CloudFlare Integration 🌤️

This integration is currently in beta. Client agent 2.5.1 or later required.


With CloudFlare worker integration you can greatly increase your Safari identification accuracy rates and remain undetected by ad blockers.

It will also make it impossible to detect that your website is using FingerprintJS Pro.

Who should use it?

If you're using CloudFlare, you should use this integration because it significantly increases the identification accuracy in Safari browsers. This is particularly important on iPhones, as manual cookie clearing is rare on mobile devices, but ITP-based lifetime capping is prevalent. After implementing this integration, you should observe significantly better identification rates on both desktop and mobile Safari.

You should also use it if your visitor base has a large percentage of ad blocking users.

Even if you are not using CloudFlare, the benefits this integration provides alone should make you want to start using CloudFlare with your website.

How it works

It works by designating a path on your website that is processed by a CloudFlare worker. Note that only this particular path is processed by the worker, the rest of your website is not affected. CloudFlare worker code is 100% open-source and fully open for review. The worker code is hosted on GitHub.

As an example, you can create a worker, that's assigned to path. All HTTP requests, sent to /metrics, will be passed through the worker. Worker code will call the Fingerprint.js PRO API and set a 1st-party cookie (Secure and HttpOnly) with the VisitorID from the API response. This will guarantee, that the cookie value is not affected by ITP and can be used for identification safely for a period of up to 1 year. All subsequent requests to /metrics will have the cookie attached, which will be read by the worker and passed along to the Fingerprint.js PRO API for identification.

Installation (command line)

This command-line guide will use the official CloudFlare Wrangler CLI.

Start by cloning the project from GitHub:

git clone git clone

Go into the cloned project directory: cd cloudflare-worker

Copy the wrangler.toml.example to wrangler.toml

cp wrangler.toml.example wrangler.toml

wrangler.toml is a file that contains all worker settings.

Now you need to replace some values in wrangler.toml

  • name the name of the worker. Give it a clear and descriptive name, e.g. fpjs-metrics

  • account_id use the CloudFlare account ID found in your dashboard.

  • zone_id use the CloudFlare zone ID found in your dashboard.

  • workers_dev set to true if you want to have a development version of the worker.

  • [env.production] route replace and /metrics with your website and the route that you want to use. You can use any route name: /metrics is a good default value.

Now that you have configured the worker in wrangler.toml, you need to authenticate with CloudFlare. Head to the API tokens page in your CloudFlare dashboard and create a new token using Edit Cloudflare Workers template.

Grab the token that you just generated and authenticate wrangler with it:

wrangler config
Enter API token:

Now you're ready to publish your worker:

wrangler publish --env production

You can now go to your CloudFlare dashboard (workers tab) and see your worker successfully registered. All the traffic that goes to /metrics from the Fingerprint.js PRO agent will be routed to the Fingerprint.js PRO API by the worker code.

JavaScript agent configuration

The last step is to change your JavaScript agent configuration. You need to specify the new route that you just registered with the worker. For CDN version, add a new endpoint configuration parameter:

window.fpLayer = window.fpLayer || [];
function fp() { fpLayer.push(arguments); }
fp('config', 'client', 'your-token');
fp('config', 'endpoint', '/metrics');
<script async src=""></script>

For NPM version, specify the endpoint parameter:

let fp = await FP.load({ client: "client-token", endpoint: "/metrics" });

That's all you need to do to implement the CloudFlare integration. After that, the requests to your new endpoint will return a __cflvid cookie (HttpOnly and Secure), which will help identification accuracy.