Many existing techniques for reversing data structures in C/C ++ binaries are limited to low-level programming constructs, such as individual variables or structs. Unfortunately, without detailed information about a program's pointer structures, forensics and reverse engineering are exceedingly hard. To fill this gap, we propose MemPick, a tool that detects and classifies high-level data structures used in stripped binaries. By analyzing how links between memory objects evolve throughout the program execution, it distinguishes between many commonly used data structures, such as singly- or doubly-linked lists, many types of trees (e.g., AVL, red-black trees, B-trees), and graphs. We evaluate the technique on 10 real world applications, 4 file system implementations and 16 popular libraries. The results show that MemPick can identify the data structures with high accuracy.
CITATION STYLE
Haller, I., Slowinska, A., & Bos, H. (2016). Scalable data structure detection and classification for C/C++ binaries. Empirical Software Engineering, 21(3), 778–810. https://doi.org/10.1007/s10664-015-9363-y
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