Kaihua Wang (Tsinghua University), Jianjun Chen (Tsinghua University), Pinji Chen (Tsinghua University), Jianwei Zhuge (Tsinghua University), Jiaju Bai (Beihang University), Haixin Duan (Tsinghua University)

QUIC is a modern transport protocol increasingly adopted by major platforms and services, making its security and correctness critically important. However, the complexity of QUIC specification and implementations introduces opportunities for subtle and dangerous logic flaws. Existing QUIC testing tools primarily focus on memory-related vulnerabilities and are ill-equipped to detect logical vulnerabilities. Therefore, the discovery of logical vulnerabilities is currently still highly dependent on manual auditing.

In this paper, we introduce MerCuriuzz, a novel black-box fuzzing framework designed to automatically uncover logical vulnerabilities in QUIC implementations. We evaluated MerCuriuzz against 16 widely used QUIC implementations and discovered 14 previously unknown logical vulnerabilities affecting popular implementations such as quiche, xquic, and aioquic. Those vulnerabilities can pose severe security risks, enabling attackers to exhaust server resources, crash services, or deny legitimate users access to the server. We categorize those vulnerabilities into six categories and propose mitigation strategies. We also responsibly disclosed our findings to the affected vendors, and 11 of them were confirmed and rewarded by the vendors, such as Cloudflare and Alibaba Cloud.

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Robust Fraud Transaction Detection: A Two-Player Game Approach

Qi Tan (College of Computer Science and Software Engineering, Shenzhen University), Yi Zhao (School of Cyberspace Science and Technology, Beijing Institute of Technology), Laizhong Cui (College of Computer Science and Software Engineering, Shenzhen University), Qi Li (Institute for Network Science and Cyberspace, Tsinghua University), Ming Zhu (Department of Computer Science and Technology, Tsinghua University), Xing…

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Validity Is Not Enough: Uncovering the Security Pitfall in...

Di Zhai (Beijing Jiaotong University), Jiashuo Zhang (Peking University), Jianbo Gao (Beijing Jiaotong University), Tianhao Liu (Beijing Jiaotong University), Tao Zhang (Beijing Jiaotong University), Jian Wang (Beijing Jiaotong University), Jiqiang Liu (Beijing Jiaotong University)

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Causal-Guided Detoxify Backdoor Attack of Open-Weight LoRA Models

Linzhi Chen (ShanghaiTech University), Yang Sun (Independent Researcher), Hongru Wei (ShanghaiTech University), Yuqi Chen (ShanghaiTech University)

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