Breaking the Shield: Analyzing and Attacking Canvas Fingerprinting Defenses in the Wild

Canvas fingerprinting has become one of the most effective techniques for tracking users online, allowing websites to identify and track visitors without their consent. In this paper, we investigate four primary defense techniques designed to counter canvas fingerprinting, systematically analyzing their adoption across 18 browser extensions in Chrome and Firefox, as well as built-in protections from five major browsers: Chrome, Firefox, Brave, Tor, and Safari. Our analysis reveals significant disparities in the implementation and effectiveness of these defenses, with randomization-based techniques being the most widely adopted, particularly across nine extensions and in the privacy-focused browser, Brave. Despite their sophistication, we demonstrate successful attacks on all these randomization mechanisms, revealing that their supposed non-deterministic behavior can, in fact, be predicted and exploited. In summary, we demonstrate that, unfortunately, no fully deployable defense against canvas fingerprinting attacks exists currently. We conclude by proposing recommendations to strengthen existing defenses and enhance their resistance to future attacks.

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Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1145/3696410.3714713
Citations
1
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
1.28

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article

Breaking the Shield: Analyzing and Attacking Canvas Fingerprinting Defenses in the Wild

Phani Vadrevu, Hoang Dai Nguyen
1 citations
Digital Media Forensic Detection
1.28
article

Breaking the Shield: Analyzing and Attacking Canvas Fingerprinting Defenses in the Wild

Phani Vadrevu, Hoang Dai Nguyen
article en
1 citations

Abstract

Canvas fingerprinting has become one of the most effective techniques for tracking users online, allowing websites to identify and track visitors without their consent. In this paper, we investigate four primary defense techniques designed to counter canvas fingerprinting, systematically analyzing their adoption across 18 browser extensions in Chrome and Firefox, as well as built-in protections from five major browsers: Chrome, Firefox, Brave, Tor, and Safari. Our analysis reveals significant disparities in the implementation and effectiveness of these defenses, with randomization-based techniques being the most widely adopted, particularly across nine extensions and in the privacy-focused browser, Brave. Despite their sophistication, we demonstrate successful attacks on all these randomization mechanisms, revealing that their supposed non-deterministic behavior can, in fact, be predicted and exploited. In summary, we demonstrate that, unfortunately, no fully deployable defense against canvas fingerprinting attacks exists currently. We conclude by proposing recommendations to strengthen existing defenses and enhance their resistance to future attacks.

Louisiana State University (US)
National Science Foundation
Openalex Percentile: Top 21%
Digital Media Forensic Detection
1.28
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Breaking the Shield: Analyzing and Attacking Canvas Fingerprinting Defenses in the Wild — Phani Vadrevu, Hoang Dai Nguyen · (2025) | TGRS Research Map | TGRS