research-article

Extracting Conditional Formulas for Cross-Platform Bug Search

Authors:

Andrew Henderson,

Heng YinAuthors Info & Claims

ASIA CCS '17: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security

Pages 346 - 359

https://doi.org/10.1145/3052973.3052995

Published: 02 April 2017 Publication History

Abstract

With the recent increase in security breaches in embedded systems and IoT devices, it becomes increasingly important to search for vulnerabilities directly in binary executables in a cross-platform setting. However, very little has been explored in this domain. The existing efforts are prone to producing considerable false positives, and their results cannot provide explainable evidence for human analysts to eliminate these false positives. In this paper, we propose to extract conditional formulas as higher-level semantic features from the raw binary code to conduct the code search. A conditional formula explicitly captures two cardinal factors of a bug: 1) erroneous data dependencies and 2) missing or invalid condition checks. As a result, binary code search on conditional formulas produces significantly higher accuracy and provide meaningful evidence for human analysts to further examine the search results. We have implemented a prototype, XMATCH, and evaluated it using well-known software, including OpenSSL and BusyBox. Experimental results have shown that XMATCH outperforms the existing bug search techniques in terms of accuracy. Moreover, by evaluating 5 recent vulnerabilities, XMATCH provides clear evidence for human analysts to determine if a matched candidate is indeed vulnerable or has been patched.

References

[1]

The LLVM Compiler Infrastructure. http://llvm.org/.

[2]

The z3 theorem prover. https://z3.codeplex.com/, 2010.

[3]

Dd-wrt firmware image r21676. ftp://ftp.dd-wrt.com/others/eko/BrainSlayer-V24-preSP2/2013/05-27-2013-r21676/senao-eoc5610/linux.bin(lastvisit: 2016-1-20), 2013.

[4]

Retargetable decompiler. https://retdec.com, 2013.

[5]

AVGERINOS, T., CHA, S. K., REBERT, A., SCHWARTZ,E. J., WOO, M., AND BRUMLEY, D. Automatic exploit generation. Communications of the ACM 57, 2 (2014), 74--84.

Digital Library

[6]

BALAKRISHNAN, G., GRUIAN, R., REPS, T., AND TEITELBAUM, T. Codesurfer/x86: A platform for analyzing x86 executables. In Compiler Construction, Lecture Notes in Computer Science. 2005.

Digital Library

[7]

BALAKRISHNAN, G., AND REPS, T. Analyzing memory accesses in x86 executables. In Compiler Construction (2004).

[8]

BRUMLEY, D., JAGER, I., AVGERINOS, T., AND SCHWARTZ, E. J. Bap: a binary analysis platform. In Computer aided verification (2011), Springer, pp. 463--469.

Digital Library

[9]

BRUMLEY, D., NEWSOME, J., SONG, D., WANG, H., AND JHA, S. Towards automatic generation of vulnerability-based signatures. In IEEE Symposium on Security and Privacy (Oakland) (2006).

Digital Library

[10]

CABALLERO, J., JOHNSON, N. M., MCCAMANT, S., AND SONG, D. Binary code extraction and interface identification for security applications. In Proceedings of the 17th Annual Network and Distributed System Security Symposium (San Diego, CA, Feb. 2010).

[11]

CHA, S. K., WOO, M., AND BRUMLEY, D. Program-adaptive mutational fuzzing. In IEEE Symposium on Security and Privacy (Oakland) (2015).

Digital Library

[12]

CHEN, D. D., EGELE, M., WOO, M., AND BRUMLEY, D. Towards automated dynamic analysis for linux-based embedded firmware. In NDSS (2016).

[13]

DAVID, Y., AND YAHAV, E. Tracelet-based code search in executables. In Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation(PLDI'14) (2014), ACM.

Digital Library

[14]

DINABURG, A., AND RUEF, A. Mcsema: Static translation of x86 instructions to llvm. In ReCon (2014).

[15]

DOLAN-GAVITT, B., LEEK, T., HODOSH, J., AND LEE, W. Tappan zee (north) bridge: mining memory accesses for introspection. In CCS (2013).

Digital Library

[16]

DULLIEN, T., AND PORST, S. Reil: A platform-independent intermediate representation of disassembled code for static code analysis. CanSecWest (2009).

[17]

EGELE, M., WOO, M., CHAPMAN, P., AND BRUMLEY, D. Blanket execution: Dynamic similarity testing for program binaries and components. In USENIX Security (2014).

Digital Library

[18]

ELWAZEER, K., ANAND, K., KOTHA, A., SMITHSON, M., AND BARUA, R. Scalable variable and data type detection in a binary rewriter. In ACM SIGPLAN Notices (2013).

Digital Library

[19]

ESCHWEILER, S., YAKDAN, K., AND GERHARDS-PADILLA, E. discovre: Efficient cross-architecture identification of bugs in binary code. In NDSS (2016).

[20]

FENG, Q., ZHOU, R., XU, C., CHENG, Y., TESTA, B., AND YIN, H. Scalable graph-based bug search for firmware images. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (2016).

