DavidD
Joined 16 years ago
Karma
53
Submissions
75
Member since
Aug 19
Recent submissions
Comment · 2 months ago
If it changes every load, that's your browser farbling canvas/audio per-read (Brave or Firefox), which means the anti-fingerprinting is working. We missed crediting that in v1, so it should read lower now if you reload.
Comment · 2 months ago
That panel reconstructs what a pixel would send from your own browser values, locally, and never makes the request. NextDNS seeing nothing is the tool working exactly as designed.
Comment · 2 months ago
A VPN or Tor swaps it out entirely, which your browser fingerprint survives. It is a strong identifier, not a permanent one.
Comment · 2 months ago
Fun fact: some malware won't execute if it sees a Russian/Ukrainian keyboard layout, because the authors avoid hitting victims in their own jurisdiction.
Comment · 2 months ago
I built this after a thread here about Alibaba using an audio-context trick to
fingerprint visitors. I knew a fair number of fingerprinting methods but not that
one, and I wanted to see all of them in one place, running against my own browser.
GlassBox runs ~31 probes (canvas, WebGL/WebGPU, audio, fonts, the WASM feature set, math/engine quirks, WebRTC IP, timezone/locale, the permission and API matrices, an incognito heuristic, cross-site login-state, and so on) and shows the raw values plus an estimate of how identifiable you are.
A few deliberate choices:
- One static HTML file, no dependencies, no build step. Everything runs client-side and nothing is sent, with one opt-out exception: IP geolocation, which calls a public API. I didn't want a privacy tool that phones home.
- The "identifiability" number is an honest model, not a measurement. It sums published per-signal entropy (Panopticlick / AmIUnique / Cover Your Tracks), discounts signals your browser masks, and caps at the ~33 bits needed to single out one person on Earth. A no-server tool can't compute true rarity against a live population, so I label it an estimate instead of pretending. For real population numbers, Cover Your Tracks and AmIUnique have the datasets.
- There's a companion guide on lowering your fingerprint, with the caveat that uniqueness isn't privacy: blending into a big crowd (Tor at its default size) beats a bespoke hardened setup that makes you the only one who looks like that.
Source (MIT): https://github.com/HotStartLabs/glassbox
I'd genuinely like to know which vectors I'm missing, especially from the anti-fraud / detection side.
Comment · 2 months ago
https://p2ppoker.com/#how - I will opensource it soon just need some time to write it up
Comment · 2 months ago
Does anyone know a way to do this for a computer? I built a p2ppoker website the protects the shuffle from the server but I would like to blank the cards on screenshots to prevent huds and AIs from making the game unplayable.