Researchers based in Washington and Chicago have developed ArtPrompt, a new way to circumvent the safety measures built into large language models (LLMs). According to the research paper ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs, chatbots such as GPT-3.5, GPT-4, Gemini, Claude, and Llama2 can be induced to respond to queries they are designed to reject using ASCII art prompts generated by their ArtPrompt tool. It is a simple and effective attack, and the paper provides examples of the ArtPrompt-induced chatbots advising on how to build bombs and make counterfeit money.
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To best understand ArtPrompt and how it works, it is probably simplest to check out the two examples provided by the research team behind the tool. In Figure 1 above, you can see that ArtPrompt easily sidesteps the protections of contemporary LLMs. The tool replaces the ‘safety word’ with an ASCII art representation of the word to form a new prompt. The LLM recognizes the ArtPrompt prompt output but sees no issue in responding, as the prompt doesn’t trigger any ethical or safety safeguards.
(Image credit: arXiv:2402.11753)
Another example provided in the research paper shows us how to successfully query an LLM about counterfeiting cash. Tricking a chatbot this way seems so basic, but the ArtPrompt developers assert how their tool fools today’s LLMs “effectively and efficiently.” Moreover, they claim it “outperforms all [other] attacks on average” and remains a practical, viable attack for multimodal language models for now.
