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As Large Language Models (LLMs) are increasingly being deployed in safety-critical applications, their vulnerability to potential jailbreaks -- malicious prompts that can disable the safety mechanism of LLMs -- has attracted growing…

密码学与安全 · 计算机科学 2024-08-08 Jiahao Zhang , Zilong Wang , Ruofan Wang , Xingjun Ma , Yu-Gang Jiang

Large Language Models face security threats from jailbreak attacks. Existing research has predominantly focused on prompt-level attacks while largely ignoring the underexplored attack surface of user-controlled response prefilling. This…

密码学与安全 · 计算机科学 2025-08-27 Yakai Li , Jiekang Hu , Weiduan Sang , Luping Ma , Dongsheng Nie , Weijuan Zhang , Aimin Yu , Yi Su , Qingjia Huang , Qihang Zhou

Small Language Models (SLMs) are emerging as efficient and economically viable alternatives to Large Language Models (LLMs), offering competitive performance with significantly lower computational costs and latency. These advantages make…

密码学与安全 · 计算机科学 2026-04-01 Md Jueal Mia , Joaquin Molto , Yanzhao Wu , M. Hadi Amini

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…

密码学与安全 · 计算机科学 2024-11-04 Qizhang Li , Yiwen Guo , Wangmeng Zuo , Hao Chen

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.…

Large Language Models (LLMs) face threats from jailbreak prompts. Existing methods for detecting jailbreak prompts are primarily online moderation APIs or finetuned LLMs. These strategies, however, often require extensive and…

计算与语言 · 计算机科学 2024-05-31 Yueqi Xie , Minghong Fang , Renjie Pi , Neil Gong

Jailbreaking large language models (LLMs) has emerged as a critical security challenge with the widespread deployment of conversational AI systems. Adversarial users exploit these models through carefully crafted prompts to elicit…

密码学与安全 · 计算机科学 2026-02-23 Sri Durga Sai Sowmya Kadali , Evangelos E. Papalexakis

As Spoken Language Models (SLMs) integrate speech and text modalities, they inherit the safety vulnerabilities of their LLM backbone and an expanded attack surface. SLMs have been previously shown to be susceptible to jailbreaking, where…

机器学习 · 计算机科学 2026-03-20 Aravind Krishnan , Karolina Stańczak , Dietrich Klakow

Large language models (LLMs) are designed to align with human values in their responses. This study exploits LLMs with an iterative prompting technique where each prompt is systematically modified and refined across multiple iterations to…

计算与语言 · 计算机科学 2025-03-27 Shih-Wen Ke , Guan-Yu Lai , Guo-Lin Fang , Hsi-Yuan Kao

Large Language Models (LLMs) are increasingly susceptible to jailbreak attacks, which are adversarial prompts that bypass alignment constraints and induce unauthorized or harmful behaviors. These vulnerabilities undermine the safety,…

机器学习 · 计算机科学 2025-09-30 Javad Forough , Mohammad Maheri , Hamed Haddadi

Recent advances in Multimodal Large Language Models (MLLMs) have significantly enhanced the naturalness and flexibility of human computer interaction by enabling seamless understanding across text, vision, and audio modalities. Among these,…

计算与语言 · 计算机科学 2025-05-27 Binhao Ma , Hanqing Guo , Zhengping Jay Luo , Rui Duan

The adoption of large language models (LLMs) in many applications, from customer service chat bots and software development assistants to more capable agentic systems necessitates research into how to secure these systems. Attacks like…

密码学与安全 · 计算机科学 2024-12-03 Erick Galinkin , Martin Sablotny

Ensuring the safety and alignment of large language models (LLMs) with human values is crucial for generating responses that are beneficial to humanity. While LLMs have the capability to identify and avoid harmful queries, they remain…

计算与语言 · 计算机科学 2024-10-22 Yihua Zhou , Xiaochuan Shi

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,…

密码学与安全 · 计算机科学 2026-05-20 Hongyu Cai , Arjun Arunasalam , Yiming Liang , Antonio Bianchi , Z. Berkay Celik

Large Language Models (LLMS) have increasingly become central to generating content with potential societal impacts. Notably, these models have demonstrated capabilities for generating content that could be deemed harmful. To mitigate these…

密码学与安全 · 计算机科学 2024-05-20 Zihao Xu , Yi Liu , Gelei Deng , Yuekang Li , Stjepan Picek

Jailbreaking attacks can effectively induce unsafe behaviors in Large Language Models (LLMs); however, the transferability of these attacks across different models remains limited. This study aims to understand and enhance the…

机器学习 · 计算机科学 2025-03-05 Junxiao Yang , Zhexin Zhang , Shiyao Cui , Hongning Wang , Minlie Huang

Large Language Models (LLMs) have achieved remarkable success across diverse tasks, yet they remain vulnerable to adversarial attacks, notably the well-known jailbreak attack. In particular, the Greedy Coordinate Gradient (GCG) attack has…

机器学习 · 计算机科学 2025-03-04 Yihao Zhang , Zeming Wei

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

Large Language Models (LLMs) guardrail systems are designed to protect against prompt injection and jailbreak attacks. However, they remain vulnerable to evasion techniques. We demonstrate two approaches for bypassing LLM prompt injection…

密码学与安全 · 计算机科学 2025-07-15 William Hackett , Lewis Birch , Stefan Trawicki , Neeraj Suri , Peter Garraghan

The recent boom and rapid integration of Large Language Models (LLMs) into a wide range of applications warrants a deeper understanding of their security and safety vulnerabilities. This paper presents a comparative analysis of the…

密码学与安全 · 计算机科学 2025-11-25 Tom Perel
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