Canvas Fingerprint Defender

Defending against Canvas fingerprinting by reporting a fake value.

Users100K

Rating3.7

Reviews74

Manifest versionV3

7-day growth0

7-day growth rate0%

Preview

Canvas Fingerprint Defender Media preview

2 assets

Trend

30-day user trend

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User Growth Over Time

Rating trend

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30-day rating change

Start

3.73

Latest

3.73

30-day rating change

0.00

2026年5月28日2026年6月3日

Growth overview

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1-day growthFlat

00%

7-day growthFlat

00%

30-day growthGrowing

+60K+150%

Technical snapshot

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Version0.2.2

ManifestV3

Size41.02KiB

Languages1English

Published--

Store updated--

Last crawled--

Overview

Product summary

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Canvas Fingerprint Defender is a lite extension that lets you easily hide your real canvas fingerprint by reporting a random fake value.

According to many tech blogs, completely blocking canvas fingerprints is not a good idea, therefore reporting a "fake" fingerprint could be the best solution to better protect your privacy. This addon simply adds a small noise to the actual fingerprint and "renews" it every time you visit a website or reload a page. It is important to note that, it does not have any settings or options to adjust. Simply add it to your browser and start surfacing the internet. If you want to test this addon, please visit a website that shows your fingerprint (i.e. browserleaks). Every time you reload the page, you will see a new fake fingerprint.

To report bugs, please visit the addon's homepage (https://mybrowseraddon.com/canvas-defender.html) and fill out the bug report form.

Reviews

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The Chrome Web Store shows 74 reviews, but only 0 review bodies have synced into ExtScope so far. Showing the synced reviews available right now.

5★

4★

3★

2★

1★

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Review related products from the Chrome Web Store detail page.

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AI product read

Privacy protection extension that defends against canvas fingerprinting by injecting random RGBA noise into canvas API responses

Websites use canvas fingerprinting to uniquely identify and track users across sessions. This extension counters that by adding small random noise to canvas pixel data before it is read via getImageData, toDataURL, or toBlob, producing a different fake fingerprint on each page load.

Install extension → it automatically runs on all pages → content scripts intercept canvas API calls and add random noise → websites receive a fake, ever-changing canvas fingerprint. Users can optionally toggle desktop notifications and test their fingerprint via the popup or context menu.

Target users: Privacy-conscious users who want to defend against canvas fingerprinting without completely blocking canvas APIs / Users seeking a lightweight, no-configuration privacy tool

No external network calls to analyze beyond the developer homepage link and a test page URL — no server-side logic to inspect
The explore.json promotes other extensions by the same developer but content was not deeply inspected for paid feature implications

Monetization

No paid features detected

No billing, subscription, license, or upgrade mechanisms found. All keyword hits for 'pro' are false positives matching JavaScript prototype chains (CanvasRenderingContext2D.prototype, HTMLCanvasElement.prototype) and the variable name 'properties'. The popup has a voluntary 'Make a donation' button that opens the developer homepage, but this is not a feature gate. All functionality is available immediately upon install.

Confidence: 95
Payment platform: --
Source: AI / High
Login required: No
Reason: No login, authentication, or account system found in any source file. The extension works entirely locally — content scripts inject canvas noise automatically on all pages without any authentication step. The only keyword hit for 'session' (lib/chrome.js:111) is a standard app session loading call (app.session.load), not a login mechanism.

Permission risk

Medium-risk permissions

This estimate uses declared permissions and host permissions to assess access scope and sensitivity.

扩展能力较强：storage

Publisher

Yubi

Independent publisher

Email: [email protected]
Phone: --
Address: --

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