Lukas Maar (Graz University of Technology), Jonas Juffinger (Graz University of Technology), Thomas Steinbauer (Graz University of Technology), Daniel Gruss (Graz University of Technology), Stefan Mangard (Graz University of Technology)

The sharing of hardware elements, such as caches, is known to introduce microarchitectural side-channel leakage. One approach to eliminate this leakage is to not share hardware elements across security domains. However, even under the assumption of leakage-free hardware, it is unclear whether other critical system components, like the operating system, introduce software-caused side-channel leakage.

In this paper, we present a novel generic software side-channel attack, KernelSnitch, targeting kernel data structures such as hash tables and trees. These structures are commonly used to store both kernel and user information, e.g., metadata for userspace locks. KernelSnitch exploits that these data structures are variable in size, ranging from an empty state to a theoretically arbitrary amount of elements. Accessing these structures requires a variable amount of time depending on the number of elements, i.e., the occupancy level. This variance constitutes a timing side channel, observable from user space by an unprivileged, isolated attacker. While the timing differences are very low compared to the syscall runtime, we demonstrate and evaluate methods to amplify these timing differences reliably. In three case studies, we show that KernelSnitch allows unprivileged and isolated attackers to leak sensitive information from the kernel and activities in other processes. First, we demonstrate covert channels with transmission rates up to 580 kbit/s. Second, we perform a kernel heap pointer leak in less than 65 s by exploiting the specific indexing that Linux is using in hash tables. Third, we demonstrate a website fingerprinting attack, achieving an F1 score of more than 89 %, showing that activity in other user programs can be observed using KernelSnitch. Finally, we discuss mitigations for our hardware-agnostic attacks.

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Haotian Zhu (Nanjing University of Science and Technology), Shuchao Pang (Nanjing University of Science and Technology), Zhigang Lu (Western Sydney University), Yongbin Zhou (Nanjing University of Science and Technology), Minhui Xue (CSIRO's Data61)

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Minghong Fang (University of Louisville), Seyedsina Nabavirazavi (Florida International University), Zhuqing Liu (University of North Texas), Wei Sun (Wichita State University), Sundararaja Iyengar (Florida International University), Haibo Yang (Rochester Institute of Technology)

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cozy: Comparative Symbolic Execution for Binary Programs

Caleb Helbling, Graham Leach-Krouse, Sam Lasser, Greg Sullivan (Draper)

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