MACKE: Compositional analysis of low-level vulnerabilities with symbolic execution

Saahil Ognawala, Martín Ochoa, Alexander Pretschner, Tobias Limmer

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

25 Scopus citations

Abstract

Concolic (concrete+symbolic) execution has recently gained popularity as an effective means to uncover non-trivial vulnerabilities in software, such as subtle buffer overows. However, symbolic execution tools that are designed to optimize statement coverage often fail to cover potentially vulnerable code because of complex system interactions and scalability issues of constraint solvers. In this paper, we present a tool (MACKE) that is based on the modular interactions inferred by static code analysis, which is combined with symbolic execution and directed inter-procedural path exploration. This provides an advantage in terms of statement coverage and ability to uncover more vulnerabilities. Our tool includes a novel feature in the form of interactive vulnerability report generation that helps developers prioritize bug fixing based on severity scores. A demo of our tool is available at https://youtu.be/icC3jc3mHEU.

Original languageEnglish
Title of host publicationASE 2016 - Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering
EditorsSarfraz Khurshid, David Lo, Sven Apel
PublisherAssociation for Computing Machinery, Inc
Pages780-785
Number of pages6
ISBN (Electronic)9781450338455
DOIs
StatePublished - 25 Aug 2016
Event31st IEEE/ACM International Conference on Automated Software Engineering, ASE 2016 - Singapore, Singapore
Duration: 3 Sep 20167 Sep 2016

Publication series

NameASE 2016 - Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering

Conference

Conference31st IEEE/ACM International Conference on Automated Software Engineering, ASE 2016
Country/TerritorySingapore
CitySingapore
Period3/09/167/09/16

Keywords

  • Compositional analysis
  • Symbolic execution

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