{"title":"MemPick: High-level data structure detection in C/C++ binaries","authors":"I. Haller, Asia Slowinska, H. Bos","doi":"10.1109/WCRE.2013.6671278","DOIUrl":null,"url":null,"abstract":"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 and 16 popular libraries. The results show that MemPick can identify the data structures with high accuracy.","PeriodicalId":275092,"journal":{"name":"2013 20th Working Conference on Reverse Engineering (WCRE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 20th Working Conference on Reverse Engineering (WCRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCRE.2013.6671278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
Abstract
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 and 16 popular libraries. The results show that MemPick can identify the data structures with high accuracy.