HYPER-CUBE: High-Dimensional Hypervisor Fuzzing

NDSS(2020)

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摘要
Virtual machine monitors (VMMs, also called hypervisors) represent a very critical part of a modern software stack: compromising them could allow an attacker to take full control of the whole cloud infrastructure of any cloud provider. Hence their security is critical for many applications, especially in the context of Infrastructure-as-a-Service. In this paper, we present the design and implementation of HYPER-CUBE, a novel fuzzer that aims explicitly at testing hypervisors in an efficient, effective, and precise way. Our approach is based on a custom operating system that implements a custom bytecode interpreter. This high-throughput design for long-running, interactive targets allows us to fuzz a large number of both open source and proprietary hypervisors. In contrast to one-dimensional fuzzers such as AFL, HYPER-CUBE can interact with any number of interfaces in any order. Our evaluation results show that we can find more bugs (over 2x) and coverage (as much as 2 x) than state-of-the-art hypervisor fuzzers. In most cases, we were even able to do so using multiple orders of magnitude less time than comparable fuzzers. HYPER-CUBE was also able to rediscover a set of well-known hypervisor vulnerabilities, such as VENOM, in less than five minutes. In total, we found 54 novel bugs, and so far obtained 43 CVEs. Our evaluation results demonstrate that nextgeneration coverage-guided fuzzers should incorporate a higherthroughput design for long-running targets such as hypervisors.
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