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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dAngr: Lifting Software Debugging to a Symbolic Level

Dairo de Ruck, Jef Jacobs, Jorn Lapon, Vincent Naessens (DistriNet, KU Leuven, 3001 Leuven, Belgium)

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Careful About What App Promotion Ads Recommend! Detecting and...

Shang Ma (University of Notre Dame), Chaoran Chen (University of Notre Dame), Shao Yang (Case Western Reserve University), Shifu Hou (University of Notre Dame), Toby Jia-Jun Li (University of Notre Dame), Xusheng Xiao (Arizona State University), Tao Xie (Peking University), Yanfang Ye (University of Notre Dame)

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SHAFT: Secure, Handy, Accurate and Fast Transformer Inference

Andes Y. L. Kei (Chinese University of Hong Kong), Sherman S. M. Chow (Chinese University of Hong Kong)

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