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Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their susceptibility to adversarial attacks, particularly jailbreaking, poses significant safety and ethical concerns. While numerous jailbreak methods exist, many…

Cryptography and Security · Computer Science 2025-06-17 Bilal Saleh Husain

We discuss the ``Infinitely Many Paraphrases'' attacks (IMP), a category of jailbreaks that leverages the increasing capabilities of a model to handle paraphrases and encoded communications to bypass their defensive mechanisms. IMPs'…

Machine Learning · Computer Science 2025-03-14 Oliver Goldstein , Emanuele La Malfa , Felix Drinkall , Samuele Marro , Michael Wooldridge

Large Language Models (LLMs) have emerged as powerful re-rankers. Recent research has however showed that simple prompt injections embedded within a candidate document (i.e., jailbreak prompt attacks) can significantly alter an LLM's…

Cryptography and Security · Computer Science 2026-02-20 Yu Yin , Shuai Wang , Bevan Koopman , Guido Zuccon

The wide adoption of Large Language Models (LLMs) has attracted significant attention from $\textit{jailbreak}$ attacks, where adversarial prompts crafted through optimization or manual design exploit LLMs to generate malicious contents.…

Computation and Language · Computer Science 2025-10-01 Xurui Song , Zhixin Xie , Shuo Huai , Jiayi Kong , Jun Luo

Jailbreak techniques for large language models (LLMs) evolve faster than benchmarks, making robustness estimates stale and difficult to compare across papers due to drift in datasets, harnesses, and judging protocols. We introduce JAILBREAK…

Cryptography and Security · Computer Science 2026-03-06 Zhicheng Fang , Jingjie Zheng , Chenxu Fu , Wei Xu

Adversarial prompts generated using gradient-based methods exhibit outstanding performance in performing automatic jailbreak attacks against safety-aligned LLMs. Nevertheless, due to the discrete nature of texts, the input gradient of LLMs…

Cryptography and Security · Computer Science 2024-11-04 Qizhang Li , Yiwen Guo , Wangmeng Zuo , Hao Chen

Large Language Models (LLMs) are commonly evaluated for robustness against paraphrased or semantically equivalent jailbreak prompts, yet little attention has been paid to linguistic variation as an attack surface. In this work, we…

Computation and Language · Computer Science 2025-11-14 Srikant Panda , Avinash Rai

Alignment in large language models (LLMs) is used to enforce guidelines such as safety. Yet, alignment fails in the face of jailbreak attacks that modify inputs to induce unsafe outputs. In this paper, we introduce and evaluate a new…

Cryptography and Security · Computer Science 2026-02-19 Jean-Charles Noirot Ferrand , Yohan Beugin , Eric Pauley , Ryan Sheatsley , Patrick McDaniel

We find that language models have difficulties generating fallacious and deceptive reasoning. When asked to generate deceptive outputs, language models tend to leak honest counterparts but believe them to be false. Exploiting this…

Computation and Language · Computer Science 2025-05-26 Yue Zhou , Henry Peng Zou , Barbara Di Eugenio , Yang Zhang

Jailbreak attacks pose a serious threat to Large Language Models (LLMs) by bypassing their safety mechanisms. A truly advanced jailbreak is defined not only by its effectiveness but, more critically, by its stealthiness. However, existing…

Cryptography and Security · Computer Science 2026-03-13 Jianing Geng , Biao Yi , Zekun Fei , Ruiqi He , Lihai Nie , Tong Li , Zheli Liu

We study a new vulnerability in commercial-scale safety-aligned large language models (LLMs): their refusal to generate harmful responses can be broken by flipping only a few bits in model parameters. Our attack jailbreaks billion-parameter…

Cryptography and Security · Computer Science 2025-10-06 Zachary Coalson , Jeonghyun Woo , Chris S. Lin , Joyce Qu , Yu Sun , Shiyang Chen , Lishan Yang , Gururaj Saileshwar , Prashant Nair , Bo Fang , Sanghyun Hong

Large language models (LLMs) have achieved widespread adoption across numerous applications. However, many LLMs are vulnerable to malicious attacks even after safety alignment. These attacks typically bypass LLMs' safety guardrails by…

Cryptography and Security · Computer Science 2025-06-17 Yucheng Li , Surin Ahn , Huiqiang Jiang , Amir H. Abdi , Yuqing Yang , Lili Qiu

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…

Computation and Language · Computer Science 2024-06-13 Zhexin Zhang , Junxiao Yang , Pei Ke , Fei Mi , Hongning Wang , Minlie Huang

The rise of Large Language Models (LLMs) has led to significant applications but also introduced serious security threats, particularly from jailbreak attacks that manipulate output generation. These attacks utilize prompt engineering and…

Cryptography and Security · Computer Science 2025-02-20 Yanzeng Li , Yunfan Xiong , Jialun Zhong , Jinchao Zhang , Jie Zhou , Lei Zou

Large Language Models (LLMs) are known to be vulnerable to jailbreaking attacks, wherein adversaries exploit carefully engineered prompts to induce harmful or unethical responses. Such threats have raised critical concerns about the safety…

Cryptography and Security · Computer Science 2025-05-22 Taiye Chen , Zeming Wei , Ang Li , Yisen Wang

Large Language Models (LLMs) are susceptible to Jailbreaking attacks, which aim to extract harmful information by subtly modifying the attack query. As defense mechanisms evolve, directly obtaining harmful information becomes increasingly…

Machine Learning · Computer Science 2024-10-03 Yixin Cheng , Markos Georgopoulos , Volkan Cevher , Grigorios G. Chrysos

The advancement of Pre-Trained Language Models (PTLMs) and Large Language Models (LLMs) has led to their widespread adoption across diverse applications. Despite their success, these models remain vulnerable to attacks that exploit their…

Computation and Language · Computer Science 2025-06-30 Mohamed Ahmed , Mohamed Abdelmouty , Mingyu Kim , Gunvanth Kandula , Alex Park , James C. Davis

Large Language Models (LLMs) have revolutionized Artificial Intelligence (AI) services due to their exceptional proficiency in understanding and generating human-like text. LLM chatbots, in particular, have seen widespread adoption,…

Cryptography and Security · Computer Science 2024-02-14 Gelei Deng , Yi Liu , Yuekang Li , Kailong Wang , Ying Zhang , Zefeng Li , Haoyu Wang , Tianwei Zhang , Yang Liu

The proliferation of large language models (LLMs) has underscored concerns regarding their security vulnerabilities, notably against jailbreak attacks, where adversaries design jailbreak prompts to circumvent safety mechanisms for potential…

Cryptography and Security · Computer Science 2025-06-10 Yingchaojie Feng , Zhizhang Chen , Zhining Kang , Sijia Wang , Haoyu Tian , Wei Zhang , Minfeng Zhu , Wei Chen

With the widespread application of large language models (LLMs) in various fields, the security challenges they face have become increasingly prominent, especially the issue of jailbreak. These attacks induce the model to generate erroneous…

Cryptography and Security · Computer Science 2025-11-12 Shuyuan Liu , Jiawei Chen , Xiao Yang , Hang Su , Zhaoxia Yin