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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Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A...

Ningfei Wang (University of California, Irvine), Shaoyuan Xie (University of California, Irvine), Takami Sato (University of California, Irvine), Yunpeng Luo (University of California, Irvine), Kaidi Xu (Drexel University), Qi Alfred Chen (University of California, Irvine)

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Fuzzing Space Communication Protocols

Stephan Havermans (IMDEA Software Institute), Lars Baumgaertner, Jussi Roberts, Marcus Wallum (European Space Agency), Juan Caballero (IMDEA Software Institute)

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Oreo: Protecting ASLR Against Microarchitectural Attacks

Shixin Song (Massachusetts Institute of Technology), Joseph Zhang (Massachusetts Institute of Technology), Mengjia Yan (Massachusetts Institute of Technology)

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DRAGON: Predicting Decompiled Variable Data Types with Learned Confidence...

Caleb Stewart, Rhonda Gaede, Jeffrey Kulick (University of Alabama in Huntsville)

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