CS2 player builds behavioral biometrics system to make bans follow cheaters, not accounts

A master's thesis at the Norwegian University of Science and Technology developed a system that identifies CS2 players by their mouse and keyboard behavior using existing match demos. The mouse fingerprint identified the correct player 100% of the time across 1,000+ players, while the keyboard fingerprint hit 98%.

• System builds a "CS-fingerprint" from demos CS2 already records
• Mouse fingerprint hit 100% accuracy, keyboard fingerprint 98%
• Method surfaced unknown smurfs and all 13 known same-player account pairs
• Researcher suggests using it alongside VAC and Trust Factor, not for auto-bans