Characterizing Cryptocurrency-Themed Malicious Browser Extensions

The popularity of cryptocurrencies has led to the growth of browser extensions, including malicious ones that cause financial losses and evade vetting processes. We conduct a systematic study to identify and characterize cryptocurrency-themed malicious extensions. By monitoring seven extension distribution venues for 18 months (December 2020 to June 2022) and collecting around 3,600 unique extensions, we identify 186 malicious extensions in five categories. We analyze their distribution channels, life cycles, developers, behaviors, and illegal gains, revealing their status quo , disguises, and programmatic features. Our work unveils the status quo of the cryptocurrency-themed malicious extensions and reveals the disguises and programmatic features on which detection techniques can be based. Our work serves as a warning to extension users, and as an appeal to extension store operators to enact dedicated countermeasures. To facilitate future research in this area, we release our dataset of the identified malicious extensions and open source our analyzer.

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Publication Details

Journal
Communications of the ACM
Published
2025-10-23
DOI
https://doi.org/10.1145/3715673
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Characterizing Cryptocurrency-Themed Malicious Browser Extensions

Kailong Wang, Guangdong Bai, Beng Chin Ooi, Zhou Yu et al.
Communications of the ACM
Advanced Malware Detection Techniques
article

Characterizing Cryptocurrency-Themed Malicious Browser Extensions

Kailong Wang, Guangdong Bai, Beng Chin Ooi, Zhou Yu, Yuxi Ling, Jin Song Dong, Yanjun Zhang, Haoyu Wang
article en

Abstract

The popularity of cryptocurrencies has led to the growth of browser extensions, including malicious ones that cause financial losses and evade vetting processes. We conduct a systematic study to identify and characterize cryptocurrency-themed malicious extensions. By monitoring seven extension distribution venues for 18 months (December 2020 to June 2022) and collecting around 3,600 unique extensions, we identify 186 malicious extensions in five categories. We analyze their distribution channels, life cycles, developers, behaviors, and illegal gains, revealing their status quo , disguises, and programmatic features. Our work unveils the status quo of the cryptocurrency-themed malicious extensions and reveals the disguises and programmatic features on which detection techniques can be based. Our work serves as a warning to extension users, and as an appeal to extension store operators to enact dedicated countermeasures. To facilitate future research in this area, we release our dataset of the identified malicious extensions and open source our analyzer.

Communications of the ACMVol. 68(11)
University of Technology Sydney (AU), The University of Queensland (AU), National University of Singapore (SG), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 61%
Advanced Malware Detection Techniques
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