Tianchang Yang (Pennsylvania State University), Sathiyajith K S (Pennsylvania State University), Ashwin Senthil Arumugam (Pennsylvania State University), Syed Rafiul Hussain (Pennsylvania State University)

We present our work-in-progress on designing and implementing a black-box evolutionary fuzzer for REST APIs, specifically targeting 5G core networks that utilize a service-based architecture (SBA). Unlike existing tools that rely on static generation-based approaches, our approach progressively refines test inputs to explore deeper code regions in the target system. We incorporate a thorough analysis of the limited response message feedback available in black-box settings and employ a carefully crafted mutation method to generate effective state-aware test inputs. Evaluation of our current implementation has uncovered two previously unknown vulnerabilities in open-source 5G core network implementations, resulting in the assignment of two CVEs. Additionally, our approach already demonstrates superior performance compared to existing black-box fuzzing methods.

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DeFiIntel: A Dataset Bridging On-Chain and Off-Chain Data for...

Iori Suzuki (Graduate School of Environment and Information Sciences, Yokohama National University), Yin Minn Pa Pa (Institute of Advanced Sciences, Yokohama National University), Nguyen Thi Van Anh (Institute of Advanced Sciences, Yokohama National University), Katsunari Yoshioka (Graduate School of Environment and Information Sciences, Yokohama National University)

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Secret Spilling Drive: Leaking User Behavior through SSD Contention

Jonas Juffinger (Graz University of Technology), Fabian Rauscher (Graz University of Technology), Giuseppe La Manna (Amazon), Daniel Gruss (Graz University of Technology)

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QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Matteo Marini (Sapienza University of Rome), Daniele Cono D'Elia (Sapienza University of Rome), Mathias Payer (EPFL), Leonardo Querzoni (Sapienza University of Rome)

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