yviler/cs2-cheat-detection
Detecting aimbot behavior in CS2 using neural networks trained on engineered aim data from demo files.
This system helps competitive Counter-Strike 2 players, league organizers, and anti-cheat developers automatically identify potential aimbot users in match recordings. You provide CS2 demo files (.dem), and the system analyzes player movements and aiming patterns to output a probability that a player segment exhibits cheating behavior. This is for anyone needing to verify fair play in CS2 matches.
No commits in the last 6 months.
Use this if you need to systematically analyze CS2 match demos to flag suspicious aim behavior without manually reviewing every moment.
Not ideal if you need a real-time, in-game anti-cheat solution that prevents cheaters from playing, as this analyzes recorded demo files.
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Jupyter Notebook
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Last pushed
Jun 30, 2025
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