Disclosure first: I’m the author of this page (香蕉痞 Yang), and I used an AI assistant to help write this post. It’s free, no account, no ads.

I kept getting asked “why does site X still recognise me when I’m on a VPN?”, so I built a page that shows the answer from the website’s side. It reads what a normal site can read from your browser without any permission prompt (118 signals: timezone vs. IP location, languages, fonts, GPU/canvas, screen, network, etc.), then writes it up as one plain paragraph, the kind of profile a tracker could build.

The part I find most useful is the contradiction checks: WebRTC leaks, DNS leaks, and mismatches such as a US exit IP with an Asia/Shanghai timezone and zh-CN fonts, which is usually what gives away a VPN, proxy or a spoofed user agent.

Privacy notes, since this is the right crowd to ask: no IP is stored, only anonymous counts of how common each value is (used for the “how unique are you” part). The page itself is not open source yet; the wider 1ms.dog network toolset it belongs to is MIT on GitHub (yt1988/1ms.dog).

Link: https://who.1ms.dog/

Genuinely curious what people here see. Do Tor Browser / Mullvad Browser / LibreWolf with resistFingerprinting come out looking “common”, and are there signals you think I’m missing or over-weighting?