Automated Bug Detection and Replay for COTS Linux Kernel Modules with Concolic Execution
2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)
Linux kernel is pervasive in the cloud, on mobile platforms, and on supercomputers. To support these diverse computing environments, the Linux kernel provides extensibility and modularity through Loadable Kernel Modules (LKM), while featuring a monolithic architecture for execution efficiency. This architecture design brings a major challenge to the security of Linux kernel. Having LKMs run in the same memory space as the base kernel on Ring 0, a single flaw from LKMs may compromise the entire system, e.g., gaining root access. However, validation and debugging of LKMs are inherently challenging, because of its special interface buried deeply in the kernel, and non-determinism from interrupts. Also, LKMs are shipped by various vendors and the public may not have access to their source code, making the validation even harder. In this paper, we propose a framework for efficient bug detection and replay of commercial off-the-shelf (COTS) Linux kernel modules based on concolic execution. Our framework automatically generates compact sets of test cases for COTS LKMs, proactively checks for common kernel bugs, and allows to reproduce reported bugs repeatedly with actionable test cases. We evaluate our approach on over 20 LKMs covering major modules from the network and sound subsystems of Linux kernel. The results show that our approach can effectively detect various kernel bugs, and reports 5 new vulnerabilities including an unknown flaw that allows non-privileged users to trigger a kernel panic. By leveraging the replay capability of our framework, we patched all the reported bugs in the Linux kernel upstream, including 3 patches that were selected to the stable release of Linux kernel and back-ported to numerous production kernel versions. We also compare our prototype with kAFL, the state-of-the-art kernel fuzzer, and demonstrate the effectiveness of concolic execution over fuzzing on the kernel level.
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Chen, B., Yang, Z., Lei, L., Cong, K., & Xie, F. (2020). Automated Bug Detection and Replay for COTS Linux Kernel Modules with Concolic Execution. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/saner48275.2020.9054797