• DocumentCode
    650689
  • Title

    An Accurate Stack Memory Abstraction and Symbolic Analysis Framework for Executables

  • Author

    Anand, Kushal ; ElWazeer, Khaled ; Kotha, Aparna ; Smithson, Matthew ; Barua, Rajeev ; Keromytis, Angelos

  • Author_Institution
    Univ. of Maryland, College Park, MD, USA
  • fYear
    2013
  • fDate
    22-28 Sept. 2013
  • Firstpage
    90
  • Lastpage
    99
  • Abstract
    This paper makes two contributions regarding reverse engineering of executables. First, techniques are presented for recovering a precise and correct stack memory model in executables in presence of executable-specific artifacts such as indirect control transfers. Next, the enhanced memory model is employed to define a novel symbolic analysis framework for executables that can perform the same types of program analysis as source-level tools. Frameworks hitherto fail to simultaneously maintain the properties of correct representation and precise memory model and ignore memory-allocated variables while defining symbolic analysis mechanisms. Our methods do not use symbolic, relocation, or debug information, which are usually absent in deployed binaries. We describe our framework, highlighting the novel intellectual contributions of our approach, and demonstrate its efficacy and robustness by applying it to various traditional analyses, including identifying information flow vulnerabilities in five real-world programs.
  • Keywords
    program diagnostics; reverse engineering; executable-specific artifacts; intellectual contributions; program analysis; reverse engineering; source-level tools; stack memory abstraction; symbolic analysis framework; Analytical models; Boundary conditions; Computational modeling; Equations; Mathematical model; Prototypes; Silicon; Binary Analysis; Reverse Engineering; Symbolic Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance (ICSM), 2013 29th IEEE International Conference on
  • Conference_Location
    Eindhoven
  • ISSN
    1063-6773
  • Type

    conf

  • DOI
    10.1109/ICSM.2013.20
  • Filename
    6676880