Understanding evasion techniques that abuse differences among javascript implementations

Yuta Takata*, Mitsuaki Akiyama, Takeshi Yagi, Takeo Hariu, Shigeki Goto

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)


    There is a common approach to detecting drive-by downloads using a classifier based on the static and dynamic features of malicious websites collected using a honeyclient. However, attackers detect the honeyclient and evade analysis using sophisticated JavaScript code. The evasive code indirectly identifies clients by abusing the differences among JavaScript implementations. Attackers deliver malware only to targeted clients on the basis of the evasion results while avoiding honeyclient analysis. Therefore, we are faced with a problem in that honeyclients cannot extract features from malicious websites and the subsequent classifier does not work. Nevertheless, we can observe the evasion nature, i.e., the results in accessing malicious websites by using targeted clients are different from those by using honeyclients. In this paper, we propose a method of extracting evasive code by leveraging the above differences to investigate current evasion techniques and to use them for analyzing malicious websites. Our method analyzes HTTP transactions of the same website obtained using two types of clients, a real browser as a targeted client and a browser emulator as a honeyclient. As a result of evaluating our method with 8,467 JavaScript samples executed in 20,272 malicious websites, we discovered unknown evasion techniques that abuse the differences among JavaScript implementations. These findings will contribute to improving the analysis capabilities of conventional honeyclients.

    Original languageEnglish
    Title of host publicationWeb Information Systems Engineering – WISE 2017 - 18th International Conference, Proceedings
    PublisherSpringer Verlag
    Number of pages17
    Volume10570 LNCS
    ISBN (Print)9783319687858
    Publication statusPublished - 2017
    Event18th International Conference on Web Information Systems Engineering, WISE 2017 - Puschino, Russian Federation
    Duration: 2017 Oct 72017 Oct 11

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10570 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Other18th International Conference on Web Information Systems Engineering, WISE 2017
    Country/TerritoryRussian Federation


    • Differential analysis
    • Evasive code
    • JavaScript
    • Web security

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)


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