Educational Demonstration

Cookies are fading slowly. Fingerprinting is already here.

Most people have heard that third-party cookies are being phased out. In practice, the transition is uneven and slow across browsers and ecosystems. Meanwhile, many vendors combine browser and device fragments into persistent identifiers.

This page shows how those fragments can be assembled into a fingerprint. Then it shows how Lokker helps site owners identify when fingerprinting techniques are running on their pages, often through third parties they did not fully audit.

Typical fingerprint inputs

  • User agent and browser brand hints
  • Screen and viewport dimensions
  • Language, timezone, and locale settings
  • Hardware signals like core count and memory
  • Graphics stack details (WebGL vendor/renderer)
  • Plugin and feature availability patterns

Fingerprinting scripts present

We surface when fingerprinting libraries or custom fingerprinting routines appear in your request chain.

Who introduced it

We map parent-child request relationships so you can see whether a first party, tag manager, or third-party vendor introduced the behavior.

Risk context, not noise

Some fingerprinting can support fraud prevention or bot defense. We focus on where behavior, disclosure, and consent expectations are misaligned.

Before you start

This is an educational simulation. The page does not start signal collection until you choose to run it. We do not transmit your generated fingerprint to any external system, and we do not persist it in local storage.

No upload. No storage. In-browser only.
Fingerprint simulation console

Engine is waiting

Click Start local demo to collect browser/device fragments and produce a simulated fingerprint hash in-browser.

No network calls. No storage. No export.

Why this matters

The web has identity layers users never see

Even when users do not knowingly accept all tracking, fingerprint-style profiling can still emerge from ambient browser signals. That is why consent banners alone are not enough.

Privacy teams need to observe what actually leaves the browser, validate opt-out and GPC behavior, and continuously monitor third-party changes over time.

Legitimate vs risky usage

  • Potentially legitimate: bot defense, account takeover detection, and security forensics with clear governance.
  • Higher concern: silent cross-site profiling through third parties with weak disclosure or consent alignment.
  • Lokker focus: identify the behavior, show where it came from, and prioritize actionable remediation.

From demo to action

Understand the invisible layer. Then control it.

Lokker helps teams measure real request behavior, validate consent controls, and reduce privacy exposure across portfolios of sites.