17 citations · 58 across the 25 of their papers we have counts for
9 papers · 1 filter
RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process
Peiran Wang, Xiaogeng Liu, Chaowei Xiao
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 (L…
System-Level Defense against Indirect Prompt Injection Attacks: An Information Flow Control Perspective
Fangzhou Wu, Ethan Cecchetti, Chaowei Xiao
Large Language Model-based systems (LLM systems) are information and query processing systems that use LLMs to plan operations from natural-language prompts and feed the output of…
InjecGuard: Benchmarking and Mitigating Over-defense in Prompt Injection Guardrail Models
Hao Li, Xiaogeng Liu
Prompt injection attacks pose a critical threat to large language models (LLMs), enabling goal hijacking and data leakage. Prompt guard models, though effective in defense, suffer…
AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Xiaogeng Liu, Peiran Li, Edward Suh +7
In this paper, we propose AutoDAN-Turbo, a black-box jailbreak method that can automatically discover as many jailbreak strategies as possible from scratch, without any human inter…
JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks
Weidi Luo, Siyuan Ma, Xiaogeng Liu +2
With the rapid advancements in Multimodal Large Language Models (MLLMs), securing these models against malicious inputs while aligning them with human values has emerged as a criti…
Automatic and Universal Prompt Injection Attacks against Large Language Models
Xiaogeng Liu, Zhiyuan Yu, Yizhe Zhang +2
Large Language Models (LLMs) excel in processing and generating human language, powered by their ability to interpret and follow instructions. However, their capabilities can be ex…
Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
Zhiyuan Yu, Xiaogeng Liu, Shunning Liang +3
Recent advancements in generative AI have enabled ubiquitous access to large language models (LLMs). Empowered by their exceptional capabilities to understand and generate human-li…
A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems
Fangzhou Wu, Ning Zhang, Somesh Jha +2
Large Language Model (LLM) systems are inherently compositional, with individual LLM serving as the core foundation with additional layers of objects such as plugins, sandbox, and…
WIPI: A New Web Threat for LLM-Driven Web Agents
Fangzhou Wu, Shutong Wu, Yulong Cao +1
With the fast development of large language models (LLMs), LLM-driven Web Agents (Web Agents for short) have obtained tons of attention due to their superior capability where LLMs…