From debugging-information based binary-level type inference to CFG generation

Dongrui Zeng, Gang Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Binary-level Control-Flow Graph (CFG) construction is essential for applications such as control-flow integrity. There are two main approaches: the binary-analysis approach and the compiler-modification approach. The binary-analysis approach does not require source code, but it constructs low-precision CFGs. The compiler-modification approach requires source code and modifies compilers for CFG generation. We describe the design and implementation of an alternative system for high-precision CFG construction, which still assumes source code but does not modify compilers. Our approach makes use of standard compiler-generated meta-information, including symbol tables, relocation information, and debugging information. A key component in the system is a type-inference engine that infers types of low-level storage locations such as registers from types in debugging information. Inferred types enable a type-signature matching method for high-precision CFG construction.

Original languageEnglish (US)
Title of host publicationCODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy
PublisherAssociation for Computing Machinery, Inc
Pages366-376
Number of pages11
ISBN (Electronic)9781450356329
DOIs
StatePublished - Mar 13 2018
Event8th ACM Conference on Data and Application Security and Privacy, CODASPY 2018 - Tempe, United States
Duration: Mar 19 2018Mar 21 2018

Publication series

NameCODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy
Volume2018-January

Other

Other8th ACM Conference on Data and Application Security and Privacy, CODASPY 2018
CountryUnited States
CityTempe
Period3/19/183/21/18

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Software

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