VDF: Targeted Evolutionary Fuzz Testing of Virtual Devices

As cloud computing becomes more and more prevalent, there is increased interest in mitigating attacks that target hypervisors from within the virtualized guest environments that they host. We present VDF, a targeted evolutionary fuzzing framework for discovering bugs within the software-based virtual devices implemented as part of a hypervisor. To achieve this, VDF selectively instruments the code of a given virtual device, and performs record and replay of memory-mapped I/O (MMIO) activity specific to the virtual device. We evaluate VDF by performing cloud-based parallel fuzz testing of eighteen virtual devices implemented within the QEMU hypervisor, executing over two billion test cases and revealing over one thousand unique crashes or hangs in one third of the tested devices. Our custom test case minimization algorithm further reduces the erroneous test cases into only 18.57% of the original sizes on average.