alexloth.com

Trackless Links: Clean URLs, Zero Tracking

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by

Alexander Loth
in ,

Every link you click carries invisible baggage. Those cryptic strings at the end of URLs — utm_source, fbclid, gclid, twclid — are tracking parameters. They tell advertisers where you came from, what you clicked, and how to follow you across the web.

Most people never notice them. But once you do, they are everywhere: in links your friends share, in newsletters, in search results. Each one is a breadcrumb that connects your browsing sessions into a detailed profile.

What Tracking Parameters Actually Reveal

A typical tracked URL looks like this:

https://example.com/article?utm_source=twitter&utm_medium=social&utm_campaign=spring2026&fbclid=IwAR3x...&gclid=Cj0KCQ...

Strip the tracking, and all you need is:

https://example.com/article

Those extra parameters tell the destination site (and every analytics tool it runs) exactly which campaign brought you, which platform you came from, and sometimes even which specific ad you clicked. When you share a tracked link with someone else, you are passing along that tracking context — and potentially linking their activity to yours.

Introducing Trackless Links

Trackless Links is a Safari extension for iOS and macOS that automatically strips tracking parameters from URLs as you browse. No manual cleanup, no copy-paste workarounds. It just works in the background.

Key design principles:

  • 100% on-device processing — Your URLs never leave your device. There is no server, no analytics, no data collection.
  • Comprehensive coverage — Strips UTM parameters, Facebook Click ID (fbclid), Google Click ID (gclid), TikTok, Twitter/X, and dozens more.
  • Smart redirects — Optionally redirects privacy-invasive frontends (e.g., Twitter to Nitter alternatives, Instagram to privacy-friendly viewers).
  • Universal purchase — Buy once, use on iPhone, iPad, and Mac with iCloud sync.

Bonus: Source Credibility with CRED-1

Trackless Links also ships with an integrated credibility layer powered by the CRED-1 dataset. This dataset covers 2,672 domains with five independent trust signals aggregated from established credibility databases. When you visit a site with known credibility issues, Trackless Links can flag it.

CRED-1 grew out of my doctoral research on AI-driven disinformation at Frankfurt University of Applied Sciences. The dataset is open source (CC BY 4.0) and documented in a peer-reviewed paper accepted at ACM WebConf 2026.

Try It

Trackless Links has 30 stars on GitHub. The code is available for review, and contributions are welcome.

If you care about keeping your URLs clean and your browsing private, give it a try. And if you find a tracking parameter that slips through, open an issue — I will add it.