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Commodity operating systems execute core kernel subsystems in a single address space along with hundreds of dynamically loaded extensions and device drivers. Lack of isolation within the kernel implies that a vulnerability in any of the kernel subsystems or device drivers opens a way to mount a successful attack on the entire kernel. Historically, isolation within the kernel remained prohibitive due to the high cost of hardware isolation primitives. Recent CPUs, however, bring a new set of mechanisms. Extended page-table (EPT) switching with VM functions and memory protection keys (MPKs) provide memory isolation and invocations across boundaries of protection domains with overheads comparable to system calls. Unfortunately, neither MPKs nor EPT switching provide architectural support for isolation of privileged ring 0 kernel code, i.e., control of privileged instructions and well-defined entry points to securely restore state of the system on transition between isolated domains. Our work develops a collection of techniques for lightweight isolation of privileged kernel code. To control execution of privileged instructions, we rely on a minimal hypervisor that transparently deprivileges the system into a non-root VT-x guest. We develop a new isolation boundary that leverages extended page table (EPT) switching with the VMFUNC instruction. We define a set of invariants that allows us to isolate kernel components in the face of an intricate execution model of the kernel, e.g., provide isolation of preemptable, concurrent interrupt handlers. To minimize overheads of virtualization, we develop support for exitless interrupt delivery across isolated domains. We evaluate our approach by developing isolated versions of several device drivers in the Linux kernel. 

Privilege separation is an effective technique to improve software security. However, past partitioning systems do not allow programmers to make quantitative tradeoffs between security and performance. In this paper, we describe our toolchain called PM. It can automatically find the optimal boundary in program partitioning. This is achieved by solving an integer-programming model that optimizes for a user-chosen metric while satisfying the remaining security and performance constraints on other metrics. We choose security metrics to reason about how well computed partitions enforce information flow control to: (1) protect the program from low-integrity inputs or (2) prevent leakage of program secrets. As a result, functions in the sensitive module that fall on the optimal partition boundaries automatically identify where declassification is necessary. We used PM to experiment on a set of real-world programs to protect confidentiality and integrity; results show that, with moderate user guidance, PM can find partitions that have better balance between security and performance than partitions found by a previous tool that requires manual declassification.