Browser Fingerprint Test
Discover how unique your browser is. This tool collects the same signals that trackers use — canvas rendering, WebGL, screen properties, hardware specs, and more — to generate your browser fingerprint and rate your uniqueness.
What Is Browser Fingerprinting?
Browser fingerprinting is a tracking technique that identifies users by collecting a unique combination of browser and device characteristics. Unlike cookies, which are stored locally and can be deleted, fingerprints are generated from information your browser naturally exposes — such as screen resolution, installed fonts, GPU model, timezone, and language settings. When enough of these data points are combined, they create a profile so specific that it can uniquely identify your browser among millions of others. Studies have shown that over 90% of browsers have a unique fingerprint.
How Canvas Fingerprinting Works
Canvas fingerprinting is one of the most powerful fingerprinting techniques. It works by asking your browser to draw text and shapes on an invisible HTML canvas element, then reading back the pixel data. Due to differences in GPU hardware, graphics drivers, operating systems, and font rendering engines, the exact same drawing instructions produce slightly different results on different machines. These subtle differences create a unique signature. Even two identical computer models may produce different canvas fingerprints due to driver version differences.
WebGL Fingerprinting
WebGL provides another powerful fingerprinting vector. Beyond the GPU renderer and vendor strings, WebGL exposes detailed information about supported extensions, maximum texture sizes, shader precision formats, and rendering capabilities. The combination of these parameters is highly distinctive. WebGL fingerprinting is particularly effective because GPU hardware varies enormously across devices, and the specific driver implementation details create additional uniqueness even among devices with the same GPU model.
The Fingerprint Hash
This tool combines all collected signals into a single hash string that represents your browser's fingerprint. The hash is generated by concatenating all signal values and running them through a simple hash function. If any single signal changes (like updating your browser, changing screen resolution, or modifying language settings), the hash will change. The hash itself is not personally identifying — it is simply a unique identifier derived from your browser's publicly exposed characteristics. Think of it as a digital license plate for your browser.
Protecting Against Fingerprinting
Reducing your fingerprint uniqueness is challenging because many fingerprinting signals are necessary for normal web browsing. However, several strategies can help. The Tor Browser is specifically designed to make all users look identical by standardizing window size, fonts, and other signals. Firefox offers Enhanced Tracking Protection that blocks known fingerprinting scripts. Browser extensions like CanvasBlocker can add noise to canvas and WebGL data. Using common hardware and default browser settings also helps you blend in with the crowd. The goal is not to block all signals but to make your combination of signals as common as possible.
Fingerprinting vs Cookies
Traditional cookie-based tracking requires storing data on your device, which you can clear, block, or manage through browser settings. Privacy regulations like GDPR and CCPA have given users more control over cookies. Fingerprinting, however, is passive — it reads information your browser already provides without storing anything. This makes it harder to detect, block, and regulate. Many companies are shifting to fingerprinting as cookie restrictions tighten. Understanding your fingerprint helps you make informed decisions about privacy tools and browser configurations.