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Jailbreak attacks, which aim to cause LLMs to perform unrestricted behaviors, have become a critical and challenging direction in AI safety. Despite achieving the promising attack success rate using dictionary-based evaluation, existing…

密码学与安全 · 计算机科学 2025-04-14 Tianyi Wu , Zhiwei Xue , Yue Liu , Jiaheng Zhang , Bryan Hooi , See-Kiong Ng

While significant attention has been dedicated to exploiting weaknesses in LLMs through jailbreaking attacks, there remains a paucity of effort in defending against these attacks. We point out a pivotal factor contributing to the success of…

计算与语言 · 计算机科学 2024-06-13 Zhexin Zhang , Junxiao Yang , Pei Ke , Fei Mi , Hongning Wang , Minlie Huang

Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks. However, they remain exposed to jailbreak attacks, eliciting harmful responses. The nested scenario strategy has been increasingly adopted across…

密码学与安全 · 计算机科学 2025-11-18 Ning Xu , Bo Gao , Hui Dou

LLMs have made impressive progress, but their growing capabilities also expose them to highly flexible jailbreaking attacks designed to bypass safety alignment. While many existing defenses focus on known types of attacks, it is more…

密码学与安全 · 计算机科学 2025-05-27 Haoyu Wang , Zeyu Qin , Yifei Zhao , Chao Du , Min Lin , Xueqian Wang , Tianyu Pang

Extensive efforts have been made before the public release of Large language models (LLMs) to align their behaviors with human values. However, even meticulously aligned LLMs remain vulnerable to malicious manipulations such as…

密码学与安全 · 计算机科学 2024-10-01 Zeguan Xiao , Yan Yang , Guanhua Chen , Yun Chen

Large Language Models (LLMs) remain vulnerable to jailbreak attacks that bypass their safety mechanisms. Existing attack methods are fixed or specifically tailored for certain models and cannot flexibly adjust attack strength, which is…

密码学与安全 · 计算机科学 2024-10-08 Yiting Dong , Guobin Shen , Dongcheng Zhao , Xiang He , Yi Zeng

In recent years, Large Language Models (LLMs) have gained widespread use, raising concerns about their security. Traditional jailbreak attacks, which often rely on the model internal information or have limitations when exploring the unsafe…

密码学与安全 · 计算机科学 2024-10-04 Zhihao Lin , Wei Ma , Mingyi Zhou , Yanjie Zhao , Haoyu Wang , Yang Liu , Jun Wang , Li Li

The recent breakthrough in large language models (LLMs) such as ChatGPT has revolutionized production processes at an unprecedented pace. Alongside this progress also comes mounting concerns about LLMs' susceptibility to jailbreaking…

机器学习 · 计算机科学 2024-05-24 Tianrong Zhang , Bochuan Cao , Yuanpu Cao , Lu Lin , Prasenjit Mitra , Jinghui Chen

Modern large language model (LLM) developers typically conduct a safety alignment to prevent an LLM from generating unethical or harmful content. Recent studies have discovered that the safety alignment of LLMs can be bypassed by…

密码学与安全 · 计算机科学 2024-06-14 Xuan Chen , Yuzhou Nie , Lu Yan , Yunshu Mao , Wenbo Guo , Xiangyu Zhang

Large Language Models (LLMs), despite advanced general capabilities, still suffer from numerous safety risks, especially jailbreak attacks that bypass safety protocols. Understanding these vulnerabilities through black-box jailbreak…

密码学与安全 · 计算机科学 2025-05-29 Yao Huang , Yitong Sun , Shouwei Ruan , Yichi Zhang , Yinpeng Dong , Xingxing Wei

Large language models (LLMs) are increasingly deployed in a wide range of applications, yet remain vulnerable to adversarial jailbreak attacks that circumvent their safety guardrails. Existing evaluation frameworks typically report binary…

密码学与安全 · 计算机科学 2026-05-14 Zvi Topol

In the era of rapid generative AI development, interactions with large language models (LLMs) pose increasing risks of misuse. Prior research has primarily focused on attacks using template-based prompts and optimization-oriented methods,…

密码学与安全 · 计算机科学 2026-03-03 Wenhan Chang , Tianqing Zhu , Yu Zhao , Shuangyong Song , Ping Xiong , Wanlei Zhou

This paper proposes a game theoretic framework that models the interaction between prompt engineers and large language models (LLMs) as a two player extensive form game coupled with a Rapidly exploring Random Trees (RRT) search over prompt…

人工智能 · 计算机科学 2026-03-04 Zhengye Han , Quanyan Zhu

Large language models (LLMs) remain vulnerable to sophisticated prompt engineering attacks that exploit contextual framing to bypass safety mechanisms, posing significant risks in cybersecurity applications. We introduce Jailbreak Mimicry,…

密码学与安全 · 计算机科学 2025-10-28 Pavlos Ntais

Large language models (LLMs) generate human-aligned content under certain safety constraints. However, the current known technique ``jailbreak prompt'' can circumvent safety-aligned measures and induce LLMs to output malicious content.…

密码学与安全 · 计算机科学 2025-08-28 Xi Wang , Songlei Jian , Shasha Li , Xiaopeng Li , Bin Ji , Jun Ma , Xiaodong Liu , Jing Wang , Feilong Bao , Jianfeng Zhang , Baosheng Wang , Jie Yu

Large Language Models (LLMs) have become increasingly popular for their advanced text generation capabilities across various domains. However, like any software, they face security challenges, including the risk of 'jailbreak' attacks that…

密码学与安全 · 计算机科学 2024-01-31 Jie Li , Yi Liu , Chongyang Liu , Ling Shi , Xiaoning Ren , Yaowen Zheng , Yang Liu , Yinxing Xue

Large language models (LLMs) have made significant advancements across various tasks, but their safety alignment remain a major concern. Exploring jailbreak prompts can expose LLMs' vulnerabilities and guide efforts to secure them. Existing…

密码学与安全 · 计算机科学 2025-11-25 Xiaoning Dong , Wenbo Hu , Wei Xu , Tianxing He

Large language models (LLMs), such as ChatGPT, have emerged with astonishing capabilities approaching artificial general intelligence. While providing convenience for various societal needs, LLMs have also lowered the cost of generating…

计算与语言 · 计算机科学 2023-08-28 Zhenhua Wang , Wei Xie , Kai Chen , Baosheng Wang , Zhiwen Gui , Enze Wang

Large language models (LLMs) have significantly enhanced the performance of numerous applications, from intelligent conversations to text generation. However, their inherent security vulnerabilities have become an increasingly significant…

计算与语言 · 计算机科学 2024-08-12 Xiongtao Sun , Deyue Zhang , Dongdong Yang , Quanchen Zou , Hui Li

Multimodal Large Language Models (MLLMs) have become widely deployed, yet their safety alignment remains fragile under adversarial inputs. Previous work has shown that increasing inference steps can disrupt safety mechanisms and lead MLLMs…

计算机视觉与模式识别 · 计算机科学 2026-04-17 Xiangdong Hu , Yangyang Jiang , Qin Hu , Xiaojun Jia
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