Summary of When “competency” in Reasoning Opens the Door to Vulnerability: Jailbreaking Llms Via Novel Complex Ciphers, by Divij Handa et al.

When “Competency” in Reasoning Opens the Door to Vulnerability: Jailbreaking LLMs via Novel Complex Ciphers

by Divij Handa, Zehua Zhang, Amir Saeidi, Shrinidhi Kumbhar, Chitta Baral

First submitted to arxiv on: 16 Feb 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary This paper investigates the paradoxical vulnerability of Large Language Models (LLMs) to novel jailbreaking attacks. As LLMs improve their reasoning abilities, they inadvertently become more susceptible to sophisticated attacks that encode malicious queries with custom ciphers. The authors introduce two attack techniques: Attacks using Custom Encryptions (ACE) and Layered Attacks using Custom Encryptions (LACE), which exploit the increased ability of LLMs to interpret complex instructions and decode encrypted text. They also develop CipherBench, a benchmark designed to evaluate LLMs’ accuracy in decoding benign text. The experiments reveal a critical trade-off: more capable LLMs are more vulnerable to jailbreaking attacks, with success rates escalating from 40% under ACE to 78% with LACE on GPT-4o. This highlights the importance of considering the increased vulnerability of advanced LLMs when designing safety training and evaluating their robustness.
Low	GrooveSquid.com (original content)	Low Difficulty Summary Large Language Models (LLMs) are getting better at understanding complex instructions and decoding secret messages. But, surprisingly, this makes them more vulnerable to sneaky attacks that try to trick them into doing things they shouldn’t do. The researchers found that as LLMs get smarter, they become more likely to fall for these clever tricks. They developed special techniques called ACE and LACE that can manipulate the LLMs into giving up their secrets. This is a big deal because it means that even if we try to make the LLMs safer, new attacks will come along and find ways to exploit their vulnerabilities.