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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WCDCAnalyzer: Scalable Security Analysis of Wi-Fi Certified Device Connectivity...

Zilin Shen (Purdue University), Imtiaz Karim (The University of Texas at Dallas), Elisa Bertino (Purdue University)

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Private Yet Accurate: A Decentralized Approach to System Intrusion...

Jinghan Zhang (University of Virginia), Mati Ur Rehman (University of Virginia), Sharon Biju (University of Virginia), Saleha Muzammil (University of Virginia), Wajih Ul Hassan (University of Virginia)

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Building Next-Generation Datasets for Provenance-Based Intrusion Detection

Qizhi Cai (Zhejiang University), Lingzhi Wang (Northwestern University), Yao Zhu (Zhejiang University), Zhipeng Chen (Zhejiang University), Xiangmin Shen (Hofstra University), Zhenyuan Li (Zhejiang University)

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