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arXiv · 2405.14189

Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization

Yihao Huang·Chong Wang·Xiaojun Jia·Qing Guo·Felix Juefei-Xu·Jian Zhang·Geguang Pu·Yang Liu
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Abstract

Universal goal hijacking is a kind of prompt injection attack that forces LLMs to return a target malicious response for arbitrary normal user prompts. The previous methods achieve high attack performance while being too cumbersome and time-consuming. Also, they have concentrated solely on optimization algorithms, overlooking the crucial role of the prompt. To this end, we propose a method called POUGH that incorporates an efficient optimization algorithm and two semantics-guided prompt organization strategies. Specifically, our method starts with a sampling strategy to select representative prompts from a candidate pool, followed by a ranking strategy that prioritizes them. Given the sequentially ranked prompts, our method employs an iterative optimization algorithm to generate a fixed suffix that can concatenate to arbitrary user prompts for universal goal hijacking. Experiments conducted on four popular LLMs and ten types of target responses verified the effectiveness.

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Yihao Huang, Chong Wang, Xiaojun Jia, Qing Guo, Felix Juefei-Xu, Jian Zhang, Geguang Pu, Yang Liu. 2024-05-23. Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization. https://arxiv.org/abs/2405.14189

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