Summary of All in How You Ask For It: Simple Black-box Method For Jailbreak Attacks, by Kazuhiro Takemoto
All in How You Ask for It: Simple Black-Box Method for Jailbreak Attacks
by Kazuhiro Takemoto
First submitted to arxiv on: 18 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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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 study introduces a straightforward method for efficiently crafting “jailbreak” prompts that can circumvent safeguards in Large Language Models (LLMs) like ChatGPT. The approach iteratively transforms harmful prompts into benign expressions, leveraging the target LLM’s ability to autonomously generate expressions that evade safeguards. The method achieved an attack success rate exceeding 80% within an average of five iterations for forbidden questions on both GPT-3.5 and GPT-4 versions of ChatGPT, as well as Gemini-Pro. The generated prompts were naturally-worded, succinct, and challenging to defend against, underscoring the heightened risk posed by black-box jailbreak attacks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study helps us understand how computers can generate bad things to say using big language models like ChatGPT. They found a way to make these models say nice things instead of mean things. This is important because it means that someone could use this method to trick the model into saying something bad, even if there are rules in place to stop them. The researchers tested their idea on three different versions of ChatGPT and showed that it worked well. This is a concern because it could lead to problems. |
Keywords
» Artificial intelligence » Gemini » Gpt
