Towards automatic discovery of deviations in binary implementations with applications to error detection and fingerprint generation

  • Authors:
  • David Brumley;Juan Caballero;Zhenkai Liang;James Newsome;Dawn Song

  • Affiliations:
  • Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University

  • Venue:
  • SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
  • Year:
  • 2007

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Abstract

Different implementations of the same protocol specification usually contain deviations, i.e., differences in how they check and process some of their inputs. Deviations are commonly introduced as implementation errors or as different interpretations of the same specification. Automatic discovery of these deviations is important for several applications. In this paper, we focus on automatic discovery of deviations for two particular applications: error detection and fingerprint generation. We propose a novel approach for automatically detecting deviations in the way different implementations of the same specification check and process their input. Our approach has several advantages: (1) by automatically building symbolic formulas from the implementation, our approach is precisely faithful to the implementation; (2) by solving formulas created from two different implementations of the same specification, our approach significantly reduces the number of inputs needed to find deviations; (3) our approach works on binaries directly, without access to the source code. We have built a prototype implementation of our approach and have evaluated it using multiple implementations of two different protocols: HTTP and NTP. Our results show that our approach successfully finds deviations between different implementations, including errors in input checking, and differences in the interpretation of the specification, which can be used as fingerprints.