The past 24 hours have been filled with a variety of groundbreaking developments in the world of Machine Learning and Artificial Intelligence. From new vulnerabilities of Large Language Models (LLMs) integrated into various applications to targeted adversarial prompting, such as Prompt Injection (PI) attacks, to the exploration of ChatGPT Jailbreaking and AI Safety Nerfing, the possibilities of AI are growing ever more expansive.
Here are the key takeaways from the highlighted videos from the past 24 hours:
A new attack vector, Indirect Prompt Injection, enables adversaries to remotely exploit LLM-integrated applications by strategically injecting prompts into data likely to be retrieved.
A comprehensive taxonomy of the impacts and vulnerabilities of these attacks, including data theft, worming, and information ecosystem contamination, has been developed.
Practical viability of Indirect Prompt Injection attacks against real-world systems and synthetic applications built on GPT-4 has been demonstrated.
Solutions, the difficulty of detecting prompt injection attacks, and the need for separating instruction and data channels have been discussed.
Welcome to the latest installment of our series, ChatGPT! In this edition, we explore the new threat of Indirect Prompt Injection Exploits and learn how to stay safe from it. Scroll down to view the highlighted videos to learn more about the implications of this new attack vector, as well as potential solutions for defending against it.
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