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Statistical similarity of binaries

Authors:

Nimrod Partush,

Eran YahavAuthors Info & Claims

ACM SIGPLAN Notices, Volume 51, Issue 6

Pages 266 - 280

https://doi.org/10.1145/2980983.2908126

Published: 02 June 2016 Publication History

Abstract

We address the problem of finding similar procedures in stripped binaries. We present a new statistical approach for measuring the similarity between two procedures. Our notion of similarity allows us to find similar code even when it has been compiled using different compilers, or has been modified. The main idea is to use similarity by composition: decompose the code into smaller comparable fragments, define semantic similarity between fragments, and use statistical reasoning to lift fragment similarity into similarity between procedures. We have implemented our approach in a tool called Esh, and applied it to find various prominent vulnerabilities across compilers and versions, including Heartbleed, Shellshock and Venom. We show that Esh produces high accuracy results, with few to no false positives -- a crucial factor in the scenario of vulnerability search in stripped binaries.

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Cited By

Peng JWang YXue JLiu Z(2024)Fast Cross-Platform Binary Code Similarity Detection Framework Based on CFGs Taking Advantage of NLP and Inductive GNNChinese Journal of Electronics10.23919/cje.2022.00.22833:1(128-138)Online publication date: Jan-2024
https://doi.org/10.23919/cje.2022.00.228
Jia YYu ZHong Z(2024)Semantic aware-based instruction embedding for binary code similarity detectionPLOS ONE10.1371/journal.pone.030529919:6(e0305299)Online publication date: 11-Jun-2024
https://doi.org/10.1371/journal.pone.0305299
Lin RFu YYi WYang JCao JDong ZXie FLi H(2024)Vulnerabilities and Security Patches Detection in OSS: A SurveyACM Computing Surveys10.1145/369478257:1(1-37)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3694782
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Index Terms

Statistical similarity of binaries
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
    2. Formal language definitions
2. Theory of computation
  1. Formal languages and automata theory
  2. Semantics and reasoning
    1. Program semantics

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Information & Contributors

Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 51, Issue 6

PLDI '16

June 2016

726 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/2980983

Editor:
Andy Gill
University of Kansas, Lawrence, KS

Issue’s Table of Contents

PLDI '16: Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation
June 2016
726 pages
ISBN:9781450342612
DOI:10.1145/2908080
General Chair:
Chandra Krintz
University of California at Santa Barbara, USA
,
Program Chair:
Emery Berger
University of Massachusetts at Amherst, USA

Copyright © 2016 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 June 2016

Published in SIGPLAN Volume 51, Issue 6

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Cited By

Peng JWang YXue JLiu Z(2024)Fast Cross-Platform Binary Code Similarity Detection Framework Based on CFGs Taking Advantage of NLP and Inductive GNNChinese Journal of Electronics10.23919/cje.2022.00.22833:1(128-138)Online publication date: Jan-2024
https://doi.org/10.23919/cje.2022.00.228
Jia YYu ZHong Z(2024)Semantic aware-based instruction embedding for binary code similarity detectionPLOS ONE10.1371/journal.pone.030529919:6(e0305299)Online publication date: 11-Jun-2024
https://doi.org/10.1371/journal.pone.0305299
Lin RFu YYi WYang JCao JDong ZXie FLi H(2024)Vulnerabilities and Security Patches Detection in OSS: A SurveyACM Computing Surveys10.1145/369478257:1(1-37)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3694782
Jia LWu CZhang PWang ZShrivastava ASui Y(2024)CodeExtract: Enhancing Binary Code Similarity Detection with Code Extraction TechniquesProceedings of the 25th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems10.1145/3652032.3657572(143-154)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3652032.3657572
Wang HGao ZZhang CSun MZhou YQiu HXiao XChristakis MPradel M(2024)CEBin: A Cost-Effective Framework for Large-Scale Binary Code Similarity DetectionProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652117(149-161)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3652117
Eom HKim DLim SKoo HHwang S(2024)R2I: A Relative Readability Metric for Decompiled CodeProceedings of the ACM on Software Engineering10.1145/36437441:FSE(383-405)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3643744
Li LDing SWalenstein ACharland PFung BSerra ESpezzano F(2024)Dynamic Neural Control Flow Execution: an Agent-Based Deep Equilibrium Approach for Binary Vulnerability DetectionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679726(1215-1225)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679726
Zhang YFang BXiong ZWang YLiu YZheng CZhang Q(2024)A Semantics-Based Approach on Binary Function Similarity DetectionIEEE Internet of Things Journal10.1109/JIOT.2024.338901411:15(25910-25924)Online publication date: 1-Aug-2024
https://doi.org/10.1109/JIOT.2024.3389014
Wang HLiu ZWang SWang YTang QNie SWu S(2024)Are We There Yet? Filling the Gap Between Binary Similarity Analysis and Binary Software Composition Analysis2024 IEEE 9th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP60621.2024.00034(506-523)Online publication date: 8-Jul-2024
https://doi.org/10.1109/EuroSP60621.2024.00034
Zhang PWu CWang Z(2024)BinCodex: A comprehensive and multi-level dataset for evaluating binary code similarity detection techniquesBenchCouncil Transactions on Benchmarks, Standards and Evaluations10.1016/j.tbench.2024.1001634:2(100163)Online publication date: Jun-2024
https://doi.org/10.1016/j.tbench.2024.100163
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