ViDeZZo: Dependency-aware Virtual Device Fuzzing
Qiang Liu, Flavio Toffalini, Yajin Zhou, Mathias Payer
摘要
A virtual machine interacts with its host environment through virtual devices, driven by virtual device messages, e.g., I/O operations. By issuing crafted messages, an adversary can exploit a vulnerability in a virtual device to escape the virtual machine, gaining host access. Even though hundreds of bugs in virtual devices have been discovered, coverage-based virtual device fuzzers hardly consider intra-message dependencies (a field in a virtual device message may be dependent on another field) and inter-message dependencies (a message may depend on a previously issued message), thus resulting in limited scalability or efficiency.ViDeZZo, our new dependency-aware fuzzing framework for virtual devices, overcomes the limitations of existing virtual device fuzzers by annotating intra-message dependencies with a lightweight grammar, and by self-learning inter-message dependencies with new mutation rules. Specifically, ViDeZZo annotates message dependencies and applies three categories of message mutators. This approach avoids heavy manual effort to analyze specifications and speeds up the slow exploration by satisfying dependencies, resulting in a scalable and efficient fuzzer that boosts bug discovery in virtual devices.In our evaluation, ViDeZZo covers two hypervisors, four architectures, five device categories, and 28 virtual devices, and reaches competitive coverage faster. Moreover, ViDeZZo successfully finds 24 existing and 28 new bugs across diverse bug types. We are actively engaging with the community with 7 of our submitted patches already accepted.
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引用它的顶会 Paper11
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- HYPERPILL: Fuzzing for Hypervisor-bugs by leveraging the Hardware Virtualization InterfaceAlexander Bulekov, Qiang Liu, Manuel Egele, Mathias PayerUSENIX Security 2024 · 被引用 15 次
- Atlas: Automating Cross-Language Fuzzing on Android Closed-Source LibrariesHao Xiong, Qinming Dai, Rui Chang, Mingran Qiu 等ISSTA 2024 · 被引用 6 次
- Breaking Isolation: A New Perspective on Hypervisor Exploitation via Cross-Domain AttacksGaoning Pan, Yiming Tao, Qinying Wang, Chunming Wu 等NDSS 2026
- Sheep's Clothing, Wolf's Data: Detecting Server-Induced Client Vulnerabilities in Windows Remote IPCFangming Gu, Qingli Guo, Jie Lu, Qinghe Xie 等NDSS 2025
它引用的顶会 Paper17
- Evaluating Fuzz TestingGeorge Klees, Andrew Ruef, Benji Cooper, Shiyi Wei 等CCS 2018 · 被引用 753 次
- Skyfire: Data-Driven Seed Generation for FuzzingJunjie Wang, Bihuan Chen, Lei Wei, Yang LiuS&P 2017 · 被引用 382 次
- NAUTILUS: Fishing for Deep Bugs with GrammarsCornelius Aschermann, Tommaso Frassetto, Thorsten Holz, Patrick Jauernig 等NDSS 2019 · 被引用 291 次
- DIFUZE: Interface Aware Fuzzing for Kernel DriversJake Corina, Aravind Machiry, Christopher Salls, Yan Shoshitaishvili 等CCS 2017 · 被引用 195 次
- MoonShine: Optimizing OS Fuzzer Seed Selection with Trace DistillationShankara Pailoor, Andrew Aday, Suman JanaUSENIX Security 2018 · 被引用 180 次
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