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Building Dynamic System Call Sandbox with Partial Order Analysis

  • Quan Zhang
  • , Chijin Zhou
  • , Yiwen Xu
  • , Zijing Yin
  • , Mingzhe Wang
  • , Zhuo Su
  • , Chengnian Sun
  • , Yu Jiang*
  • , Jiaguang Sun
  • *Corresponding author for this work
  • Tsinghua University
  • University of Waterloo

Research output: Contribution to journalArticlepeer-review

Abstract

Attack surface reduction is a security technique that secures the operating system by removing the unnecessary code or features of a program. By restricting the system calls that programs can use, the system call sandbox is able to reduce the exposed attack surface of the operating system and prevent attackers from damaging it through vulnerable programs. Ideally, programs should only retain access to system calls they require for normal execution. Many researchers focus on adopting static analysis to automatically restrict the system calls for each program. However, these methods do not adjust the restriction policy along with program execution. Thus, they need to permit all system calls required for program functionalities. We observe that some system calls, especially security-sensitive ones, are used a few times in certain stages of a program's execution and then never used again. This motivates us to minimize the set of required system calls dynamically. In this paper, we propose , which gradually disables access to unnecessary system calls throughout the program's execution. To accomplish this, we utilize partial order analysis to transform the program into a partially ordered graph, which enables efficient identification of the necessary system calls at any given point during program execution. Once a system call is no longer required by the program, can restrict it immediately. To evaluate , we applied it to seven widely-used programs with an average of 615 KLOC, including web servers and databases. With partial order analysis, restricts an average of 23.50, 16.86, and 15.89 more system calls than the state-of-the-art Chestnut, Temporal Specialization, and the configuration-aware sandbox, C2C, respectively. For mitigating malicious exploitations, on average, defeats 83.42% of 1726 exploitation payloads with only a 5.07% overhead.

Original languageEnglish
Pages (from-to)1253-1280
Number of pages28
JournalProceedings of the ACM on Programming Languages
Volume7
Issue numberOOPSLA2
DOIs
StatePublished - 16 Oct 2023
Externally publishedYes

Keywords

  • Attack Surface Reduction
  • Program Analysis
  • System Call Sandbox

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