Browser Fingerprinting Guide

Browser Fingerprinting in 2025Canvas, WebGL, Audio & Font Detection Explained

Browser fingerprinting has become the dominant tracking method as cookies fade. In 2025, over 10,000 top websites deploy fingerprinting, achieving 80-90% unique identification rates. Understanding these techniques is essential for any privacy operation.

80-90%
Of all browsers are uniquely identifiable
10,000+
Actively deploy fingerprinting scripts
200+
Browser attributes analyzed together
99.9%
When combined with other signals

Research updated: December 2025

How Browser Fingerprinting Works

Fingerprinting collects dozens of browser attributes and combines them into a unique identifier. Unlike cookies, fingerprints persist across sessions and can't be easily deleted. Here's the collection process.

1

JavaScript API Calls

Scripts call browser APIs: Canvas for 2D rendering, WebGL for 3D/GPU info, AudioContext for audio processing, and navigator properties for system details.

2

Hash Generation

Each attribute is hashed. Canvas pixels become a hash. WebGL parameters become a hash. These are combined into a composite fingerprint identifier.

3

Cross-Session Tracking

The fingerprint persists across sessions, private modes, and cookie clearing. Your device produces the same fingerprint until hardware/software changes.

Example: Canvas Fingerprinting Script

// Basic canvas fingerprinting (simplified)
function getCanvasFingerprint() {
  const canvas = document.createElement('canvas');
  canvas.width = 200;
  canvas.height = 50;

  const ctx = canvas.getContext('2d');

  // Draw text with specific font and colors
  ctx.textBaseline = 'alphabetic';
  ctx.font = '14px Arial';
  ctx.fillStyle = '#f60';
  ctx.fillRect(100, 1, 62, 20);

  ctx.fillStyle = '#069';
  ctx.fillText('Hello, world!', 2, 15);
  ctx.fillStyle = 'rgba(102, 204, 0, 0.7)';
  ctx.fillText('Hello, world!', 4, 17);

  // Extract pixel data as hash
  return canvas.toDataURL();
}

// Each device produces different pixel output
// due to GPU, drivers, fonts, and anti-aliasing

Major Fingerprinting Techniques

Each technique exploits different browser APIs to extract device-specific information. Together, they create a highly unique identifier.

Canvas Fingerprinting

Very High Entropy

The most powerful fingerprinting technique. Websites render invisible graphics using the HTML5 Canvas API, then read the pixel data.

How It Works

  1. 1Script creates an invisible <canvas> element
  2. 2Draws text, shapes, and gradients with specific fonts and colors
  3. 3Reads the resulting pixel array using toDataURL()
  4. 4GPU drivers, font rendering, and anti-aliasing create unique variations

Defense Methods

  • Antidetect browsers inject fake canvas data
  • Tor Browser blocks/standardizes canvas reads
  • Safari adds noise in private mode
  • Firefox has optional canvas protection

Key Insight: Tor Project states: "Canvas is the single largest fingerprinting threat browsers face today."

WebGL Fingerprinting

Very High Entropy

Goes deeper than Canvas by probing GPU capabilities. Extracts vendor strings, renderer info, and shader compilation differences.

How It Works

  1. 1Queries WEBGL_debug_renderer_info for GPU vendor/renderer
  2. 2Tests supported extensions and parameters
  3. 3Renders 3D scenes to detect floating-point calculation variations
  4. 4Shader compilation produces GPU-specific bytecode patterns

Defense Methods

  • Antidetect browsers spoof vendor/renderer strings
  • Tor disables WebGL by default
  • Random parameter modification can break consistency
  • Must match spoofed GPU to rendering capability

Key Insight: WebGL reveals GPU model (e.g., "NVIDIA GeForce RTX 4090") and driver version directly.

AudioContext Fingerprinting

High Entropy

Generates audio using the Web Audio API and analyzes subtle processing differences across devices.

How It Works

  1. 1Creates an OscillatorNode with DynamicsCompressor
  2. 2Processes audio signal through the pipeline
  3. 3Reads output samples as floating-point array
  4. 4Audio hardware/drivers create measurable variations

Defense Methods

  • Safari 17+ adds noise in Private mode
  • Antidetect browsers can spoof audio output
  • Complete API blocking breaks legitimate sites
  • Noise injection is more effective than blocking

Key Insight: Apple added protection in Safari 17: AudioContext injects randomness in Private mode.

Font Fingerprinting

High Entropy

Detects which fonts are installed by measuring text rendering dimensions. Each font combination creates a unique signature.

How It Works

  1. 1Renders text with fallback font detection
  2. 2Measures bounding box width/height for each test font
  3. 3Differences indicate font presence or absence
  4. 4Tests 100+ fonts to build unique font list

Defense Methods

  • Tor limits available fonts with fallback lists
  • Antidetect browsers can spoof font metrics
  • CSS font-display can mask some detection
  • Browser extensions can limit exposed fonts

Key Insight: Average Windows system has 200+ fonts; combinations create billions of unique signatures.

The 2025 Detection Landscape

Detection has evolved from simple fingerprinting to ML-powered behavioral analysis. Here's what's changed in 2025.

Machine Learning Detection

Modern systems like Cloudflare and PerimeterX use ML to analyze fingerprint consistency across sessions. They detect when fingerprints change too often (randomization) or stay too static (spoofing).

Defense: Antidetect browsers create consistent profiles that evolve naturally over time, avoiding both randomization and static patterns.

Hardware-Level Detection

WebGL now reveals GPU model and driver version directly. If your Canvas claims to render like an RTX 4090 but WebGL shows Intel integrated graphics, you're flagged immediately.

Defense: Use antidetect browsers that match Canvas rendering to WebGL capabilities. Inconsistency is the biggest tell.

Cross-Browser Fingerprinting

Advanced fingerprinting can identify you across different browsers on the same device. GPU, audio hardware, and installed fonts remain constant.

Defense: Each antidetect profile should simulate a completely different device, including hardware characteristics.

Anti-Fingerprinting Detection

Detection systems now identify anti-fingerprinting tools. Random values, blocked APIs, or inconsistent responses trigger suspicion.

Defense: Quality antidetect browsers produce realistic, consistent fingerprints rather than blocking or randomizing APIs.

How Mobile Proxies Complement Antidetect

Fingerprinting is just one layer. Your IP address is checked first. Here's why mobile proxies are essential for fingerprint bypass.

IP-Fingerprint Correlation

Detection systems correlate IP type with browser fingerprint. A mobile fingerprint from a datacenter IP is instantly suspicious. Mobile IPs make mobile fingerprints believable.

Consistent IP-fingerprint pairing

Trust Score Foundation

IP reputation is checked before fingerprinting runs. Datacenter IPs are flagged immediately. Mobile IPs from real carriers start with high trust, giving fingerprint spoofing a chance to work.

Pass initial IP checks

CGNAT Advantage

Mobile carriers use CGNAT - thousands of users share IPs. Platforms can't ban mobile IPs aggressively without blocking real users. This protection extends to your spoofed fingerprints.

Shared IP protection

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