Adaptive Android Kernel Live Patching
Yue Chen, Yulong Zhang, Zhi Wang, Liangzhao Xia, Chenfu Bao, Tao Wei
摘要
Android kernel vulnerabilities pose a serious threat to user security and privacy. They allow attackers to take full control over victim devices, install malicious and unwanted apps, and maintain persistent control. Unfortunately, most Android devices are never timely updated to protect their users from kernel exploits. Recent Android malware even has built-in kernel exploits to take advantage of this large window of vulnerability. An effective solution to this problem must be adaptable to lots of (out-of-date) devices, quickly deployable, and secure from misuse. However, the fragmented Android ecosystem makes this a complex and challenging task.
To address that, we systematically studied 1, 139 Android kernels and all the recent critical Android kernel vulnerabilities. We accordingly propose KARMA, an adaptive live patching system for Android kernels. KARMA features a multi-level adaptive patching model to protect kernel vulnerabilities from exploits. Specifically, patches in KARMA can be placed at multiple levels in the kernel to filter malicious inputs, and they can be automatically adapted to thousands of Android devices. In addition, KARMA's patches are written in a high-level memory-safe language, making them secure and easy to vet, and their run-time behaviors are strictly confined to prevent them from being misused. Our evaluation demonstrates that KARMA can protect most critical kernel vulnerabilities on many Android devices (520 devices in our evaluation) with only minor performance overhead (< 1%).
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引用它的顶会 Paper26
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