Despite extensive pre-training in moral alignment to prevent generating harmful information, large language models (LLMs) remain vulnerable to jailbreak attacks. In this paper, we propose AutoDefense, a multi-agent defense framework that filters harmful responses from LLMs. With the response-filtering mechanism, our framework is robust against different jailbreak attack prompts, and can be used to defend different victim models. AutoDefense assigns different roles to LLM agents and employs them to complete the defense task collaboratively. The division in tasks enhances the overall instruction-following of LLMs and enables the integration of other defense components as tools. With AutoDefense, small open-source LMs can serve as agents and defend larger models against jailbreak attacks. Our experiments show that AutoDefense can effectively defense against different jailbreak attacks, while maintaining the performance at normal user request. For example, we reduce the attack success rate on GPT-3.5 from 55.74% to 7.95% using LLaMA-2-13b with a 3-agent system. Our code and data are publicly available at https://github.com/XHMY/AutoDefense.
Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
School of EECS, Peking University（电子工程系，北京大学）；School of Mathematical Sciences, Peking University（数学系，北京大学）；State Key Lab of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University（通用人工智能国家重点实验室，智能科学与技术学校，北京大学）；Institute for Artificial Intelligence, Peking University（人工智能研究院，北京大学）
Test-Time Immunization: A Universal Defense Framework Against Jailbreaks for (Multimodal) Large Language Models
NLPR & MAIS, Institute of Automation, Chinese Academy of Sciences（国家工程实验室与人工智能研究所，中国科学院）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
DoubtProbe: Black-Box Jailbreak Defense via Structural Verification and Semantic Auditing
East China Normal University（东华大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）
Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks
Lab of Artificial Intelligence for Education, East China Normal University, Shanghai 200062, China（教育人工智能实验室，东华大学，上海200062，中国）；Shanghai Institute of Artificial Intelligence for Education, East China Normal University, Shanghai 200062, China（教育人工智能研究所，东华大学，上海200062，中国）；School of Computer Science and Technology, East China Normal University, Shanghai 200062, China（计算机科学与技术学院，东华大学，上海200062，中国）
Unified Defense for Large Language Models against Jailbreak and Fine-Tuning Attacks in Education
Shanghai Institute of Artificial Intelligence for Education, East China Normal University, Shanghai 200062, China（教育人工智能研究所，华东师范大学，上海200062，中国）；School of Computer Science and Technology, East China Normal University, Shanghai 200062, China（计算机科学与技术学院，华东师范大学，上海200062，中国）；School of Computer Science（计算机科学学院）
QueryAttack: Jailbreaking Aligned Large Language Models Using Structured Non-natural Query Language
Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院）；Pengcheng Laboratory（鹏城实验室）；The Chinese University of Hong Kong（香港中文大学）；Jilin University（吉林大学）；Southwest University（西南大学）；University of Electronic Science and Technology of China（电子科技大学）；Shenzhen University（深圳大学）
A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
The Harbin Institute of Technology（哈尔滨工业大学）；The Hong Kong Polytechnic University（香港理工大学）；Shenzhen University（深圳大学）；Shenzhen Loop Area Institute（深圳河套学院）
FRACTURED-SORRY-Bench: Framework for Revealing Attacks in Conversational Turns Undermining Refusal Efficacy and Defenses over SORRY-Bench (Automated Multi-shot Jailbreaks)
Jailbreaking LLMs' Safeguard with Universal Magic Words for Text Embedding Models
Dept. of Comp. Sci. and Tech., Inst. for AI, Tsinghua-Bosch Joint ML Center, THBI Lab, BNRist Center, Tsinghua University, Beijing, 100084, China（计算机科学与技术系、人工智能研究所、清华-博世联合机器学习中心、THBI实验室、BNRist中心、清华大学、北京）；Department of Mathematical Sciences, Tsinghua University（数学科学系、清华大学）；BIMSA, Beijing, China（BIMSA、北京、中国）
X-Boundary: Establishing Exact Safety Boundary to Shield LLMs from Multi-Turn Jailbreaks without Compromising Usability
School of Electronic Information and Electric Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
School of Computer Science and Technology, Guangdong University of Technology（广东工业大学计算机科学与技术学院）；School of Computer Science and Intelligence Education, Lingnan Normal University（岭南师范学院计算机与智能教育学院）；College of Computer, National University of Defense Technology（国防科技大学计算机学院）；School of Information Science and Technology, Guangdong University of Foreign Studies（广东外语外贸大学信息科学与技术学院）
E$^2$AT: Multimodal Jailbreak Defense via Dynamic Joint Optimization for Multimodal Large Language Models
School of Cyber Science and Engineering, Nanjing University of Science and Technology, China（南京理工大学信息科学与工程学院）；HKUST(GZ) and INSAIT, Sofia University St. Kliment Ohridski（香港科技大学（广州）及INSAIT，索菲亚大学圣克莱门特·奥赫里迪斯学院）；College of Computing and Data Science, Nanyang Technological University, Singapore（南洋理工大学计算与数据科学学院）
