yviler/cs2-cheat-detection

Detecting aimbot behavior in CS2 using neural networks trained on engineered aim data from demo files.

24
/ 100
Experimental

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.

esports-integrity game-moderation anti-cheat CS2-analysis competitive-gaming
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 7 / 25
Community 9 / 25

How are scores calculated?

Stars

16

Forks

2

Language

Jupyter Notebook

License

Last pushed

Jun 30, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yviler/cs2-cheat-detection"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.