Jailbreaking Large Language Models with Symbolic Mathematics

🔑 Jailbreaking Large Language Models with Symbolic Mathematics

This research paper investigates a new vulnerability in AI safety mechanisms by introducing MathPrompt, a technique that utilizes symbolic mathematics to bypass LLM safety measures. The paper demonstrates that encoding harmful natural language prompts into mathematical problems allows LLMs to generate harmful content, despite being trained to prevent it. Experiments across 13 state-of-the-art LLMs show a high success rate for MathPrompt, indicating that existing safety measures are not effective against mathematically encoded inputs. The study emphasizes the need for more comprehensive safety mechanisms that can handle various input types and their associated risks.

📎 Link to paper