KASR: A Reliable and Practical Approach to Attack Surface Reduction of Commodity OS Kernels
Zhi Zhang, Yueqiang Cheng, Surya Nepal, Dongxi Liu, Qingni Shen, Fethi, Rabhi

TL;DR
KASR is a system that reduces the attack surface of commodity OS kernels at runtime by disabling unused code and segmenting used code, enhancing security with minimal performance impact.
Contribution
KASR introduces a hypervisor-based, source-code-independent method for dynamically reducing kernel attack surfaces through code permission management and segmentation.
Findings
Reduces kernel attack surface by 64%
Blocks all tested kernel rootkits
Imposes less than 1% performance overhead
Abstract
Commodity OS kernels have broad attack surfaces due to the large code base and the numerous features such as device drivers. For a real-world use case (e.g., an Apache Server), many kernel services are unused and only a small amount of kernel code is used. Within the used code, a certain part is invoked only at runtime while the rest are executed at startup and/or shutdown phases in the kernel's lifetime run. In this paper, we propose a reliable and practical system, named KASR, which transparently reduces attack surfaces of commodity OS kernels at runtime without requiring their source code. The KASR system, residing in a trusted hypervisor, achieves the attack surface reduction through a two-step approach: (1) reliably depriving unused code of executable permissions, and (2) transparently segmenting used code and selectively activating them. We implement a prototype of KASR on…
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