AmiUnique.io

Introduction to AmiUnique.io

AmiUnique.io is a browser fingerprinting analysis tool that quantifies how identifiable a user's browser configuration is within a reference database of over two million fingerprints. It provides real-time insights into the uniqueness of technical attributes collected from web browsers, enabling users to understand their digital traceability across websites. The tool is designed for privacy-conscious individuals, security professionals, developers, and compliance auditors who need objective visibility into browser-based identification vectors.

The platform operates without requiring account creation, stores no personal data on the client or server beyond transient session identifiers, and delivers results in under 100 milliseconds. Its interface emphasizes transparency through documented signal collection, statistical context, and clear classification of fingerprint dimensions by stability and origin.

Key Takeaways

• Analyzes over 80 deterministic browser fingerprinting dimensions including Canvas, WebGL, AudioContext, font enumeration, TLS parameters, and motion sensors
• Classifies signals using a Three-Lock system: Gold (hardware-level, highly stable), Silver (software-level, medium stability), and Bronze (network-level, session-specific)
• Provides real-time percentile ranking against a database of 2M+ fingerprints, showing where a given fingerprint falls on the statistical distribution curve
• Includes lie detection to identify inconsistencies such as timezone drift, locale mismatches, or user-agent spoofing
• Features transparent data governance: every collector is documented, auditable, and mapped to its storage location (e.g., Cloudflare Workers, D1 database)
• Built with static Next.js 14 export and deployed on a global edge network for low-latency performance
• Offers a fully client-side scan process with no persistent tracking, data selling, or third-party analytics

How AmiUnique.io Works

AmiUnique.io executes a series of standardized JavaScript APIs and Web APIs in the user’s browser to collect deterministic attributes. These include rendering outputs from Canvas and WebGL contexts, audio processing graphs, font availability hashes, language and timezone configurations, hardware capabilities (e.g., display resolution, HDR gamut, ProMotion), and network characteristics (e.g., ASN, TLS cipher suites, RTT, Cloudflare colocation). Each signal is evaluated for uniqueness relative to the platform’s anonymized, aggregated fingerprint database.

Collected signals are grouped into the Three-Lock taxonomy based on persistence and origin: Gold-lock signals reflect immutable or hardware-bound properties; Silver-lock signals derive from software configuration and are subject to change with OS or browser updates; Bronze-lock signals depend on network conditions and may vary between sessions. The platform computes a composite percentile score and highlights top-contributing dimensions—flagging rare values (e.g., "1 in 10,000") or common ones (e.g., "1 in 4")—alongside behavioral anomalies detected via cross-signal validation.

Core Benefits and Applications

Security teams use AmiUnique.io to assess fingerprinting exposure during red-teaming exercises or browser hardening validation. Privacy researchers leverage the documented schema and open telemetry to audit fingerprinting resistance in browsers and extensions. Developers integrate insights to inform anti-fingerprinting design patterns—for example, normalizing screen settings, limiting font enumeration, or rotating egress IPs. Compliance professionals reference the transparent data contract and collector documentation when evaluating adherence to GDPR, CCPA, or UK ICO guidance on consentless identification.

The tool also supports end-user education: by visualizing how combinations of technical attributes form a stable identifier, it clarifies why traditional cookie deletion does not mitigate cross-site tracking—and why techniques like Tor Browser standardization or Firefox Enhanced Tracking Protection reduce fingerprint entropy. Use cases span threat modeling, browser configuration benchmarking, and privacy awareness training.