Digital Library

[21]

GAO, D., REITER, M. K., AND SONG, D. Binhunt: Automatically finding semantic differences in binary programs. In Information and Communications Security. Springer, 2008, pp. 238--255.

Digital Library

[22]

GEOFFRION, A. M. Lagrangean relaxation for integer programming. Springer, 1974.

[23]

IRELAND, A., AND STARK, J. On the automatic discovery of loop invariants. In NASA Conference Publication (1997).

[24]

JANG, J. Scaling Software Security Analysis to Millions of Malicious Programs and Billions of Lines of Code. PhD thesis, CARNEGIE MELLON UNIVERSITY, 2013.

[25]

JANG, J., AGRAWAL, A., AND BRUMLEY, D. Redebug: finding unpatched code clones in entire os distributions. In IEEE Symposium on Security and Privacy (Oakland) (2012).

Digital Library

[26]

JHALA, R., AND MAJUMDAR, R. Path slicing. In ACM SIGPLAN Notices (2005).

Digital Library

[27]

KAMIYA, T., KUSUMOTO, S., AND INOUE, K. Ccfinder: a multilinguistic token-based code clone detection system for large scale source code. IEEE Transactions on Software Engineering 28, 7 (2002), 654--670.

Digital Library

[28]

KARIM, M. E., WALENSTEIN, A., LAKHOTIA, A., AND PARIDA, L. Malware phylogeny generation using permutations of code. Journal in Computer Virology 1, 1-2 (2005), 13--23.

[29]

KHOO, W. M., MYCROFT, A., AND ANDERSON, R. Rendezvous: A search engine for binary code. In Proceedings of the 10th Working Conference on Mining Software Repositories (2013), IEEE Press.

Digital Library

[30]

KUHN, H. W. The hungarian method for the assignment problem. In 50 Years of Integer Programming 1958-2008. 2010, pp. 29--47.

[31]

LEE, J., AVGERINOS, T., AND BRUMLEY, D. Tie: Principled reverse engineering of types in binary programs. In Network and Distributed System Security Symposium (Feb. 2011).

[32]

LI, Z., LU, S., MYAGMAR, S., AND ZHOU, Y. Cp-miner: A tool for finding copy-paste and related bugs in operating system code. In OSDI (2004), vol. 4, pp. 289--302.

Digital Library

[33]

MING, J., PAN, M., AND GAO, D. ibinhunt: binary hunting with inter-procedural control flow. In Information Security and Cryptology. Springer, 2012, pp. 92--109.

Digital Library

[34]

NETHERCOTE, N., AND SEWARD, J. Valgrind: a framework for heavyweight dynamic binary instrumentation. In PLDI (2007), pp. 89--100.

Digital Library

[35]

PEWNY, J., GARMANY, B., GAWLIK, R., ROSSOW, C., AND HOLZ, T. Cross-architecture bug search in binary executables. In 2015 IEEE Symposium on Security and Privacy (Oakland'15) (2015), IEEE.

Digital Library

[36]

PEWNY, J., SCHUSTER, F., BERNHARD, L., HOLZ, T., AND ROSSOW, C. Leveraging semantic signatures for bug search in binary programs. In ACSAC (2014).

Digital Library

[37]

REBERT, A., CHA, S. K., AVGERINOS, T., FOOTE, J., WARREN, D., GRIECO, G., AND BRUMLEY, D. Optimizing seed selection for fuzzing. In USENIX Security (2014).

Digital Library

[38]

RIESEN, K., NEUHAUS, M., AND BUNKE, H. Bipartite graph matching for computing the edit distance of graphs. In Graph-Based Representations in Pattern Recognition. 2007, pp. 1--12.

Digital Library

[39]

SCHWARTZ, E. J., LEE, J., WOO, M., AND BRUMLEY, D. Native x86 decompilation using semantics-preserving structural analysis and iterative control-flow structuring. In USENIX Security (2013).

Digital Library

[40]

SHOSHITAISHVILI, Y., WANG, R., HAUSER, C., KRUEGEL, C., AND VIGNA, G. Firmalice-automatic detection of authentication bypass vulnerabilities in binary firmware. In NDSS (2015).

[41]

SONG, D., BRUMLEY, D., YIN, H., CABALLERO, J., JAGER, I., KANG, M. G., LIANG, Z., NEWSOME, J., POOSANKAM, P., AND SAXENA, P. BitBlaze: A newapproach to computer security via binary analysis. In Proceedings of the 4th International Conference on Information Systems Security (Hyderabad, India, Dec. 2008).

Digital Library

[42]

STEPHENS, N., GROSEN, J., SALLS, C., DUTCHER, A., AND WANG, R. Driller: Augmenting fuzzing through selective symbolic execution. In NDSS (2016).

[43]

TAHA, H. A. Integer programming: theory, applications, and computations. Academic Press, 2014.

