Browser Fingerprinting & Privacy Audit Lab: Canvas, WebGL, AudioContext, and Tracking Surface Analysis

// Demonstration: Defensive Canvas Noise Injection Script
// Injects undetectable noise into HTML5 Canvas to defeat tracking hashes
(function protectCanvasPrivacy() {
  const originalToDataURL = HTMLCanvasElement.prototype.toDataURL;
  const originalGetImageData = CanvasRenderingContext2D.prototype.getImageData;

  // Add subtle mathematical noise to pixel values
  function addNoise(canvas: HTMLCanvasElement) {
    const ctx = canvas.getContext('2d');
    if (!ctx) return;
    const width = canvas.width;
    const height = canvas.height;
    if (width === 0 || height === 0) return;

    try {
      const imgData = originalGetImageData.call(ctx, 0, 0, width, height);
      // Alter 1 in 1000 pixels by +/- 1 color value (invisible to human eye)
      for (let i = 0; i < imgData.data.length; i += 4) {
        if (Math.random() < 0.005) {
          imgData.data[i] = (imgData.data[i] + 1) % 256; // Red channel subtle shift
        }
      }
      ctx.putImageData(imgData, 0, 0);
    } catch {
      // Cross-origin tainted canvas
    }
  }

  HTMLCanvasElement.prototype.toDataURL = function(...args) {
    addNoise(this);
    return originalToDataURL.apply(this, args);
  };
})();