A Hybrid Alias Analysis and Its Application to Global Variable Protection in the Linux Kernel
Guoren Li, Hang Zhang, Jinmeng Zhou, Wenbo Shen, Yulei Sui, Zhiyun Qian
摘要
Global variables in the Linux kernel have been a common target of memory corruption attacks to achieve privilege escalation. Several potential defense mechanisms can be employed to safeguard global variables. One approach involves placing global variables in read-only pages after kernel initialization (ro_after_init), while another involves employing software fault isolation (SFI) to dynamically block unintended writes to these variables. To deploy such solutions in practice, a key building block is a sound, precise, and scalable alias analysis that is capable of identifying all the pointer aliases of global variables, as any pointer alias may be used for intended writes to a global variable. Unfortunately, the two existing styles of data-flow-based (e.g., Andersen-style) alias analysis and typebased alias analysis have serious limitations in scalability and precision when applied to the Linux kernel. This paper proposes a novel and general hybrid alias analysis that unifies the two complementary approaches in a graph reachability framework using context-free-language, also known as CFL-reachability. We show our hybrid alias analysis is extremely effective, significantly and simultaneously outperforming the data-flow-based alias analysis in scalability and the type-based alias analysis in precision. Under the same time budget, our hybrid analysis finds 42% of the Linux kernel global variables protectable as ro_after_init, whereas the two separate analyses find a combined 16% only.
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