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C2C: Fine-grained Configuration-driven System Call Filtering

  • Stony Brook University
  • Purdue University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

Configuration options allow users to customize application features according to the desired requirements. While the code that corresponds to disabled features is never executed, it still resides in process memory and comprises part of the application's attack surface, e.g., it can be reused for the construction of exploit code. Automatically reducing the attack surface of disabled application features according to a given configuration is thus a desirable defense-in-depth capability. The intricacies of modern software design and the complexities of popular programming languages, however, introduce significant challenges in automatically deriving the mapping of configuration options to their corresponding application code. In this paper, we present Configuration-to-Code (C2C), a generic configuration-driven attack surface reduction technique that automatically maps configuration options to application code using static code analysis and instrumentation. C2C operates at a fine-grained level by pruning configuration-dependent conditional branches in the control flow graph, allowing the precise identification of a given configuration option's code at the basic block level. At runtime, C2C reduces the application's attack surface by filtering any system calls required exclusively by disabled features. Using popular applications, we show how security-critical system calls (such as execve) can be automatically disabled when not needed, limiting an attacker's vulnerability exploitation capabilities. System call filtering also reduces the exposed attack surface of the underlying Linux kernel, neutralizing 32 additional CVEs (for a total of 88) compared to previous software specialization techniques.

Original languageEnglish
Title of host publicationCCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages1243-1257
Number of pages15
ISBN (Electronic)9781450394505
DOIs
StatePublished - Nov 7 2022
Event28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022 - Hybrid, Los Angeles, United States
Duration: Nov 7 2022Nov 11 2022

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022
Country/TerritoryUnited States
CityHybrid, Los Angeles
Period11/7/2211/11/22

Keywords

  • attack surface reduction
  • configuration
  • system call filtering

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