Free tools that show what a site sees about you

Why this matters more than your VPN does

Most people who get flagged running multiple accounts assume it was the IP address. Sometimes it is. More often it’s everything else the browser hands over before the page even finishes loading: canvas rendering, installed fonts, GPU model, audio stack, screen geometry, timezone offset, and a dozen smaller signals that combine into something close to a fingerprint. You can rotate a proxy in two seconds. You can’t rotate a fingerprint that fast unless the browser is built to change it properly, and even then you need to know what “properly” means.

The good news is you don’t have to guess what a site sees. There’s a small set of free tools that expose the same data points platforms use, and running your setup through them before you touch a real account is one of the cheapest habits in this line of work. This isn’t about beating detection with a trick. It’s about understanding your own exposure so you’re not finding out the hard way.

What a fingerprint actually is

A browser fingerprint isn’t one thing, it’s a bundle of individually weak signals that get strong when combined.

• Canvas fingerprint: the browser is asked to draw a hidden image or piece of text, and the exact pixel output varies slightly by GPU, driver, and OS. That variation is a stable identifier across sessions.
• WebGL / GPU report: your graphics card and driver version, readable through the WebGL renderer string. Ten “different” browser profiles all reporting the same obscure GPU model is a pattern.
• Audio fingerprint: similar idea to canvas, but through the Web Audio API’s oscillator output. Rarely spoofed correctly by cheap tools.
• Fonts: the list of installed fonts a page can detect, which narrows down OS, region, and sometimes the specific machine image if it’s a cloned VM.
• Screen and hardware: resolution, color depth, CPU core count, device memory, all exposed through standard JS APIs.
• Timezone and locale vs IP: a proxy in Singapore paired with a system clock set to US Eastern is a mismatch a script catches instantly.
• TLS/JA3 and HTTP header order: the way your client negotiates the TLS handshake and orders its headers has its own signature, separate from anything JavaScript reports. This one catches automation tools that get the browser fingerprint right but never touch the network layer.

No single signal proves anything on its own. What gets accounts flagged is consistency, or the lack of it, across a fleet: the same canvas hash showing up under twenty different names, or a profile that’s internally contradictory, like a mobile user agent paired with a desktop GPU string.

The tools worth actually using

These are free, don’t require an account, and each one shows a different slice of the picture. None of them tell you whether a specific platform will ban you, they tell you what data is available for a platform to use.

BrowserLeaks is the broadest single stop. It breaks out canvas, WebGL, fonts, audio, WebRTC (which can leak your real IP even behind a proxy if it’s not handled), and a full HTTP header dump. Good first stop because it separates every signal instead of giving you one composite score.

AmIUnique takes a different angle: it compares your fingerprint against a crowd-sourced database and tells you how many other visitors shared the exact same combination of signals. A fingerprint that’s “unique” isn’t inherently bad, but if you’re trying to blend a browser profile in with normal traffic, uniqueness is the opposite of what you want.

EFF’s Cover Your Tracks (the successor to Panopticlick) was built for privacy research rather than antidetect testing, but it’s useful precisely because it wasn’t built for people like us. It gives a plain read on whether your browser is protected against tracking and fingerprinting, and it’s a good sanity check on default browser settings before you start layering anything on top.

CreepJS is the most aggressive of the group. It doesn’t just read your fingerprint, it actively probes for signs of spoofing: lies between what the browser claims and what it actually does under the hood, inconsistent API behavior, timing anomalies that suggest automation. If a stealth or antidetect setup is going to get caught by anything free, it’s usually this one. Worth running last, after you’ve cleaned up everything the simpler tools flagged.

Pixelscan is built specifically around the “does this look automated” question and gives a more direct verdict on bot-like signals, WebRTC leaks, and IP-to-timezone consistency. It’s closer in spirit to what a platform’s fraud system is checking than a general privacy tool is.

IPLeak.net focuses on the network side: does your visible IP match your proxy, does WebRTC leak a second address, does your DNS resolve through a server that gives away your real location. If you’re running residential or mobile proxies, this is the fastest way to catch a leak before it shows up as a ban.

Reading the results without overreacting

A clean pass on all six tools doesn’t mean an account is safe, and one flagged signal doesn’t mean it’s doomed. What you’re looking for is pattern, not perfection:

• Does the IP’s geolocation match the timezone and locale the browser reports? Mismatches here are the single most common thing that gets an account flagged early, because it’s the easiest thing for a platform to check automatically.
• Is WebRTC leaking your real IP behind the proxy? This is a configuration bug, not a fingerprinting subtlety, and it’s fixable.
• Does the canvas or WebGL hash repeat identically across profiles that are supposed to be independent? If every “different” account is running the same VM image with the same GPU passthrough, they’ll share a hash no matter what the user agent string says.
• Does CreepJS catch a lie? If it flags that your reported hardware concurrency doesn’t match your reported device memory, or that a spoofed property doesn’t behave like the real one under a timing test, that’s a signal a more sophisticated detection system will likely catch too.

None of these tools can see your account history, your behavioral patterns, or the internal risk model a platform runs after login. They’re pre-flight checks, not guarantees. Anyone telling you a clean scan means you’re safe is selling something.

Where the stack actually matters

This is the part free tools can’t fix for you: a profile that passes a scan today needs the underlying browser fingerprint to actually be a real, coherent, individually-assigned identity, not a template copied across fifty windows with a font list swapped. That’s the difference between an antidetect browser that generates a fresh, internally consistent fingerprint per profile and one that just changes the user agent string and calls it done.

Same logic applies to the network layer. A residential or mobile IP that matches the fingerprint’s claimed location, that isn’t shared across your other accounts, and that comes from a real device rather than a datacenter block passing itself off as residential, closes most of the gaps these tools expose. We run our own proxy infrastructure out of Singapore and manage cloud phones for exactly this reason: it’s easier to keep a fingerprint honest when the IP behind it is a real mobile connection rather than a rented block that a dozen other operators are also routing through.

Run your setup through a couple of these tools before you commit real accounts to it. It costs nothing, takes ten minutes, and it’s the difference between finding a leak yourself and finding out from a suspended account.

If you’re building out a fleet and want proxies, cloud phones, and antidetect browsers that are actually built around this, take a look at what we run.

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