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In this study, we introduce RePD, an innovative attack Retrieval-based Prompt Decomposition framework designed to mitigate the risk of jailbreak attacks on large language models (LLMs). Despite rigorous pretraining and finetuning focused on…

Cryptography and Security · Computer Science 2024-12-02 Peiran Wang , Xiaogeng Liu , Chaowei Xiao

Recent advancements in generative AI have enabled ubiquitous access to large language models (LLMs). Empowered by their exceptional capabilities to understand and generate human-like text, these models are being increasingly integrated into…

Cryptography and Security · Computer Science 2024-10-02 Zhiyuan Yu , Xiaogeng Liu , Shunning Liang , Zach Cameron , Chaowei Xiao , Ning Zhang

Multimodal large language models (MLLMs) are widely used in vision-language reasoning tasks. However, their vulnerability to adversarial prompts remains a serious concern, as safety mechanisms often fail to prevent the generation of harmful…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Zuoou Li , Weitong Zhang , Jingyuan Wang , Shuyuan Zhang , Wenjia Bai , Bernhard Kainz , Mengyun Qiao

The misuse of large language models (LLMs) has drawn significant attention from the general public and LLM vendors. One particular type of adversarial prompt, known as jailbreak prompt, has emerged as the main attack vector to bypass the…

Cryptography and Security · Computer Science 2024-05-16 Xinyue Shen , Zeyuan Chen , Michael Backes , Yun Shen , Yang Zhang

Machine learning is advancing rapidly, with applications bringing notable benefits, such as improvements in translation and code generation. Models like ChatGPT, powered by Large Language Models (LLMs), are increasingly integrated into…

Machine Learning · Computer Science 2025-06-10 Torsten Krauß , Hamid Dashtbani , Alexandra Dmitrienko

The study of large language models (LLMs) is a key area in open-world machine learning. Although LLMs demonstrate remarkable natural language processing capabilities, they also face several challenges, including consistency issues,…

Large Language Models (LLMs) are increasingly attracting attention in various applications. Nonetheless, there is a growing concern as some users attempt to exploit these models for malicious purposes, including the synthesis of controlled…

Artificial Intelligence · Computer Science 2025-08-26 Chongwen Zhao , Zhihao Dou , Kaizhu Huang

Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate output behavior, privacy and security breaches, offensive…

Computation and Language · Computer Science 2024-03-28 Abhinav Rao , Sachin Vashistha , Atharva Naik , Somak Aditya , Monojit Choudhury

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…

Cryptography and Security · Computer Science 2024-01-31 Jie Li , Yi Liu , Chongyang Liu , Ling Shi , Xiaoning Ren , Yaowen Zheng , Yang Liu , Yinxing Xue

Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling applications across fields beyond healthcare, software engineering, and conversational systems.…

Safety mechanisms for large language models (LLMs) remain predominantly English-centric, creating systematic vulnerabilities in multilingual deployment. Prior work shows that translating malicious prompts into other languages can…

Computation and Language · Computer Science 2026-04-29 Shirin Alanova , Bogdan Minko , Sabrina Sadiekh , Evgeniy Kokuykin

We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic natural conversational settings, making them easier to bypass safety-aligned LLM than…

Computation and Language · Computer Science 2026-05-05 Jialin Song , Xiaodong Liu , Weiwei Yang , Wuyang Chen , Mingqian Feng , Xuekai Zhu , Jianfeng Gao

Recent advancements in AI safety have led to increased efforts in training and red-teaming large language models (LLMs) to mitigate unsafe content generation. However, these safety mechanisms may not be comprehensive, leaving potential…

Cryptography and Security · Computer Science 2024-11-06 Emet Bethany , Mazal Bethany , Juan Arturo Nolazco Flores , Sumit Kumar Jha , Peyman Najafirad

Large Language Model (LLM) alignment remains vulnerable to jailbreak attacks that elicit unsafe responses, motivating pre-model and post-model guards. Pre-model guards audit the safety of prompts before invoking target models. However,…

Cryptography and Security · Computer Science 2026-05-20 Hongyu Cai , Arjun Arunasalam , Yiming Liang , Antonio Bianchi , Z. Berkay Celik

Automatic adversarial prompt generation provides remarkable success in jailbreaking safely-aligned large language models (LLMs). Existing gradient-based attacks, while demonstrating outstanding performance in jailbreaking white-box LLMs,…

Machine Learning · Computer Science 2025-01-22 Qizhang Li , Xiaochen Yang , Wangmeng Zuo , Yiwen Guo

Large language models (LLMs) are widely applied in various fields of society due to their powerful reasoning, understanding, and generation capabilities. However, the security issues associated with these models are becoming increasingly…

Computation and Language · Computer Science 2025-05-30 Yanxu Mao , Peipei Liu , Tiehan Cui , Zhaoteng Yan , Congying Liu , Datao You

The recent growth in the use of Large Language Models has made them vulnerable to sophisticated adversarial assaults, manipulative prompts, and encoded malicious inputs. Existing countermeasures frequently necessitate retraining models,…

Computation and Language · Computer Science 2026-03-10 Sheikh Samit Muhaimin , Spyridon Mastorakis

Large Language Models (LLMs), used in creative writing, code generation, and translation, generate text based on input sequences but are vulnerable to jailbreak attacks, where crafted prompts induce harmful outputs. Most jailbreak prompt…

Computation and Language · Computer Science 2024-02-28 Xiaoxia Li , Siyuan Liang , Jiyi Zhang , Han Fang , Aishan Liu , Ee-Chien Chang

Large Language Models (LLMs), such as ChatGPT and GPT-4, are designed to provide useful and safe responses. However, adversarial prompts known as 'jailbreaks' can circumvent safeguards, leading LLMs to generate potentially harmful content.…

Computation and Language · Computer Science 2024-04-09 Peng Ding , Jun Kuang , Dan Ma , Xuezhi Cao , Yunsen Xian , Jiajun Chen , Shujian Huang

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…

Computation and Language · Computer Science 2025-02-14 Riccardo Cantini , Giada Cosenza , Alessio Orsino , Domenico Talia