Canvas Hash

1. Technical Classification

Category: Rendering Fingerprint

Data Type: Hexadecimal String (Hash)

Availability: All modern browsers with HTML5 Canvas support

A canvas hash is a cryptographic fingerprint generated from the rendered output of HTML5 canvas operations. It works by:

• Rendering Process: JavaScript draws specific text and graphics on an invisible canvas
• Data Extraction: The pixel data is converted to a data URL (base64-encoded PNG)
• Hash Generation: The data URL is passed through a hash function (MD5, SHA-256, or custom)
• Unique Identifier: The resulting hash is stable across sessions and acts as a digital fingerprint

2. Background & Purpose

Historical Context:

Canvas fingerprinting was first documented in 2012 by Keaton Mowery and Hovav Shacham in their paper "Pixel Perfect: Fingerprinting Canvas in HTML5." The technique exploits subtle differences in how different systems render graphics.

How Canvas Hashing Works:

1. Draw Operations: A website uses JavaScript to draw text (with specific fonts) and shapes on an HTML5 canvas element
2. Pixel Rendering: Different combinations of hardware (GPU), software (graphics drivers), and OS render the same canvas slightly differently at the pixel level
3. Data Extraction: The canvas is converted to a PNG image encoded as a base64 data URL using toDataURL()
4. Hashing: The data URL string (typically 4,000-10,000 characters) is passed through a hash function to create a short, unique identifier
5. Tracking: This hash remains consistent for the same browser/system combination and can track users across websites

Why Hashing Instead of Raw Data?

• Reduces data size from ~5-10KB to 16-64 characters
• Makes comparison faster (string matching instead of image comparison)
• Provides stable identifier for database storage
• Easier to share across tracking networks

3. Hash Characteristics & Uniqueness

Common Hash Functions Used:

• MD5: 128-bit hash (32 hexadecimal characters) - Fast but older
• SHA-1: 160-bit hash (40 hex characters) - More secure than MD5
• SHA-256: 256-bit hash (64 hex characters) - Most secure, slower
• Custom: Simple hash algorithms like the one used in this demo (variable length)

Uniqueness Statistics:

What Makes Each Hash Unique?

• GPU & Graphics Driver: Different GPUs (Intel, NVIDIA, AMD) render slightly different pixel values
• Operating System: Windows, macOS, and Linux use different rendering engines
• Font Rendering: Subtle differences in anti-aliasing and subpixel rendering
• Browser Engine: Chromium, Gecko, and WebKit render canvases slightly differently
• Image Compression: PNG encoding algorithms vary slightly between implementations

4. Common Uses

Legitimate Uses:

• Fraud Detection: Banks and payment processors use canvas fingerprinting to detect suspicious login attempts from unfamiliar devices
• Bot Detection: Distinguishing human users from automated bots (bots often have consistent canvas fingerprints)
• Security Enhancement: Adding an extra layer to multi-factor authentication
• A/B Testing: Ensuring users get consistent experiences across sessions without cookies

Privacy-Invasive Uses:

• Cross-Site Tracking: Tracking users across different websites without consent
• Cookie Resurrection: Re-identifying users who deleted their cookies
• Incognito Mode Bypass: Tracking users even in private browsing mode
• Profile Building: Creating detailed behavioral profiles tied to device fingerprints
• Ad Targeting: Serving targeted ads based on persistent device identification

5. Platform & Browser Differences

Key Observations:

• Hardware Dependent: Same browser on different hardware = different hashes
• Driver Updates: Graphics driver updates can change the canvas fingerprint
• OS Updates: Major OS updates may alter rendering engines slightly
• Mobile Consistency: Mobile devices of the same model often produce identical hashes

7. Protection & Countermeasures

Browser-Based Protections:

Tor Browser (Best Protection):

• Returns blank canvas or standardized values
• All Tor users get identical canvas fingerprints
• Completely defeats canvas tracking
• Downside: Some websites may break or detect Tor usage

Brave Browser (Balanced Approach):

• Randomizes canvas fingerprint on each session (called "farbling")
• Different hash on every visit to the same site
• Prevents persistent tracking while maintaining compatibility
• Enabled by default in Standard shields mode

Firefox (Manual Configuration):

• Set privacy.resistFingerprinting to true in about:config
• Returns white canvas or standardized values
• Part of broader anti-fingerprinting protection
• May cause some websites to malfunction

Browser Extensions:

• CanvasBlocker (Firefox): Blocks or randomizes canvas fingerprinting attempts
• Privacy Badger (EFF): Detects and blocks tracking scripts including canvas fingerprinting
• uBlock Origin: Can block known canvas fingerprinting scripts

What Doesn't Work:

• ❌ Clearing cookies and cache (fingerprint is regenerated immediately)
• ❌ Private/Incognito mode (generates the same fingerprint as normal mode)
• ❌ VPNs alone (only change IP address, not device fingerprint)
• ❌ Disabling JavaScript (breaks most modern websites)

Best Practices:

• Use Tor Browser for maximum anonymity
• Use Brave or Firefox with anti-fingerprinting enabled for daily browsing
• Avoid using unique font collections or browser configurations
• Keep your system and graphics drivers updated (changes fingerprint occasionally)
• Use multiple browsers for different types of activities

8. Learn More