12 citations · 28 across the 35 of their papers we have counts for
36 papers
The Safeguard Worked. Is the LLM System Safer?
Pingyu Wu, Weiming Zhang, Nenghai Yu
Safeguards in deployed LLM services are evaluated by refusal, attack success, and policy violation rates. Those rates characterize how a control performed on the requests it was te…
Breadcrumbing Search Agents
Xuebin Li, Hanqing Zhao, Siyuan Liang +4
LLM-based search agents are widely used for information-seeking tasks, but their reliance on external tool returns introduces a critical security risk: web content retrieved during…
Beyond Text Matching: Towards Reference-Free Evaluation for Human-Oriented Binary Reverse Engineering
Xiuwei Shang, Li Hu, Xiao Jiang +7
Human-Oriented Binary Reverse Engineering (HOBRE) aims to transform decompiled pseudocode into a more human-friendly representation, thereby reducing the cognitive burden of revers…
Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs
Pingyu Wu, Lingyao Zhu, Weiming Zhang +1
Large language model safeguards decide whether to answer before seeing how an answer will be used. This creates a basic problem for dual-use tasks: the same answer can help an auth…
Cross-modal Retrieval Models for Stripped Binary Analysis
Guoqiang Chen, Lingyun Ying, Ziyang Song +7
Retrieving binary code via natural language queries is a pivotal capability for downstream tasks in the software security domain, such as vulnerability detection and malware analys…
PSRT: Accelerating LRM-based Guard Models via Prefilled Safe Reasoning Traces
Jiawei Zhao, Yuang Qi, Weiming Zhang +2
Large Reasoning Models (LRMs) have demonstrated remarkable performance on tasks such as mathematics and code generation. Motivated by these strengths, recent work has empirically d…
Multimodal Prompt Decoupling Attack on the Safety Filters in Text-to-Image Models
Xingkai Peng, Jun Jiang, Meng Tong +4
Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work…
ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing
Long Xing, Qidong Huang, Xiaoyi Dong +10
This paper presents ScaleCap, an inference-time scalable image captioning strategy that generates comprehensive and detailed image captions. The key challenges of high-quality imag…
TAG-WM: Tamper-Aware Generative Image Watermarking via Diffusion Inversion Sensitivity
Yuzhuo Chen, Zehua Ma, Han Fang +2
AI-generated content (AIGC) enables efficient visual creation but raises copyright and authenticity risks. As a common technique for integrity verification and source tracing, digi…
BinMetric: A Comprehensive Binary Analysis Benchmark for Large Language Models
Xiuwei Shang, Guoqiang Chen, Shaoyin Cheng +5
Binary analysis remains pivotal in software security, offering insights into compiled programs without source code access. As large language models (LLMs) continue to excel in dive…
CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System
Li Hu, Guoqiang Chen, Xiuwei Shang +6
With open-source projects growing in size and complexity, manual compilation becomes tedious and error-prone, highlighting the need for automation to improve efficiency and accurac…
An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding
Xiuwei Shang, Zhenkan Fu, Shaoyin Cheng +5
Binary code analysis plays a pivotal role in the field of software security and is widely used in tasks such as software maintenance, malware detection, software vulnerability disc…
Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing
Shuai Li, Jie Zhang, Yuang Qi +4
Large-scale image retrieval using deep hashing has become increasingly popular due to the exponential growth of image data and the remarkable feature extraction capabilities of dee…
MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAG
Pingyu Wu, Daiheng Gao, Jing Tang +4
Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by using external knowledge, but it struggles with precise entity information retrieval. In this paper, w…
Beyond the Edge of Function: Unraveling the Patterns of Type Recovery in Binary Code
Gangyang Li, Xiuwei Shang, Shaoyin Cheng +5
Type recovery is a crucial step in binary code analysis, holding significant importance for reverse engineering and various security applications. Existing works typically simply t…
M3-AGIQA: Multimodal, Multi-Round, Multi-Aspect AI-Generated Image Quality Assessment
Chuan Cui, Kejiang Chen, Zhihua Wei +3
The rapid advancement of AI-generated image (AIGI) models presents new challenges for evaluating image quality, particularly across three aspects: perceptual quality, prompt corres…
AutoPT: How Far Are We from the End2End Automated Web Penetration Testing?
Benlong Wu, Guoqiang Chen, Kejiang Chen +5
Penetration testing is essential to ensure Web security, which can detect and fix vulnerabilities in advance, and prevent data leakage and serious consequences. The powerful infere…
SQL Injection Jailbreak: A Structural Disaster of Large Language Models
Jiawei Zhao, Kejiang Chen, Weiming Zhang +1
Large Language Models (LLMs) are susceptible to jailbreak attacks that can induce them to generate harmful content. Previous jailbreak methods primarily exploited the internal prop…
Binary Code Similarity Detection via Graph Contrastive Learning on Intermediate Representations
Xiuwei Shang, Li Hu, Shaoyin Cheng +4
Binary Code Similarity Detection (BCSD) plays a crucial role in numerous fields, including vulnerability detection, malware analysis, and code reuse identification. As IoT devices…
Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate
Qidong Huang, Xiaoyi Dong, Pan Zhang +6
We present the Modality Integration Rate (MIR), an effective, robust, and generalized metric to indicate the multi-modal pre-training quality of Large Vision Language Models (LVLMs…
GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models
Kunsheng Tang, Wenbo Zhou, Jie Zhang +7
Large language models (LLMs) have exhibited remarkable capabilities in natural language generation, but they have also been observed to magnify societal biases, particularly those…
SPSW: Database Watermarking Based on Fake Tuples and Sparse Priority Strategy
Zhiwen Ren, Zehua Ma, Weiming Zhang +1
Databases play a crucial role in storing and managing vast amounts of data in various organizations and industries. Yet the risk of database leakage poses a significant threat to d…
©Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model
Chao Zhou, Huishuai Zhang, Jiang Bian +2
This paper addresses the contentious issue of copyright infringement in images generated by text-to-image models, sparking debates among AI developers, content creators, and legal…
How Far Have We Gone in Binary Code Understanding Using Large Language Models
Xiuwei Shang, Shaoyin Cheng, Guoqiang Chen +6
Binary code analysis plays a pivotal role in various software security applications, such as software maintenance, malware detection, software vulnerability discovery, patch analys…