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

Installation

You can install FP-Devicer with

npm install devicer.js
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You can also install the meta-package for the entire Devicer Intelligence Suite with

npm install @gatewaycorporate/devicer-intel
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Quickstart

To run the quickstart example:

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

Plugin Architecture

DeviceManager supports a universal plugin system via use(). Any object implementing DeviceManagerPlugin (with a registerWith(deviceManager) method) can extend identify() results with additional signals.

import { createSqliteAdapter, DeviceManager } from "devicer.js";
import { IpManager } from "ip-devicer";
import { TlsManager } from "tls-devicer";

const manager = new DeviceManager(createSqliteAdapter("./db.sqlite"));

manager.use(new IpManager({ licenseKey: process.env.DEVICER_LICENSE_KEY }));
manager.use(new TlsManager({ licenseKey: process.env.DEVICER_LICENSE_KEY }));

// result now includes ipEnrichment, tlsConsistency, etc.
const result = await manager.identify(fp, {
	ip: req.ip,
	tlsProfile: req.tlsProfile,
});

// Optionally unregister a plugin later:
const unregister = manager.use(myPlugin);
unregister();
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Custom plugins implement DeviceManagerPlugin from devicer.js. See the documentation for the full interface reference.

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
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Whitepaper

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