This is a project for a browser fingerprinting technique that can track users not only within a single browser but also across different browsers on the same machine.
GPL-3.0 License
Author: Yinzhi Cao, Song Li, Erik Wijmans
Group: System Security Lab in Johns Hopkins University
Website: http://uniquemachine.org
Paper: Paper
The master
branch is used for testing purposes only. If you want to deploy it and collect browser fingerprints, please visit the aws_deploy branch.
Related repo: https://github.com/Song-Li/LanguageDetector Used to detect supported languages
This is a project for a browser fingerprinting technique that can track users not only within a single browser but also across different browsers on the same machine.
Specifically, our approach utilizes many novel OS and hardware level features, such as those from graphics cards, CPU, and installed writing scripts (Implementing). We extract these features by asking browsers to perform tasks that rely on corresponding OS and hardware functionalities.
In this project, we have a client side, web-based application, and a backend flask server file. The server side is written in Python 2.
YOURSERVER
text at Line 286 of the ./client/fingerprint/js/details.js
file to your server address.YOURSERVER
text at Line 2 of the ./client/fingerprint/js/toServer.js
file to your server address.python -m http.server 9876
(for python 3) or python -m SimpleHTTPServer 9876
(for python 2)pip install -r requirements.txt
in the root dir of the project folderpython flask/server.py
After you deployed the client side and the server side, you can start to play with it by visiting localhost:9876
The whole client part is JS based in "client" dir. Some of the modules are generated from C or coffee. Here is a list of usful description of dirs in "client":
The server part is writen in python. Using apache2 and flask as the framework.