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PromptFuzz: Harnessing Fuzzing Techniques for Robust Testing of Prompt Injection in LLMs

Source
IEEE Xplore (Security & AI Journals)(opens in a new tab)
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Summary

PromptFuzz is a testing framework that applies software fuzzing techniques to assess how robust LLMs are against prompt injection attacks. It runs in two stages, a prepare phase that selects seed prompts and collects few-shot examples, and a focus phase that generates diverse prompt injections. In a real-world competition it ranked 7th of over 4000 participants within 2 hours, and 92% of 50 popular LLM-integrated applications were exploitable with its prompts.

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