How identifiable is your browser?
Even without cookies, the small facts your browser shares can add up to a near-unique signature. This test gathers those signals and estimates how much you stand out. Everything runs on your device.
What browser fingerprinting is
Fingerprinting is a way to recognise a browser from the combination of its characteristics rather than from a stored identifier like a cookie. Any single characteristic, say that you use a common browser on a common operating system, is shared by millions of people. But stack enough of them together (your exact screen size, your timezone, your language list, your graphics hardware, tiny quirks in how your device draws text on a canvas) and the odds that anyone else matches you exactly drop fast.
The unsettling part is that it needs no permission and no storage. A script reads these values as a page loads, hashes them, and can recognise you again later even if you clear cookies or switch to private browsing. That is why fingerprinting is a favourite of trackers and, more defensibly, of anti-fraud systems that want to spot a returning device.
How to read your score
The entropy figure is measured in bits. Each bit roughly doubles the number of distinct browsers a value can distinguish, so more bits means you are more identifiable. A result in the low range means you blend in with a large crowd; a high range means your particular combination is rare. The WebGL renderer and canvas signals usually dominate, because your graphics hardware and its driver are far less common than your browser name.
Why sites collect it
Advertisers, analytics firms and anti-fraud systems build fingerprints to recognise returning devices without cookies, link sessions, and detect bots or account abuse. The same technique serves both tracking and legitimate security.
Privacy implications
Fingerprinting is one of the hardest forms of tracking to escape because it needs no storage on your device and ignores your cookie choices. The counter-intuitive defence is sameness: the more your browser looks exactly like everyone else's, the harder you are to single out, which is the strategy privacy browsers pursue.
How to become less unique
- Use a browser that fights fingerprinting for you. Tor Browser makes its users look identical to one another, which is the only approach that fully works. Brave and Firefox both mask or randomise the strongest signals, which helps without Tor's costs.
- Keep a mainstream, up to date setup. A current, common browser version on a common operating system means your signals match a very large crowd. Heavy customisation makes you easier to fingerprint, not harder.
- Go easy on rare fonts and extensions. Unusual installed fonts change how text rasterises, which changes your canvas signal. Some extensions leave detectable traces of their own.
- Harden the graphics signals before anything else. The WebGL renderer and canvas rendering contribute more than everything else on this page put together. A browser that blocks or normalises them is worth more than any number of smaller adjustments.
Then look at the individual signals, because which ones stand out differs from person to person. The WebGL renderer, user agent, screen resolution and timezone pages each explain what that one reveals and what softening it costs you.
One warning applies to all of it: a measure that makes you rare is worse than no measure at all. Swapping a user agent shared with millions for one almost nobody sends leaves you easier to pick out, not harder. Blending in beats standing out, every time.
Frequently asked questions
Can fingerprinting track me without cookies?
Yes. That is the point of it. Fingerprinting recognises your device from its signals, so it survives clearing cookies and using private browsing.
How do I make my browser less unique?
Use an anti-fingerprinting browser, keep a mainstream and updated configuration so you blend in, and avoid rare fonts and extensions. Looking common is the goal.
Is a lower entropy score better?
For privacy, yes. Lower entropy means more people share your combination of signals, so you are harder to single out. Higher entropy means you stand out more.
How this compares to Cover Your Tracks and AmIUnique
Both of those measure against a real dataset, which is something this page cannot do and does not claim to. They can tell you how rare your combination is among the browsers they have seen. This page tells you which signals your browser hands over, and offers a clearly labelled estimate of what each one is worth.
The difference is what you pay. Comparing yourself against a population means contributing your own fingerprint to that population, which is a fair trade and worth making knowingly. EFF Cover Your Tracks and AmIUnique are the two worth using for that. Ideally use both: this page to see the mechanism, those to see the rarity.
Sources
Last checked on . Every figure on this page, and where it comes from, is set out on the methodology page.