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KSplit: Automating Device Driver Isolation

Yongzhe Huang, Vikram Narayanan, David Detweiler, Kaiming Huang, Gang Tan, Trent Jaeger, Anton Burtsev

2022Year
26Citations
9Top-tier citations

Abstract

Researchers have shown that recent CPU extensions support practical, low-overhead driver isolation to protect kernels from defects and vulnerabilities in device drivers. With performance no longer being the main roadblock, the complexity of isolating device drivers has become the main challenge. Device drivers and kernel extensions are developed in a shared memory environment in which the state shared between the kernel and the driver is mixed in a complex hierarchy of data structures, making it difficult for programmers to ensure that the shared state is synchronized correctly. In this paper, we present KSplit, a new framework for isolating unmodified device drivers in a modern, full-featured kernel. KSplit performs automated analyses on the unmodified source code of the kernel and the driver to: 1) identify the state shared between the kernel and driver and 2) to compute the synchronization requirements for this shared state for efficient isolation. While some kernel idioms present ambiguities that cannot be resolved automatically at present, KSplit classifies most ambiguous pointers and identifies ones requiring manual intervention. We evaluate our solution on nine subsystems in the Linux kernel by applying KSplit to 354 device drivers and validating isolation for 10 drivers. For example, for a complex ixgbe driver, KSplit requires only 53 lines of manual changes to 2,476 lines of automatically generated interface specifications and 19 lines of changes to the driver's code. The KSplit analysis of the 354 drivers shows a similar fraction of manual work is expected, showing that KSplit is a practical tool for automating key tasks to enable driver isolation.

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