Circuit: A JavaScript Memory Heap-Based Approach for Precisely Detecting Cryptojacking Websites

Hyunji Hong, Seunghoon Woo, Sunghan Park, Jeongwook Lee, Heejo Lee

Research output: Contribution to journalArticlepeer-review


Cryptojacking is often used by attackers as a means of gaining profits by exploiting users' resources without their consent, despite the anticipated positive effect of browser-based cryptomining. Previous approaches have attempted to detect cryptojacking websites, but they have the following limitations: (1) they failed to detect several cryptojacking websites either because of their evasion techniques or because they cannot detect JavaScript-based cryptojacking and (2) they yielded several false alarms by focusing only on limited characteristics of cryptojacking, such as counting computer resources. In this paper, we propose CIRCUIT, a precise approach for detecting cryptojacking websites. We primarily focuse on the JavaScript memory heap, which is resilient to script code obfuscation and provides information about the objects declared in the script code and their reference relations. We then extract a reference flow that can represent the script code behavior of the website from the JavaScript memory heap. Hence, CIRCUIT determines that a website is running cryptojacking if it contains a reference flow for cryptojacking. In our experiments, we found 1,813 real-world cryptojacking websites among 300K popular websites. Moreover, we provided new insights into cryptojacking by modeling the identified evasion techniques and considering the fact that characteristics of cryptojacking websites now appear on normal websites as well.

Original languageEnglish
Pages (from-to)95356-95368
Number of pages13
JournalIEEE Access
Publication statusPublished - 2022


  • Browser security
  • cryptojacking
  • web security

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)
  • Electrical and Electronic Engineering


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