What is Canvas Fingerprinting and How to Bypass It

Canvas fingerprinting has become one of the most popular bot detection methods used by over 5% of major websites. In this comprehensive guide, we’ll dive into what exactly canvas fingerprinting is, how it works to identify scrapers and bots, limitations of basic bypassing approaches, and two advanced methods to mimic a real browser fingerprint.

What is Canvas Fingerprinting & Why it's Used

When you connect to a website, details like your operating system, screen resolution, browser, etc automatically get shared and make up a browser fingerprint unique to your device.

Websites leverage this concept using canvas fingerprinting to have scripts draw hidden images and analyze subtle rendering differences to extract dozens of data points beyond basic fingerprints.

Sites use canvas fingerprinting for:

  • Security – Identifying bots from real visitors to prevent attacks
  • Personalization – Customizing content by linking behaviors to user fingerprint
  • Analytics – Tracking users across sites using fingerprint as persistent identifier

So how does canvas fingerprinting manage to extract detailed fingerprints from simple images?

How Does Canvas Fingerprinting Work?

Canvas fingerprint relies on the HTML5 <canvas> element. When you visit a site using it, the script instructs your browser to:

  1. Draw a hidden image with random shapes, text, colors
  2. Extract the rendered image data
  3. Run it through a hashing algorithm to get a fingerprint hash value

Even tiny differences in how browsers render the image lead to completely different fingerprint hashes.

Why Hashing is Key

Hashing algorithms are key because they produce the same fixed-length results for identical inputs. For example, passing the text "canvas fingerprinting" into SHA-256 will always output:


But adding just a single space before "canvas" results in a totally different hash:


This allows sites to reliably link all current and future visits back to your browser’s fingerprint hash value.

Now that you understand how canvas fingerprinting works, let's look at why basic bypassing approaches have limitations.

Limitations of Basic Canvas Fingerprint Bypassing

The most straightforward approach to bypass canvas fingerprinting is disabling JavaScript or the Canvas API altogether. However, this can break site functionality that relies on them to render content.

Our goal shouldn’t be to blindly disable canvas but rather mimic a real browser's fingerprint. This allows bypassing fingerprinting while maintaining full access to site content.

Bypassing Canvas Fingerprinting with Puppeteer

To demonstrate generating fake canvas fingerprints, we'll use Puppeteer – a popular headless Chrome browser automation library.

The key concept is to hook the toDataURL method and return our own fabricated image data instead of the actual render.

First import Puppeteer and launch a browser instance:

const puppeteer = require('puppeteer');

const browser = await puppeteer.launch();
const page = await browser.newPage();

Next we'll define a page evaluation callback to override toDataURL:

await page.evaluateOnNewDocument(() => {

    const originalToDataURL = HTMLCanvasElement.prototype.toDataURL;

    HTMLCanvasElement.prototype.toDataURL = function(type) {

        if (type === 'image/png') {
            return 'data:image/png;base64,iVBORw0...'; // FAKE IMAGE
        return originalToDataURL.apply(this, arguments);


Now when the site's fingerprinting script calls toDataURL(), instead of rendering the image we return a fake static PNG data string.

This generates a consistent fingerprint on every visit that may work initially. However there are some downsides:

  • Unique fingerprints get blocklisted by fingerprinting defenses
  • Reusing the same fingerprint reduces anonymity

Rather than returning a static fake fingerprint, randomizing it makes scraping more resilient long-term.

Bypassing with Canvas Fingerprint Extensions

Browser extensions like Canvas Fingerprint Defender specialize in intercepting canvas rendering to randomly generate fingerprint hashes each visit.

The extension works by redefining toDataURL(), toBlob(), and getImageData() – the key functions websites rely on to extract render data.

For example, it may noisify image data before it gets hashed:

const noisify = (canvas, context) => {

  let imageData = context.getImageData(); 

  // Introduce random noise pixels  


CanvasRenderingContext2D.prototype.getImageData = () => {

  noisify(canvas, context);
  return originalGetImageData(); 

With Puppeteer, we can programatically install extensions to leverage this fingerprint randomization.

By natively integrating extensions and proxy rotation into your scripts, tools like Bright Data handle fingerprinting and other bot protections for you behind the scenes. This allows focusing on your business logic while they manage low-level anti-detection.


Canvas fingerprinting has become highly prevalent across the web for accurately identifying scrapers and bots. Bypassing it client-side is challenging but can be achieved by mimicking or randomizing fingerprint hashes.

However for reliable large-scale web scraping, leveraging a dedicated proxy solution like Bright Data to handle canvas fingerprinting and advanced bot mitigations is essential. Their infrastructure and residentials proxies obscure fingerprints and make scraping seamless.

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