Compiler-Agnostic Function Detection in Binaries

2017 IEEE European Symposium on Security and Privacy (EuroS&P)(2017)

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摘要
We propose Nucleus, a novel function detection algorithm for binaries. In contrast to prior work, Nucleus is compiler-agnostic, and does not require any learning phase or signature information. Instead of scanning for signatures, Nucleus detects functions at the Control Flow Graph-level, making it inherently suitable for difficult cases such as non-contiguous or multi-entry functions. We evaluate Nucleus on a diverse set of 476 C and C ++ binaries, compiled with gcc, clang and Visual Studio for x86 and x64, at optimization levels O0-O3. We achieve consistently good performance, with a mean F-score of 0.95.
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关键词
Disassembly,static analysis,function detection,reverse engineering
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