Yinggang Guo (State Key Laboratory for Novel Software Technology, Nanjing University; University of Minnesota), Zicheng Wang (State Key Laboratory for Novel Software Technology, Nanjing University), Weiheng Bai (University of Minnesota), Qingkai Zeng (State Key Laboratory for Novel Software Technology, Nanjing University), Kangjie Lu (University of Minnesota)

The endless stream of vulnerabilities urgently calls for principled mitigation to confine the effect of exploitation. However, the monolithic architecture of commodity OS kernels, like the Linux kernel, allows an attacker to compromise the entire system by exploiting a vulnerability in any kernel component. Kernel compartmentalization is a promising approach that follows the least-privilege principle. However, existing mechanisms struggle with the trade-off on security, scalability, and performance, given the challenges stemming from mutual untrustworthiness among numerous and complex components.

In this paper, we present BULKHEAD, a secure, scalable, and efficient kernel compartmentalization technique that offers bi-directional isolation for unlimited compartments. It leverages Intel's new hardware feature PKS to isolate data and code into mutually untrusted compartments and benefits from its fast compartment switching. With untrust in mind, BULKHEAD introduces a lightweight in-kernel monitor that enforces multiple important security invariants, including data integrity, execute-only memory, and compartment interface integrity. In addition, it provides a locality-aware two-level scheme that scales to unlimited compartments. We implement a prototype system on Linux v6.1 to compartmentalize loadable kernel modules (LKMs). Extensive evaluation confirms the effectiveness of our approach. As the system-wide impacts, BULKHEAD incurs an average performance overhead of 2.44% for real-world applications with 160 compartmentalized LKMs. While focusing on a specific compartment, ApacheBench tests on ipv6 show an overhead of less than 2%. Moreover, the performance is almost unaffected by the number of compartments, which makes it highly scalable.

View More Papers

Towards Understanding Unsafe Video Generation

Yan Pang (University of Virginia), Aiping Xiong (Penn State University), Yang Zhang (CISPA Helmholtz Center for Information Security), Tianhao Wang (University of Virginia)

Read More

MTZK: Testing and Exploring Bugs in Zero-Knowledge (ZK) Compilers

Dongwei Xiao (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Yiteng Peng (The Hong Kong University of Science and Technology), Shuai Wang (The Hong Kong University of Science and Technology)

Read More

Oreo: Protecting ASLR Against Microarchitectural Attacks

Shixin Song (Massachusetts Institute of Technology), Joseph Zhang (Massachusetts Institute of Technology), Mengjia Yan (Massachusetts Institute of Technology)

Read More

A Systematic Evaluation of Novel and Existing Cache Side...

Fabian Rauscher (Graz University of Technology), Carina Fiedler (Graz University of Technology), Andreas Kogler (Graz University of Technology), Daniel Gruss (Graz University of Technology)

Read More