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Automatically Generating Searchable Fingerprints For WordPress Plugins Using Static Program Analysis

Abstract Details

2022, Master of Science (MS), Wright State University, Computer Science.
This thesis introduces a novel method to automatically generate fingerprints for WordPress plugins. Our method performs static program analysis using Abstract Syntax Trees (ASTs) of WordPress plugins. The generated fingerprints can be used for identifying these plugins using search engines, which have support critical applications such as proactively identifying web servers with vulnerable WordPress plugins. We have used our method to generate fingerprints for over 10,000 WordPress plugins and analyze the resulted fingerprints. Our fingerprints have also revealed 453 websites that are potentially vulnerable. We have also compared fingerprints for vulnerable plugins and those for vulnerability-free plugins.
Junjie Zhang, Ph.D. (Advisor)
Krishnaprasad Thirunarayan, Ph.D. (Committee Member)
Bin Wang, Ph.D. (Committee Member)
44 p.

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Citations

  • Li, C. (2022). Automatically Generating Searchable Fingerprints For WordPress Plugins Using Static Program Analysis [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1654033837621927

    APA Style (7th edition)

  • Li, Chuang. Automatically Generating Searchable Fingerprints For WordPress Plugins Using Static Program Analysis. 2022. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1654033837621927.

    MLA Style (8th edition)

  • Li, Chuang. "Automatically Generating Searchable Fingerprints For WordPress Plugins Using Static Program Analysis." Master's thesis, Wright State University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=wright1654033837621927

    Chicago Manual of Style (17th edition)