This is FULLY AI made other than the two gameplay videos it found and downloaded (yt-dlp), the music it made via scripting (manually writing wav, no encoder, no library, which is nuts to me), the editing it scripted (remotion). All graphics (svgs, html css), 3d objects (via blender mcp), the menu, etc, is AI. Everything other than the actual csgo footage is ALL coded by it rendered to a video.

is it good? no, but i think its so goofy that its funny

The Akamai solver supports V2 & V3 sensors and the pixel challenge.

It doesn’t use a browser, however it runs a minimal V8 sandbox.

NodeJS: https://proofofbots.github.io/web-re-toolkit/packages/node/

Python: https://proofofbots.github.io/web-re-toolkit/packages/python/

It is a massive monorepo so just to clarify: The web-re-toolkit itself is a project that provides tools for web reverse engineering, Akamai (and other) solvers are just a small part that use it.

The NPM & PyPI packages are just wrappers for the client built with WRE (github.com/proofofbots/web-re-toolkit) so they include a binary which contains the actual sandbox and solver. All of it is open sourced, so feel free to compile it yourself.

Akamai client (solver) source code is here: github.com/proofofbots/web-re-toolkit/tree/main/clients/akamai

Akamai client docs: https://proofofbots.github.io/web-re-toolkit/guides/akamai/

It does not use host's fingerprint, rather you provide the fingerprint profile you want akamai to use. By default it uses a Mac’s fingerprint.

This was a weekend project put together largerly with AI. There are many things I’d like to add and improve, but I do not have the time to work on this project much more than this. The docs, packages, etc are an absolute mess, I'd love if someone could contribute in cleaning them up!

I’ll be releasing Kasada’s solver too later today.

I’ve not had the chance to to throughly test it on more than a few sites, I am hoping the community (you) will help me with that. Whatever issues you run into, please make a issue in GitHub or send a message in the Discord and provide the logs + code.

Discord: https://discord.gg/nbBePnsa9

https://preview.redd.it/laqfzgt4aejh1.png?width=1080&format=png&auto=webp&s=dbaaf19c47824d24eee7ece869ec7e703a03404e

It pulls a live FPJS Pro build and turns it into clean code you can run locally, every collector intact, so a new build means rerunning the pipeline instead of reversing it again by hand.

What's in the repo:

• All 143 signals (telemetry read from ur browser, all documented)
• Every collector as its own file
• What visitor_id is actually a function of
• A live explorer that runs the collectors against your own browser so you can diff a patched environment against a stock one.

Repo: github.com/proofofbots/fingerprint-pro-internals

Docs: proofofbots.github.io/fingerprint-pro-internals/

Signal explorer

proofofbots.github.io/fingerprint-pro-internals/explorer.html

It runs entirely in your browser. No backend of mine, no call to fpjs, nothing leaves the page. It's built on the output of the lift and deobfuscation step, so what runs there is the actual collector code from the bundle rather than a reimplementation. Open it and you get every data point side by side: what the signal is and why it's collected in plain English, next to the exact value your own browser hands over for it.

Happy to answer questions on any specific detection.

I am looking forward to the next target, so if anyone has ideas on what vendor could be interesting let me know!

Before anyone calls AI slop: yes, I use LLMs, they're genuinely useful for reverse engineering. But this isn't one build hand-decoded into a writeup. It's the toolchain that does it. Point it at a live fpjs build and it deobfuscates, lifts, and emits a cleaned version you can run without their servers, plus the generated documentation for what it found.

https://preview.redd.it/pjb44j4x9ejh1.png?width=1080&format=png&auto=webp&s=1d458df296a4378ca3f67c935e96ef976398892f

It pulls a live FPJS Pro build and turns it into clean code you can run locally, every collector intact, so a new build means rerunning the pipeline instead of reversing it again by hand.

What's in the repo:

• All 143 signals (telemetry read from ur browser, all documented)
• Every collector as its own file
• What visitor_id is actually a function of
• A live explorer that runs the collectors against your own browser so you can diff a patched environment against a stock one.

Repo: github.com/proofofbots/fingerprint-pro-internals

Docs: proofofbots.github.io/fingerprint-pro-internals/

Signal explorer

proofofbots.github.io/fingerprint-pro-internals/explorer.html

It runs entirely in your browser. No backend of mine, no call to fpjs, nothing leaves the page. It's built on the output of the lift and deobfuscation step, so what runs there is the actual collector code from the bundle rather than a reimplementation. Open it and you get every data point side by side: what the signal is and why it's collected in plain English, next to the exact value your own browser hands over for it.

Happy to answer questions on any specific detection.

I am looking forward to the next target, so if anyone has ideas on what vendor could be interesting let me know!

Before anyone calls AI slop: yes, I use LLMs, they're genuinely useful for reverse engineering. But this isn't one build hand-decoded into a writeup. It's the toolchain that does it. Point it at a live fpjs build and it deobfuscates, lifts, and emits a cleaned version you can run without their servers, plus the generated documentation for what it found.

Wondering if anyone has bypassed this? It feels like no matter the setup I still get detected even with anti detect browsers

https://stealthscore.cc