Discovering Browser Extensions via Web Accessible Resources

Sjösten, Alexander; Acker, Steven Van; Sabelfeld, Andrei

doi:10.1145/3029806.3029820

Cited by 40 publications

(36 citation statements)

References 13 publications

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“…However, because of the way addons are integrated in browsers, it is possible to detect some of them. A study conducted by Sjösten et al looked at the use of web accessible resources to detect extensions [103]. By accessing very specific URLs, they can know if an extension is installed or not.…”

Section: Canvas Javascriptmentioning

confidence: 99%

Browser Fingerprinting

Bielova²,

et al. 2020

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With this paper, we survey the research performed in the domain of browser fingerprinting, while providing an accessible entry point to newcomers in the field. We explain how this technique works and where it stems from. We analyze the related work in detail to understand the composition of modern fingerprints and see how this technique is currently used online. We systematize existing defense solutions into different categories and detail the current challenges yet to overcome.

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Section: Canvas Javascriptmentioning

confidence: 99%

Browser Fingerprinting

Bielova²,

et al. 2020

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“…If a specific extension's elements or behavior are unique among all extensions, then a page can uniquely identify (i.e., fingerprint) it. Identifying exposed resources in Chrome is a straightforward process that has been demonstrated before [24], [47]. On the other hand, uniquely identifying extensions based on their behavior is a challenging task that presents several obstacles in practice.…”

Section: Background and Threat Modelmentioning

confidence: 99%

“…As mentioned previously, prior studies have demonstrated the feasibility of browser extension enumeration and fingerprintability. These studies focused their efforts on identifying extensions that expose specific resources (i.e., WAR-based enumeration) either directly [24], [47] or with clever implicit approaches [44], [46]. In the following subsections we provide technical details and outline the fingerprint generation and extension detection process for our four techniques.…”

Section: System Design and Implementationmentioning

confidence: 99%

“…Due to the potential risk, browsers do not provide any mechanism that would allow a visited webpage to directly obtain the list of installed browser extensions. In practice, however, webpages can indirectly infer which extensions are installed [24], [44], [46], [47]. Once the list of installed extensions is obtained, it can be used as part of a user's device fingerprint and coupled with other browser [18], [33], [40] or system level [13] information, which can lead to the tracking of users across the web [8], [19].…”

Section: Introductionmentioning

confidence: 99%

“…To that end we build Carnus, a modular system that analyzes Chrome extensions statically and dynamically for creating fingerprinting signatures and inferring sensitive data. Our system employs four different techniques for detecting extensions; first, it leverages the straightforward technique of identifying extensions that expose unique web-accessible resources (WARs), which has been demonstrated in prior studies [24], [47] at a smaller scale. Next, we focus on the identification of extensions through the detection of unique behaviorbased modifications to a page's DOM.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Carnus: Exploring the Privacy Threats of Browser Extension Fingerprinting

Karami¹,

Ilia²,

Σολωμός³

et al. 2020

Proceedings 2020 Network and Distributed System Security Symposium

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With users becoming increasingly privacy-aware and browser vendors incorporating anti-tracking mechanisms, browser fingerprinting has garnered significant attention. Accordingly, prior work has proposed techniques for identifying browser extensions and using them as part of a device's fingerprint. While previous studies have demonstrated how extensions can be detected through their web accessible resources, there exists a significant gap regarding techniques that indirectly detect extensions through behavioral artifacts. In fact, no prior study has demonstrated that this can be done in an automated fashion. In this paper, we bridge this gap by presenting the first fully automated creation and detection of behavior-based extension fingerprints. We also introduce two novel fingerprinting techniques that monitor extensions' communication patterns, namely outgoing HTTP requests and intra-browser message exchanges. These techniques comprise the core of Carnus, a modular system for the static and dynamic analysis of extensions, which we use to create the largest set of extension fingerprints to date. We leverage our dataset of 29,428 detectable extensions to conduct a comprehensive investigation of extension fingerprinting in realistic settings and demonstrate the practicality of our attack. Our in-depth analysis confirms the robustness of our techniques, as 83.6%-87.92% of our behavior-based fingerprints remain effective against a state-of-the-art countermeasure.

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Wild Extensions: Discovering and Analyzing Unlisted Chrome Extensions

Beggs

Kapravelos

2019

Detection of Intrusions and Malware, and Vulnerability Assessment

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Discovering Browser Extensions via Web Accessible Resources

Cited by 40 publications

References 13 publications

Browser Fingerprinting

Browser Fingerprinting

Carnus: Exploring the Privacy Threats of Browser Extension Fingerprinting

Wild Extensions: Discovering and Analyzing Unlisted Chrome Extensions

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