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.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 37 [1] => 104 ) ) ) [post__not_in] => Array ( [0] => 17332 ) )

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by...

Peizhuo Lv (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Pan Li (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Shenchen Zhu (Institute of Information Engineering, Chinese Academy of Sciences, China;…

Read More

Transforming Raw Authentication Logs into Interpretable Events

Seth Hastings, Tyler Moore, Corey Bolger, Philip Schumway (University of Tulsa)

Read More

Facilitating Threat Modeling by Leveraging Large Language Models

Isra Elsharef, Zhen Zeng (University of Wisconsin-Milwaukee), Zhongshu Gu (IBM Research)

Read More

WIP: Security Vulnerabilities and Attack Scenarios in Smart Home...

Haoqiang Wang (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Yichen Liu (Indiana University Bloomington), Yiwei Fang, Ze Jin, Qixu Liu (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Luyi Xing (Indiana University Bloomington)

Read More

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)