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devicer.js
Advanced tools
FP-Devicer is a digital fingerprinting middleware library designed for ease of use and near-universal compatibility with servers. Developed by Gateway Corporate Solutions.
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.
You can install FP-Devicer with
npm install devicer.js
You can also install the meta-package for the entire Devicer Intelligence Suite with
npm install @gatewaycorporate/devicer-intel
To run the quickstart example:
npm install express devicer.js
npx tsx src/examples/quickstart.ts
There is a public demo of FP-Devicer (FP-Cicis Command and Control) available for viewing at cicis.info.
This project uses typedoc and autodeploys via GitHub Pages. You can view the generated documentation here.
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();
Custom plugins implement DeviceManagerPlugin from devicer.js. See the
documentation for the full
interface reference.
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
The whitepaper covers the theory, architecture, and design decisions behind FP-Devicer. You can read it here.
FAQs
Open-Source Digital Fingerprinting Middleware
We found that devicer.js demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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