Jailbreak Attack
Jailbreak attacks exploit vulnerabilities in large language models (LLMs) and other AI systems, aiming to bypass safety mechanisms and elicit harmful or unintended outputs. Current research focuses on developing novel attack methods, such as those leveraging resource exhaustion, implicit references, or continuous optimization via image inputs, and evaluating their effectiveness against various model architectures (including LLMs, vision-language models, and multimodal models). Understanding and mitigating these attacks is crucial for ensuring the safe and responsible deployment of AI systems, impacting both the trustworthiness of AI and the development of robust defense strategies.
Papers
Can Large Language Models Automatically Jailbreak GPT-4V?
Yuanwei Wu, Yue Huang, Yixin Liu, Xiang Li, Pan Zhou, Lichao Sun
RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent
Huiyu Xu, Wenhui Zhang, Zhibo Wang, Feng Xiao, Rui Zheng, Yunhe Feng, Zhongjie Ba, Kui Ren
Figure it Out: Analyzing-based Jailbreak Attack on Large Language Models
Shi Lin, Rongchang Li, Xun Wang, Changting Lin, Wenpeng Xing, Meng Han
When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?
Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez
Arondight: Red Teaming Large Vision Language Models with Auto-generated Multi-modal Jailbreak Prompts
Yi Liu, Chengjun Cai, Xiaoli Zhang, Xingliang Yuan, Cong Wang
Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning
Simon Ostermann, Kevin Baum, Christoph Endres, Julia Masloh, Patrick Schramowski
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets
Zhihua Jin, Shiyi Liu, Haotian Li, Xun Zhao, Huamin Qu
Safe Unlearning: A Surprisingly Effective and Generalizable Solution to Defend Against Jailbreak Attacks
Zhexin Zhang, Junxiao Yang, Pei Ke, Shiyao Cui, Chujie Zheng, Hongning Wang, Minlie Huang
Image-to-Text Logic Jailbreak: Your Imagination can Help You Do Anything
Xiaotian Zou, Ke Li, Yongkang Chen
Enhancing the Capability and Robustness of Large Language Models through Reinforcement Learning-Driven Query Refinement
Zisu Huang, Xiaohua Wang, Feiran Zhang, Zhibo Xu, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang
Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks
Yue Zhou, Henry Peng Zou, Barbara Di Eugenio, Yang Zhang
Jailbreaking LLMs with Arabic Transliteration and Arabizi
Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, Yan Solihin, Qian Lou
WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models
Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, Nouha Dziri
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, Nouha Dziri
Poisoned LangChain: Jailbreak LLMs by LangChain
Ziqiu Wang, Jun Liu, Shengkai Zhang, Yang Yang