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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊網路與多媒體研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84947
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dc.contributor.advisor吳家麟(Ja-Ling Wu)
dc.contributor.authorYuan-Chun Chuen
dc.contributor.author朱元均zh_TW
dc.date.accessioned2023-03-19T22:34:17Z-
dc.date.copyright2022-08-24
dc.date.issued2022
dc.date.submitted2022-08-23
dc.identifier.citation[1] jsfuzz. https://gitlab.com/gitlab-org/security-products/analyzers/fuzzers/jsfuzz. Accessed: 2022-06-01. [2] Arteau. prototype-pollution-nsec18. https://github.com/HoLyVieR/prototype-pollution-nsec18. Accessed: 2022-06-01. [3] BlackFan. client-side-prototype-pollution. https://github.com/BlackFan/client-side-prototype-pollution. Accessed: 2022-06-01. [4] M. Boehme, C. Cadar, and A. Roychoudhury. Fuzzing: Challenges and reflections. IEEE Software, 38(03):79–86, may 2021. [5] E. Ecma. 262: Ecmascript language specification. ECMA (European Association for Standardizing Information and Communication Systems), pub-ECMA: adr,, 2022. [6] H. Y. Kim, J. H. Kim, H. K. Oh, B. J. Lee, S. W. Mun, J. H. Shin, and K. Kim. Dapp: automatic detection and analysis of prototype pollution vulnerability in Node.js modules. International Journal of Information Security, 21(1):1–23, 2022. [7] S. Li, M. Kang, J. Hou, and Y. Cao. Detecting Node. js prototype pollution vulnerabilities via object lookup analysis. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pages 268–279, 2021. [8] M. Zalewski. american fuzzy lop. https://lcamtuf.coredump.cx/afl/. Accessed: 2022-06-01.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84947-
dc.description.abstract本論文提出了一套框架能夠自動地在 Node.js 的函式庫中偵測原型鏈污染漏洞,並自動產生相對應的漏洞利用以驗證漏洞的存在。此框架包含了可以分開獨立實作與優化的六個步驟,依序從尋找目標、分割程式碼、植入程式碼、模糊測試、產生漏洞利用到驗證漏洞利用,結合靜態分析與動態分析的優勢,並分析利 用原型鏈污染漏洞的特性,盡可能地找出所有原型鏈污染漏洞。最後,依照每一步驟的定義,本論文實作了一套概念性驗證的工具,來驗證並分析此架構的可行性與效能。zh_TW
dc.description.abstractThis thesis proposes a framework that automatically detects Prototype Pollution Vul- nerabilities in the Node.js library and automatically generates the corresponding exploits to verify the existence of vulnerabilities. The proposed framework comprises six phases that can be implemented and optimized independently. The six phases include: finding targets, segmenting code, injecting code, fuzzing, generating exploits, and verifying ex- ploits, which combines the advantages of static and dynamic analysis and makes analyzing the concept of Prototype Pollution to find all vulnerabilities as much as possible. By ade- quately defining each phase, we implemented proof-of-concept tools to verify and analyze the feasibility and effectiveness of the framework.en
dc.description.provenanceMade available in DSpace on 2023-03-19T22:34:17Z (GMT). No. of bitstreams: 1
U0001-0707202216093800.pdf: 3718682 bytes, checksum: f5cc97a6d47430a1fb7d99ef26ee9461 (MD5)
Previous issue date: 2022
en
dc.description.tableofcontentsVerification Letter from the Oral Examination Committee i 摘要 ii Abstract iii Contents iv List of Figures vi List of Tables vii Chapter 1 Introduction 1 Chapter 2 Prototype Pollution 2 2.1 Prototype Chain ............................ 2 2.2 Prototype Pollution........................... 3 2.3 Vulnerable Pattern ........................... 5 2.4 Possible Impact............................. 6 Chapter 3 Related Work 9 3.1 PPFuzzer................................ 9 3.2 DAPP.................................. 10 3.3 ObjLupAnsys.............................. 10 Chapter 4 Proposed Method 12 4.1 Overview................................ 12 4.2 Finding Target ............................. 13 4.3 Splitting Code Segment ........................ 16 4.4 InjectingCode ............................. 18 4.5 Greybox Fuzzing............................ 21 4.6 Generating Exploit ........................... 24 4.7 VerifyingExploit............................ 25 Chapter 5 Result 27 5.1 Comparison............................... 27 5.2 ObjectMutator ............................. 28 Chapter 6 Conclusion 30 6.1 Conclusion ............................... 30 6.2 FutureWork .............................. 30 References 32
dc.language.isoen
dc.subjectNode.jszh_TW
dc.subject原型鏈污染zh_TW
dc.subject模糊測試zh_TW
dc.subjectFuzzingen
dc.subjectNode.jsen
dc.subjectPrototypePollutionen
dc.title在 Node.js 函式庫中動態偵測原型鏈污染漏洞zh_TW
dc.titleDynamic Detection of Prototype Pollution Vulnerability in Node.js Libraryen
dc.typeThesis
dc.date.schoolyear110-2
dc.description.degree碩士
dc.contributor.oralexamcommittee許超雲(Chau-Yun Hsu),陳駿承(Jun-Cheng Chen)
dc.subject.keywordNode.js,原型鏈污染,模糊測試,zh_TW
dc.subject.keywordNode.js,PrototypePollution,Fuzzing,en
dc.relation.page33
dc.identifier.doi10.6342/NTU202201333
dc.rights.note同意授權(限校園內公開)
dc.date.accepted2022-08-23
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊網路與多媒體研究所zh_TW
dc.date.embargo-lift2022-08-24-
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