SLAKE: Facilitating Slab Manipulation for Exploiting Vulnerabilities in the Linux Kernel

被引:29
|
作者
Chen, Yueqi [1 ]
Xing, Xinyu [1 ]
机构
[1] Penn State Univ, University Pk, PA 16802 USA
来源
PROCEEDINGS OF THE 2019 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'19) | 2019年
关键词
OS Security; Vulnerability Exploitation;
D O I
10.1145/3319535.3363212
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To determine the exploitability for a kernel vulnerability, a security analyst usually has to manipulate slab and thus demonstrate the capability of obtaining the control over a program counter or performing privilege escalation. However, this is a lengthy process because (1) an analyst typically has no clue about what objects and system calls are useful for kernel exploitation and (2) he lacks the knowledge of manipulating a slab and obtaining the desired layout. In the past, researchers have proposed various techniques to facilitate exploit development. Unfortunately, none of them can be easily applied to address these challenges. On the one hand, this is because of the complexity of the Linux kernel. On the other hand, this is due to the dynamics and non-deterministic of slab variations. In this work, we tackle the challenges above from two perspectives. First, we use static and dynamic analysis techniques to explore the kernel objects, and the corresponding system calls useful for exploitation. Second, we model commonly-adopted exploitation methods and develop a technical approach to facilitate the slab layout adjustment. By extending LLVM as well as Syzkaller, we implement our techniques and name their combination after SLAKE. We evaluate SLAKE by using 27 real-world kernel vulnerabilities, demonstrating that it could not only diversify the ways to perform kernel exploitation but also sometimes escalate the exploitability of kernel vulnerabilities.
引用
收藏
页码:1707 / 1722
页数:16
相关论文
共 1 条
  • [1] From Release to Rebirth: Exploiting Thanos Objects in Linux Kernel
    Liu, Danjun
    Wang, Pengfei
    Zhou, Xu
    Xie, Wei
    Zhang, Gen
    Luo, Zhenhao
    Yue, Tai
    Wang, Baosheng
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 18 : 533 - 548