• DocumentCode
    425442
  • Title

    Abstracting stack to detect obfuscated calls in binaries

  • Author

    Lakhotia, Arun ; Kumar, Eric Uday

  • Author_Institution
    Center for Adv. Comput. Studies, Louisiana Univ., Lafayette, LA
  • fYear
    2004
  • fDate
    16-16 Sept. 2004
  • Firstpage
    17
  • Lastpage
    26
  • Abstract
    Information about calls to the operating system (or kernel libraries) made by a binary executable may be used to determine whether the binary is malicious. Being aware of this approach, malicious programmers hide this information by making such calls without using the call instruction. For instance, the `call addr´ instruction may be replaced by two push instructions and a return instruction, the first push pushes the address of the instruction after the return instruction, and the second push pushes the address addr. The code may be further obfuscated by spreading the three instructions and by splitting each instruction into multiple instructions. This paper presents a method to statically detect obfuscated calls in binary code. The notion of abstract stack is introduced to associate each element in the stack to the instruction that pushes the element. An abstract stack graph is a concise representation of all abstract stacks at every point in the program. An abstract stack graph, created by abstract interpretation of the binary executables, may be used to detect obfuscated calls and other stack related obfuscations
  • Keywords
    binary codes; program compilers; binary codes; call addr instruction; call instruction; kernel libraries; malicious programmers; obfuscated call detection; operating system; Binary codes; Delay; Kernel; Laboratories; Libraries; Operating systems; Performance analysis; Programming profession; Protection; Viruses (medical);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Source Code Analysis and Manipulation, 2004. Fourth IEEE International Workshop on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-7695-2144-4
  • Type

    conf

  • DOI
    10.1109/SCAM.2004.2
  • Filename
    1386155