2025 Year-End Review: In-Depth Analysis of Top Browser Fingerprint Detection

Browser fingerprint detection tools are used to identify the device characteristics exposed by browsers when accessing web pages and analyze the uniqueness and stability of these characteristics.

These tools utilize system configuration, hardware parameters, network features, and rendering results to help users understand whether their browsing environment is consistent and whether there are any unusual discrepancies.

Below, we introduce several practical browser fingerprint detection platforms in 2025 and their feature evaluations.

1. ToDetect

Overview
ToDetect is a browser fingerprint detection platform with a Chinese interface, supporting real-time detection and visual report display. It analyzes multiple parameters to let users understand the match between the current browser environment and the actual device configuration.

Main Detection Items

• System parameters: operating system, browser version, language, time zone, etc.

• Graphics and audio fingerprints: Canvas, WebGL, AudioContext

• Fonts, plugins, network characteristics

• Resolution, proxy identifiers, fingerprint stability analysis

Features

• Fast detection, simple page structure, clear result presentation

• Generates detailed parameter lists in reports and highlights key features with charts

• Helps evaluate environment completeness and consistency

2. BrowserLeaks

Overview
BrowserLeaks is an early comprehensive detection website, providing multi-dimensional analysis from system to script layers.

Detection Modules

• Browser information, plugins, network interfaces

• Graphics rendering, time zone, and language

Features

• Large number of output parameters, comprehensive information

• Results displayed in sections, convenient for technical comparison

• No automatic scoring provided; users must manually evaluate fingerprint differences

• More suitable for technically skilled users, ideal for in-depth analysis or script verification

3. AmIUnique

Overview
AmIUnique, developed by the University of Toulouse in France, focuses on analyzing the uniqueness of browser fingerprints.

Detection Results

• Parameter list

• Comparison with sample database

• Uniqueness ratio of the browser among global samples

Features

• Helps users understand how rare their browser fingerprint is

• Clear result structure and simple operation

• Suitable for fingerprint research and educational purposes

4. Cover Your Tracks (formerly Panopticlick)

Overview
Launched by the Electronic Frontier Foundation (EFF), mainly for privacy protection detection.

Detection Items

• Whether anti-fingerprinting features are enabled

• Fingerprint uniqueness

• Ad tracking protection test

Features

• Results are presented as “trackable or not”

• Suitable for privacy-conscious users to quickly evaluate browser performance

5. FingerprintJS

Overview
FingerprintJS is the official demo platform for the open-source fingerprint recognition library, primarily demonstrating the recognition algorithm's generation effect.

Detection Items

• Browser and system parameters

• Canvas and Audio fingerprints

• Network configuration and language settings

Features

• Geared towards developer testing

• Results are structured hash data; does not provide privacy analysis

6. CreepJS

Overview
CreepJS is a community-maintained deep fingerprint detection project, offering very comprehensive detection.

Main Detection Scope

• Canvas, WebGL, AudioContext fingerprints

• GPU details and refresh rate

• Mathematical precision errors and anti-aliasing performance

• Font rendering differences

Features

• Large output of information, suitable for low-level difference analysis

• Detection process is relatively long and requires higher device performance

7. Browser Fingerprint Tool Feature Comparison

Conclusion

Different browser fingerprint detection tools, based on their own recognition logic and data collection methods, display varying scopes and structures of information:

• Some tools focus on detecting low-level parameter completeness

• Some focus on fingerprint uniqueness statistics

• Some specialize in visual reports or privacy protection performance

When analyzing detection results, users should consider the specific dimensions displayed by the tools, such as system configuration, rendering data, and network identifiers. This information reflects the match between the browser and system environment and provides reference for subsequent adjustments or verification.