Romain Malmain (EURECOM), Andrea Fioraldi (EURECOM), Aurelien Francillon (EURECOM)

Despite QEMU’s popularity for binary-only fuzzing, the fuzzing community faces challenges like the proliferation of hard-to-maintain QEMU forks and the lack of an up-to-date, flexible framework well-integrated with advanced fuzzing engines. This leads to a gap in emulation-based fuzzing tools that are both maintainable and fuzzing-oriented.

To cope with that, we present LIBAFL QEMU, a library written in Rust that provides an interface for fuzzing-based emulation by wrapping around QEMU, in both system and user mode. We focus on addressing the limitations of existing QEMU forks used in fuzzing by offering a well-integrated, maintainable and up-to-date solution. In this paper, we detail the design, implementation, and practical challenges of LIBAFL QEMU, including its APIs and fuzzing capabilities and we showcase the library’s use in two case studies: fuzzing an Android library and a Windows kernel driver.

We compare the fuzzers written for these 2 targets with the state-of-the-art, AFL++ qemu mode for the Android library, and KAFL for the Windows driver. For the former, we show that LIBAFL QEMU outperforms AFL++ qemu mode both in terms of speed and coverage. For the latter, despite KAFL being built above hardware-based virtualization instead of emulation, we show we can run complex targets such as Windows and still reach comparable performance, with an overhead expected by a software emulator.

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Separation is Good: A Faster Order-Fairness Byzantine Consensus

Ke Mu (Southern University of Science and Technology, China), Bo Yin (Changsha University of Science and Technology, China), Alia Asheralieva (Loughborough University, UK), Xuetao Wei (Southern University of Science and Technology, China & Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, SUSTech, China)

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Front-running Attack in Sharded Blockchains and Fair Cross-shard Consensus

Jianting Zhang (Purdue University), Wuhui Chen (Sun Yat-sen University), Sifu Luo (Sun Yat-sen University), Tiantian Gong (Purdue University), Zicong Hong (The Hong Kong Polytechnic University), Aniket Kate (Purdue University)

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Securing Automotive Software Supply Chains (Long)

Marina Moore, Aditya Sirish A Yelgundhalli (New York University), Justin Cappos (NYU)

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The Inconvenient Truths of Ground Truth for Binary Analysis

Jim Alves-Foss, Varsha Venugopal (University of Idaho)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)