Title:
Breaking Kernel Address Space Layout Randomization (KASLR) with Intel TSX
Breaking Kernel Address Space Layout Randomization (KASLR) with Intel TSX
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Author(s)
Jang, Yeongjin
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Abstract
Kernel hardening has been an important topic, as many applications and security mechanisms often consider the kernel their Trusted Computing Base (TCB). Among various hardening techniques, kernel address space layout randomization (KASLR) is the most effective and widely adopted technique that can practically mitigate various memory corruption vulnerabilities, such as buffer overflow and use-after-free. In principle, KASLR is secure as long as no memory disclosure vulnerability exists and high randomness is ensured. In this talk, we present a novel timing side-channel attack against KASLR, called DrK (De-randomizing Kernel address space), which can accurately, silently, and rapidly de-randomize the kernel memory layout by identifying page properties: unmapped, executable, or non-executable pages. DrK is based on a new hardware feature, Intel Transactional Synchronization Extension (TSX), which allows us to execute a transaction without interrupting the underlying operating system even when the transaction is aborted due to errors, such as access violation and page faults. In DrK, we turned this property into a timing channel that can accurately distinguish the mapping status (i.e., mapped versus unmapped) and execution status (i.e., executable versus non-executable) of the privileged address space. In addition to its surprising accuracy and precision, the DrK attack is not only universally applicable to all OSes, even under a virtualized environment, but also has no visible footprint, making it nearly impossible to be detected in practice. We demonstrate that DrK breaks the KASLR of all major OSes, including Windows, Linux, and OS X with near-perfect accuracy in a few seconds. Finally, we propose potential hardware modifications that can prevent or mitigate the DrK attack.
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Date Issued
2016-09-23
Extent
57:20 minutes
Resource Type
Moving Image
Resource Subtype
Lecture