Detecting AI cheats has been one of FACEIT's biggest focuses in 2026.
Recently, several of our anti-cheat developers, data scientists, and staff spent two days at the
@Google London office, building on that work alongside their engineers.
We collaborated with Google's team to evolve two of our current approaches:
1. Training models on past matches where our anti-cheat confirmed players cheated, learning to recognize similar patterns elsewhere.
2. Modelling what normal play looks like to flag behavior that sits outside it.
FACEIT processes millions of CS2 matches a month, with years of high-level gameplay on record. That scale creates a foundation our detection models can learn from.
Before these techniques can be applied to the full FACEIT player base, there is still more work to do. We're running new behavioral analysis in the next months, building an automated pipeline of confirmed-cheating data for our models to learn from, and improving how we capture more supporting data for the context of kills.
We will continue to collaborate with Google’s engineers and share more information as these detection methods are rolled out across the platform.