Skip to content
GET IN TOUCH

Overview

FINGER is a Chrome browser extension developed to detect and analyze web-based fingerprinting techniques in real time. Unlike traditional privacy tools that rely on static filters or blocklists, FINGER uses a behavior-based approach to monitor JavaScript property access and API calls directly within the browser. This gives users transparency and control over how their online behavior is tracked. The tool operates locally, requires minimal permissions, and is open source, ensuring privacy and allowing community collaboration.

shape

Challenge

Browser fingerprinting has become one of the most advanced and persistent forms of online tracking. It uses unique device and browser characteristics to identify users across websites, often without their consent.

Current privacy tools face several challenges:

  • Static detection limits: Traditional tools depend on predefined rules that are easy for trackers to bypass.
  • API restrictions: Chrome’s extension framework limits access to certain internal browser data, reducing visibility.
  • System-level invisibility: Some fingerprinting methods operate at hardware or privileged levels, beyond browser control.
  • Evasive techniques: Trackers use obfuscated or dynamically generated scripts to hide their behavior.

These challenges make it difficult for users to fully understand or defend against modern tracking mechanisms.

Solution

FINGER introduces a modular and adaptative system designed to overcome these limitations. It uses several key techniques:

  • Dynamic detection: Monitor JavaScript execution patterns to identify suspicious behavior, even when obfuscated.
  • Entropy-based analysis: Calculates how uniquely a user can be identified to assess privacy risk.
  • Local operation: All analysis happens within the user’s browser, meaning no data is sent externally.
  • Active Blocking: Users can instantly block or allow detected scripts. If a legitimate script is flagged, they can approve it, preventing broken pages while maintaining privacy control.
  • Minimal permissions: The tool only needs basic browser permissions, minimizing exposure.
  • Open-source and modular design: Enables transparency, community contributions and continuous improvement.
JavaScript Executes, which lead to FINGER Monitoring and scoring entropy and alerting user

Use Cases & Industry Applications

Research and academic analysis: Enables controlled studies of fingerprinting in real-world browsing contexts.

Web application auditing: Helps developers identify and correct unintended tracking behaviors in their websites.

Educational demonstrations: Serves as teaching tool for understanding fingerprinting and online privacy

Community-driven expansion: Researchers and developers can create new detection modules or scorung systems.

Advanced user monitoring: Techincal users can view detailed trace data and adjust detection settings.

Integration with research platforms: Can be linked to testing frameworks and automated systems for reproducible experiments.

Cross-browser compatibility (future): Planned support for Firefow, Edge and Safari to broaden accessibility.

Results

FINGER has proven effective in detecting and managing advanced fingerprinting behaviors, such as canvas rendering, font enumeration and audio context probing, that often evade native browser protections.

Unlike static blockers, it identifies both known and emerging techniques in real time.

The plugin also includes active blocking feature, allowing users to directly manage detected scripts. If a legitimate script is flagged, it can be allowed, avoiding broken pages while maintaining privacy control. This gives users flexible and immediate control over their browsing experience.

FINGER complements existing browser defenses by:

  • Providing real-time visibility into tracking attempts.
  • Offering a transparent, user-controllable monitoring layer.
  • Supporting rapid adaptation through modular updates.

Even browsers with built-in fingerprinting defenses remain vulnerable to sophisticated methods, but FINGER reduces this gap by giving users actionable insights and stronger control over their privacy.

Looking Ahead

The next development stages aim to expand FINGER’s coverage and functionality:

  • iFrame and embedded context detection: Detect fingerprinting within isolated frames and embedded elements.
  • Entropy-based detection models: improve accuracy by linking entropy levels with access frequency and property usage.
  • Cross browser support: Extend compatibility to Firefox, Edge and Safari.
  • Integration with research platforms: Support large-scale fingerprinting studies and collaborative experiments.

These improvements will enhance precision, adaptability, and user control, moving FINGER from a passive monitoring tool toward an active defense system for online privacy.

Need more information about this project?
Contact us
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.