PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails

Neal Mangaokar, Ashish Hooda, Jihye Choi, Shreyas Chandrashekaran, Kassem Fawaz, Somesh Jha, Atul Prakash


Abstract
Large language models (LLMs) are typically aligned to be harmless to humans. Unfortunately, recent work has shown that such models are susceptible to automated jailbreak attacks that induce them to generate harmful content. More recent LLMs often incorporate an additional layer of defense, a Guard Model, which is a second LLM that is designed to check and moderate the output response of the primary LLM. Our key contribution is to show a novel attack strategy, PRP, that is successful against several open-source (e.g., Llama 2) and closed-source (e.g., GPT 3.5) implementations of Guard Models. PRP leverages a two step prefix-based attack that operates by (a) constructing a universal adversarial prefix for the Guard Model, and (b) propagating this prefix to the response. We find that this procedure is effective across multiple threat models, including ones in which the adversary has no access to the Guard Model at all. Our work suggests that further advances are required on defenses and Guard Models before they can be considered effective. Code at https://github.com/AshishHoodaIITD/prp-llm-guard-rail-attack.
Anthology ID:
2024.acl-long.591
Volume:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
10960–10976
Language:
URL:
https://aclanthology.org/2024.acl-long.591
DOI:
10.18653/v1/2024.acl-long.591
Bibkey:
Cite (ACL):
Neal Mangaokar, Ashish Hooda, Jihye Choi, Shreyas Chandrashekaran, Kassem Fawaz, Somesh Jha, and Atul Prakash. 2024. PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10960–10976, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails (Mangaokar et al., ACL 2024)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2024.acl-long.591.pdf
Video:
 https://preview.aclanthology.org/add_acl24_videos/2024.acl-long.591.mp4