research-article

A hybrid analysis to detect Java serialisation vulnerabilities

Authors:

Jens DietrichAuthors Info & Claims

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

Pages 1209 - 1213

https://doi.org/10.1145/3324884.3418931

Published: 27 January 2021 Publication History

Abstract

Serialisation related security vulnerabilities have recently been reported for numerous Java applications. Since serialisation presents both soundness and precision challenges for static analysis, it can be difficult for analyses to precisely pinpoint serialisation vulnerabilities in a Java library. In this paper, we propose a hybrid approach that extends a static analysis with fuzzing to detect serialisation vulnerabilities. The novelty of our approach is in its use of a heap abstraction to direct fuzzing for vulnerabilities in Java libraries. This guides fuzzing to produce results quickly and effectively, and it validates static analysis reports automatically. Our approach shows potential as it can detect known serialisation vulnerabilities in the Apache Commons Collections library.

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Cited By

Kreyssig BBartel A(2024)Analyzing Prerequistes of known Deserializtion Vulnerabilities on Java ApplicationsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661176(28-37)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661176
Liu XWang HXu MZhang Y(2024)SerdeSniffer: Enhancing Java Deserialization Vulnerability Detection with Function SummariesComputer Security – ESORICS 202410.1007/978-3-031-70896-1_9(174-193)Online publication date: 6-Sep-2024
https://doi.org/10.1007/978-3-031-70896-1_9
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https://doi.org/10.1007/978-3-031-53555-0_22
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cover image ACM Conferences

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

December 2020

1449 pages

ISBN:9781450367684

DOI:10.1145/3324884

General Chair:
John Grundy,
Program Chairs:
Claire Le Goues,
David Lo

Copyright © 2020 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]

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Published: 27 January 2021

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ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering

December 21 - 25, 2020

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Cited By

Kreyssig BBartel A(2024)Analyzing Prerequistes of known Deserializtion Vulnerabilities on Java ApplicationsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661176(28-37)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661176
Liu XWang HXu MZhang Y(2024)SerdeSniffer: Enhancing Java Deserialization Vulnerability Detection with Function SummariesComputer Security – ESORICS 202410.1007/978-3-031-70896-1_9(174-193)Online publication date: 6-Sep-2024
https://doi.org/10.1007/978-3-031-70896-1_9
Luo YCui B(2024)Rev Gadget: A Java Deserialization Gadget Chains Discover Tool Based on Reverse Semantics and Taint AnalysisAdvances in Internet, Data & Web Technologies10.1007/978-3-031-53555-0_22(229-240)Online publication date: 14-Feb-2024
https://doi.org/10.1007/978-3-031-53555-0_22
Srivastava PToffalini FVorobyov KGauthier FBianchi APayer MChandra SBlincoe KTonella P(2023)Crystallizer: A Hybrid Path Analysis Framework to Aid in Uncovering Deserialization VulnerabilitiesProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616313(1586-1597)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3616313
Cao SHe BSun XOuyang YZhang CWu XSu TBo LLi BMa CLi JWei T(2023)ODDFuzz: Discovering Java Deserialization Vulnerabilities via Structure-Aware Directed Greybox Fuzzing2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179377(2726-2743)Online publication date: May-2023
https://doi.org/10.1109/SP46215.2023.10179377
Li WLu HSun YSu SQiu JTian Z(2023)Improving Precision of Detecting Deserialization Vulnerabilities with Bytecode Analysis2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS)10.1109/IWQoS57198.2023.10188756(1-2)Online publication date: 19-Jun-2023
https://doi.org/10.1109/IWQoS57198.2023.10188756
Cao SSun XWu XBo LLi BWu RLiu WHe BOuyang YLi J(2023)Improving Java Deserialization Gadget Chain Mining via Overriding-Guided Object Generation2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)10.1109/ICSE48619.2023.00044(397-409)Online publication date: May-2023
https://doi.org/10.1109/ICSE48619.2023.00044
Chen XWang BJin ZFeng YLi XFeng XLiu Q(2023)Tabby: Automated Gadget Chain Detection for Java Deserialization Vulnerabilities2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN58367.2023.00028(179-192)Online publication date: Jun-2023
https://doi.org/10.1109/DSN58367.2023.00028
Antal GHegedűs PHerczeg ZLóki GFerenc R(2023)Is JavaScript Call Graph Extraction Solved Yet? A Comparative Study of Static and Dynamic ToolsIEEE Access10.1109/ACCESS.2023.325598411(25266-25284)Online publication date: 2023
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Sayar IBartel ABodden ELe Traon Y(2022)An In-depth Study of Java Deserialization Remote-Code Execution Exploits and VulnerabilitiesACM Transactions on Software Engineering and Methodology10.1145/355473232:1(1-45)Online publication date: 5-Aug-2022
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