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Large language models (LLMs) are susceptible to a type of attack known as jailbreaking, which misleads LLMs to output harmful contents. Although there are diverse jailbreak attack strategies, there is no unified understanding on why some…

计算与语言 · 计算机科学 2024-12-04 Yuping Lin , Pengfei He , Han Xu , Yue Xing , Makoto Yamada , Hui Liu , Jiliang Tang

Aligned large language models (LLMs) are vulnerable to jailbreaking attacks, which bypass the safeguards of targeted LLMs and fool them into generating objectionable content. While initial defenses show promise against token-based threat…

计算与语言 · 计算机科学 2024-03-01 Jiabao Ji , Bairu Hou , Alexander Robey , George J. Pappas , Hamed Hassani , Yang Zhang , Eric Wong , Shiyu Chang

Defending large language models against jailbreaks so that they never engage in a broadly-defined set of forbidden behaviors is an open problem. In this paper, we investigate the difficulty of jailbreak-defense when we only want to forbid a…

Recent advancements in large language models (LLMs) have revolutionized code intelligence by improving programming productivity and alleviating challenges faced by software developers. To further improve the performance of LLMs on specific…

密码学与安全 · 计算机科学 2024-10-07 Yifei Ge , Weisong Sun , Yihang Lou , Chunrong Fang , Yiran Zhang , Yiming Li , Xiaofang Zhang , Yang Liu , Zhihong Zhao , Zhenyu Chen

As Large Language Models (LLMs) increasingly become key components in various AI applications, understanding their security vulnerabilities and the effectiveness of defense mechanisms is crucial. This survey examines the security challenges…

机器学习 · 计算机科学 2024-06-04 Frank Weizhen Liu , Chenhui Hu

Safety, security, and compliance are essential requirements when aligning large language models (LLMs). However, many seemingly aligned LLMs are soon shown to be susceptible to jailbreak attacks. These attacks aim to circumvent the models'…

密码学与安全 · 计算机科学 2025-06-05 Chen Xiong , Xiangyu Qi , Pin-Yu Chen , Tsung-Yi Ho

Large language models (LLMs) are widely adapted for downstream applications through fine-tuning, a process named customization. However, recent studies have identified a vulnerability during this process, where malicious samples can…

密码学与安全 · 计算机科学 2025-02-19 Xiaoqun Liu , Jiacheng Liang , Luoxi Tang , Muchao Ye , Weicheng Ma , Zhaohan Xi

Large language models (LLMs) rely on safety alignment to avoid responding to malicious user inputs. Unfortunately, jailbreak can circumvent safety guardrails, resulting in LLMs generating harmful content and raising concerns about LLM…

计算与语言 · 计算机科学 2024-06-14 Zhenhong Zhou , Haiyang Yu , Xinghua Zhang , Rongwu Xu , Fei Huang , Yongbin Li

Large Language Models (LLMs) are changing the way people interact with technology. Tools like ChatGPT and Claude AI are now common in business, research, and everyday life. But with that growth comes new risks, especially prompt-based…

密码学与安全 · 计算机科学 2025-05-27 Austin Howard

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

Large Language Models (LLMs) have achieved remarkable success in various domains but remain vulnerable to adversarial jailbreak attacks. Existing prompt-defense strategies, including parameter-modifying and parameter-free approaches, face…

密码学与安全 · 计算机科学 2025-02-20 Ziyi Ni , Hao Wang , Huacan Wang

Extensive work has been devoted to improving the safety mechanism of Large Language Models (LLMs). However, LLMs still tend to generate harmful responses when faced with malicious instructions, a phenomenon referred to as "Jailbreak…

计算与语言 · 计算机科学 2024-02-26 Yanrui Du , Sendong Zhao , Ming Ma , Yuhan Chen , Bing Qin

As large language models (LLMs) grow more capable, they face growing vulnerability to sophisticated jailbreak attacks. While developers invest heavily in alignment finetuning and safety guardrails, researchers continue publishing novel…

密码学与安全 · 计算机科学 2025-08-14 Boyuan Chen , Minghao Shao , Abdul Basit , Siddharth Garg , Muhammad Shafique

Although large language models (LLMs) demonstrate impressive proficiency in various tasks, they present potential safety risks, such as `jailbreaks', where malicious inputs can coerce LLMs into generating harmful content bypassing safety…

计算与语言 · 计算机科学 2025-11-26 Isack Lee , Haebin Seong

Large Language Models (LLMs) have seen rapid adoption in recent years, with industries increasingly relying on them to maintain a competitive advantage. These models excel at interpreting user instructions and generating human-like…

密码学与安全 · 计算机科学 2025-09-09 Andrew Yeo , Daeseon Choi

Large language models (LLMs) have demonstrated remarkable capabilities, but their power comes with significant security considerations. While extensive research has been conducted on the safety of LLMs in chat mode, the security…

密码学与安全 · 计算机科学 2024-12-25 Zihui Wu , Haichang Gao , Jianping He , Ping Wang

As large language models (LLMs) become more integral to society and technology, ensuring their safety becomes essential. Jailbreak attacks exploit vulnerabilities to bypass safety guardrails, posing a significant threat. However, the…

密码学与安全 · 计算机科学 2025-07-08 Xiaomeng Hu , Pin-Yu Chen , Tsung-Yi Ho

Large Language Models (LLMs) are vulnerable to prompt injection attacks, and several defenses have recently been proposed, often claiming to mitigate these attacks successfully. However, we argue that existing studies lack a principled…

密码学与安全 · 计算机科学 2025-05-27 Yuqi Jia , Zedian Shao , Yupei Liu , Jinyuan Jia , Dawn Song , Neil Zhenqiang Gong

Large Language Models (LLMs) have revolutionized artificial intelligence, demonstrating remarkable computational power and linguistic capabilities. However, these models are inherently prone to various biases stemming from their training…

计算与语言 · 计算机科学 2025-02-14 Riccardo Cantini , Giada Cosenza , Alessio Orsino , Domenico Talia

The growing capabilities of large language models (LLMs) have driven their widespread deployment across diverse domains, even in potentially high-risk scenarios. Despite advances in safety alignment techniques, current models remain…

人工智能 · 计算机科学 2026-05-05 Jiajia Li , Xiaoyu Wen , Zhongtian Ma , Shuyue Hu , Qiaosheng Zhang , Zhen Wang