Fetching the paper…
Reading the bibliography…
Jailbreak prompts pose a significant threat in AI and cybersecurity, as they are crafted to bypass ethical safeguards in large language models, potentially enabling misuse by cybercriminals.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Earlier work this paper cites.
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, and James Zou. 2023 · 2023
Earlier work this paper cites.
Defending against alignment-breaking attacks via robustly aligned llm
Bochuan Cao, Yuanpu Cao, Lu Lin, and Jinghui Chen. 2023 · 2023
Earlier work this paper cites.
From chatgpt to threatgpt: Impact of generative ai in cybersecurity and privacy
Maanak Gupta, CharanKumar Akiri, Kshitiz Aryal, Eli Parker, and Lopamudra Praharaj. 2023 · 2023
Earlier work this paper cites.
Baseline defenses for adversarial attacks against aligned language models
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein. 2023 · 2023
Earlier work this paper cites.
Tree of attacks: Jailbreaking black-box llms automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi. 2023 · 2023
Earlier work this paper cites.
An attacker’s dream? exploring the capabilities of chatgpt for developing malware
Yin Minn Pa Pa, Shunsuke Tanizaki, Tetsui Kou, Michel Van Eeten, Katsunari Yoshioka, and Tsutomu Matsumoto. 2023 · 2023
Earlier work this paper cites.
Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas. 2023 · 2023
Earlier work this paper cites.
Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang. 2023 · 2023
Earlier work this paper cites.
Defending chatgpt against jailbreak attack via self-reminders
Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, and Fangzhao Wu. 2023 · 2023
Earlier work this paper cites.
Securing large language models: Threats, vulnerabilities and responsible practices
Sara Abdali, Richard Anarfi, CJ Barberan, and Jia He. 2024 · 2024
Earlier work this paper cites.
Jailbreaking leading safety-aligned llms with simple adaptive attacks
Maksym Andriushchenko, Francesco Croce, and Nicolas Flammarion. 2024 · 2024
Cited alongside, same era.
Characterizing and evaluating the reliability of llms against jailbreak attacks
Kexin Chen, Yi Liu, Dongxia Wang, Jiaying Chen, and Wenhai Wang. 2024 · 2024
Cited alongside, same era.
Leveraging the context through multi-round interactions for jailbreaking attacks
Yixin Cheng, Markos Georgopoulos, Volkan Cevher, and Grigorios G Chrysos. 2024 · 2024
Cited alongside, same era.
Cold-attack: Jailbreaking llms with stealthiness and controllability
Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, and Bin Hu. 2024 · 2024
Cited alongside, same era.
Obscureprompt: Jailbreaking large language models via obscure input
Spml: A dsl for defending language models against prompt attacks
Reshabh K Sharma, Vinayak Gupta, and Dan Grossman. 2024 · 2024
Closest in time.
Attngcg: Enhancing jailbreaking attacks on llms with attention manipulation
Zijun Wang, Haoqin Tu, Jieru Mei, Bingchen Zhao, Yisen Wang, and Cihang Xie. 2024 · 2024
Closest in time.
Jailbroken: How does llm safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2024 · 2024
Closest in time.
Gradsafe: Detecting unsafe prompts for llms via safety-critical gradient analysis
Yueqi Xie, Minghong Fang, Renjie Pi, and Neil Gong. 2024 · 2024
Closest in time.
Defensive prompt patch: A robust and interpretable defense of llms against jailbreak attacks
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yue Huang, Jingyu Tang, Dongping Chen, Bingda Tang, Yao Wan, Lichao Sun, and Xiangliang Zhang. 2024 · 2024
Cited alongside, same era.
Break the breakout: Reinventing lm defense against jailbreak attacks with self-refinement
Heegyu Kim, Sehyun Yuk, and Hyunsouk Cho. 2024 · 2024
Cited alongside, same era.
What features in prompts jailbreak llms? investigating the mechanisms behind attacks
Nathalie Maria Kirch, Severin Field, and Stephen Casper. 2024 · 2024
Cited alongside, same era.
A hitchhiker’s guide to jailbreaking chatgpt via prompt engineering
Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, and Kailong Wang. 2024 · 2024
Cited alongside, same era.
Weidi Luo, Siyuan Ma, Xiaogeng Liu, Xiaoyu Guo, and Chaowei Xiao. 2024 · 2024
Cited alongside, same era.
Jailbreaking and mitigation of vulnerabilities in large language models
Benji Peng, Ziqian Bi, Qian Niu, Ming Liu, Pohsun Feng, Tianyang Wang, Lawrence KQ Yan, Yizhu Wen, Yichao Zhang, and Caitlyn Heqi Yin. 2024 · 2024
Cited alongside, same era.
Mitigating adversarial manipulation in llms: a prompt-based approach to counter jailbreak attacks (prompt-g)
Bhagyajit Pingua, Deepak Murmu, Meenakshi Kandpal, Jyotirmayee Rautaray, Pranati Mishra, Rabindra Kumar Barik, and Manob Jyoti Saikia. 2024 · 2024
Cited alongside, same era.
Attack prompt generation for red teaming and defending large language models
Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, and Xiangnan He. 2023a
Cited in the paper.
Chen Xiong, Xiangyu Qi, Pin-Yu Chen, and Tsung-Yi Ho. 2024 · 2024
Closest in time.
A comprehensive study of jailbreak attack versus defense for large language models
Zihao Xu, Yi Liu, Gelei Deng, Yuekang Li, and Stjepan Picek. 2024c · 2024
Closest in time.
Jailbreak attacks and defenses against large language models: A survey
Sibo Yi, Yule Liu, Zhen Sun, Tianshuo Cong, Xinlei He, Jiaxing Song, Ke Xu, and Qi Li. 2024 · 2024
Closest in time.
Don’t listen to me: Understanding and exploring jailbreak prompts of large language models
Zhiyuan Yu, Xiaogeng Liu, Shunning Liang, Zach Cameron, Chaowei Xiao, and Ning Zhang. 2024 · 2024
Closest in time.
Autodefense: Multi-agent llm defense against jailbreak attacks
Yifan Zeng, Yiran Wu, Xiao Zhang, Huazheng Wang, and Qingyun Wu. 2024 · 2024
Closest in time.
Easyjailbreak: A unified framework for jailbreaking large language models
Weikang Zhou, Xiao Wang, Limao Xiong, Han Xia, Yingshuang Gu, Mingxu Chai, Fukang Zhu, Caishuang Huang, Shihan Dou, Zhiheng Xi, et al. 2024 · 2024
Closest in time.
Is the system message really important to jailbreaks in large language models?
Xiaotian Zou, Yongkang Chen, and Ke Li. 2024 · 2024
Closest in time.