FP-Devicer

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

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.