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.

View More Papers

KnowHow: Automatically Applying High-Level CTI Knowledge for Interpretable and...

Yuhan Meng (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Jiaping Gui (School of Computer Science, Shanghai Jiao Tong University), Peng Jiang (Southeast University), Ding Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of…

Read More

Constructive Noise Defeats Adversarial Noise: Adversarial Example Detection for...

Meng Shen (Beijing Institute of Technology), Jiangyuan Bi (Beijing Institute of Technology), Hao Yu (National University of Defense Technology), Zhenming Bai (Beijing Institute of Technology), Wei Wang (Xi'an Jiaotong University), Liehuang Zhu (Beijing Institute of Technology)

Read More

ACTS: Attestations of Contents in TLS Sessions

Pierpaolo Della Monica (Sapienza University of Rome), Ivan Visconti (Sapienza University of Rome), Andrea Vitaletti (Sapienza University of Rome), Marco Zecchini (Sapienza University of Rome)

Read More