challenges/hackaprompt-2023HackAPrompt results published in this paper "Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition EMNLP 2023": https://paper.hackaprompt.com/___________________________To see and hear more Redefining CyberSecurity content on ITSPmagazine, visit: https://www.itspmagazine.com/redefining-cybersecurity-podcastAre you interested in sponsoring this show with an ad placement in the podcast?Learn More 👉 https://itspm.ag/podadplc Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of ...
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