Cited By

Ruan LXu QZhu SHuang XLin X(2024)A Survey of Binary Code Similarity Detection TechniquesElectronics10.3390/electronics1309171513:9(1715)Online publication date: 29-Apr-2024
https://doi.org/10.3390/electronics13091715
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
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
Show More Cited By

Index Terms

Extracting Conditional Formulas for Cross-Platform Bug Search
1. Security and privacy
  1. Software and application security
    1. Software security engineering
  2. Systems security
    1. Vulnerability management
      1. Vulnerability scanners

Recommendations

VulSeeker: a semantic learning based vulnerability seeker for cross-platform binary
ASE '18: Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering

Code reuse improves software development efficiency, however, vulnerabilities can be introduced inadvertently. Many existing works compute the code similarity based on CFGs to determine whether a binary function contains a known vulnerability. ...
Scalable Graph-based Bug Search for Firmware Images
CCS '16: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security

Because of rampant security breaches in IoT devices, searching vulnerabilities in massive IoT ecosystems is more crucial than ever. Recent studies have demonstrated that control-flow graph (CFG) based bug search techniques can be effective and accurate ...
Cross-Architecture Bug Search in Binary Executables
SP '15: Proceedings of the 2015 IEEE Symposium on Security and Privacy

With the general availability of closed-source software for various CPU architectures, there is a need to identify security-critical vulnerabilities at the binary level to perform a vulnerability assessment. Unfortunately, existing bug finding methods ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ASIA CCS '17: Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security

April 2017

952 pages

ISBN:9781450349444

DOI:10.1145/3052973

General Chairs:
Ramesh Karri
New York University, New York, USA
,
Ozgur Sinanoglu
New York University Abu Dhabi, UAE
,
Program Chairs:
Ahmad-Reza Sadeghi
Technische Universität Darmstadt, Germany
,
Xun Yi
RMIT University, Australia

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGSAC: ACM Special Interest Group on Security, Audit, and Control

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 April 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

DARPA Grant
National Science Foundation Grant
Air Force Research Lab Grant

Conference

ASIA CCS '17

Sponsor:

SIGSAC

ASIA CCS '17: ACM Asia Conference on Computer and Communications Security

April 2 - 6, 2017

Abu Dhabi, United Arab Emirates

Acceptance Rates

ASIA CCS '17 Paper Acceptance Rate 67 of 359 submissions, 19%;

Overall Acceptance Rate 418 of 2,322 submissions, 18%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

48
Total Citations
View Citations
490
Total Downloads

Downloads (Last 12 months)37
Downloads (Last 6 weeks)4

Reflects downloads up to 04 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Ruan LXu QZhu SHuang XLin X(2024)A Survey of Binary Code Similarity Detection TechniquesElectronics10.3390/electronics1309171513:9(1715)Online publication date: 29-Apr-2024
https://doi.org/10.3390/electronics13091715
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
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
Jiang XWang SGong YYu TLiu LYu X(2024)HAformer: Semantic fusion of hex machine code and assembly code for cross-architecture binary vulnerability detectionComputers & Security10.1016/j.cose.2024.104029145(104029)Online publication date: Oct-2024
https://doi.org/10.1016/j.cose.2024.104029
Yan YYu LWang TLi YPan Z(2024)Optir-SBERT: Cross-Architecture Binary Code Similarity Detection Based on Optimized LLVM IRDigital Forensics and Cyber Crime10.1007/978-3-031-56583-0_7(95-113)Online publication date: 3-Apr-2024
https://doi.org/10.1007/978-3-031-56583-0_7
Luo ZWang PXie WZhou XWang B(2023)IoTSim: Internet of Things-Oriented Binary Code Similarity Detection with Multiple Block RelationsSensors10.3390/s2318778923:18(7789)Online publication date: 11-Sep-2023
https://doi.org/10.3390/s23187789
Liu GZhou XPang JYue FLiu WWang J(2023)Codeformer: A GNN-Nested Transformer Model for Binary Code Similarity DetectionElectronics10.3390/electronics1207172212:7(1722)Online publication date: 4-Apr-2023
https://doi.org/10.3390/electronics12071722
Luo ZWang PXie WZhou XWang B(2023)BlockMatch: A Fine-Grained Binary Code Similarity Detection Approach Using Contrastive Learning for Basic Block MatchingApplied Sciences10.3390/app13231275113:23(12751)Online publication date: 28-Nov-2023
https://doi.org/10.3390/app132312751
Li SWang YDong CYang SLi HSun HLang ZChen ZWang WZhu HSun L(2023)LibAM: An Area Matching Framework for Detecting Third-Party Libraries in BinariesACM Transactions on Software Engineering and Methodology10.1145/362529433:2(1-35)Online publication date: 23-Dec-2023
https://dl.acm.org/doi/10.1145/3625294
Wang MYuan YYan HSui HZuo FLiu YLi YJin D(2023)Discovering Causes of Traffic Congestion via Deep Transfer ClusteringACM Transactions on Intelligent Systems and Technology10.1145/360481014:5(1-24)Online publication date: 11-Aug-2023
https://dl.acm.org/doi/10.1145/3604810
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents