devicer.js

FP-Devicer

Developed by Gateway Corporate Solutions LLC

FP-Devicer is a digital fingerprinting middleware library designed for ease of use and near-universal compatibility with servers.

Usage

Importing and using the library to compare fingerprints between users is as simple as collecting some user data and running the calculateConfidence function.

// 1. Simple Method (Using defaults)
import { calculateConfidence } from "devicer.js";

const score = calculateConfidence(fpData1, fpData2);

// 2. Advanced Method (Custom weights & comparitors)
import { createConfidenceCalculator, registerPlugin } from "devicer.js";

registerPlugin("userAgent", {
  weight: 25,
  comparator: (a, b) => levenshteinSimilarity(String(a || "").toLowerCase(), String(b || "").toLowerCase())
});

const advancedCalculator = createConfidenceCalculator({
  weights: {
    platform: 20,
    fonts: 20,
    screen: 15
  }
})

const advancedScore = advancedCalculator.calculateConfidence(fpData1, fpData2);

// 3. Enterprise usage (DeviceManager)
import express from 'express';
import { DeviceManager, createInMemoryAdapter } from 'devicer.js';

const manager = new DeviceManager(createInMemoryAdapter());
const app = express();
app.use(express.json());

app.get('/', (req, res) => {
	res.sendFile('public/index.html', { root: process.cwd() });
});

app.post('/identify', async (req, res) => {
  const result = await manager.identify(req.body, { userId: (req as any).user?.id, ip: req.ip });
  res.json(result); // → { deviceId, confidence, isNewDevice, linkedUserId }
});

app.listen(3000, () => console.log('✅ FP-Devicer server ready at http://localhost:3000'));

The resulting confidence will range between 0 and 100, with 100 providing the highest confidence of the users being identical.

Quickstart

To run the quickstart example:

npm install express devicer.js
npx tsx src/examples/quickstart.ts

Demo

There is a public demo of FP-Devicer (FP-Cicis Command and Control) available for viewing at cicis.info.

Documentation

This project uses typedoc and autodeploys via GitHub Pages. You can view the generated documentation here.

Benchmarks

When calibrated correctly, FP-Devicer is over 99% accurate and gets more accurate as it analyzes fingerprints. The average time to calculate the difference between two fingerprints is less than 1ms. To view/run the benchmarks on your machine:

npm run bench

Whitepaper

The whitepaper covers the theory, architecture, and design decisions behind FP-Devicer. You can read it here.