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AI anticheat for Minecraft servers: neural networks catch KillAura, aim assist, triggerbot and reach. Paper, Spigot, Folia 1.16.5–1.21.

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GITHUB · launched Oct 27, 2026 · 32 upvotes (top 42%)

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Could you build this?

Partial The plugin shell, multi-version Paper/Spigot/Folia compatibility, and alerting are vibe-codeable. The hard part is training neural networks that separate cheat input from legitimate play, which requires large labeled datasets of human and cheating behavior.

What it would actually take: Build a server plugin (Java) that logs per-tick player telemetry (rotations, clicks, hit timing, reach) and streams it to an inference service running a trained model, with thresholds and moderator tooling on top. The hard piece is collecting and labeling a diverse dataset of real cheating and legitimate sessions across client versions, then tuning to keep false positives low. This needs ML engineering, data-labeling effort, and access to real players or cheat samples.

Competitors

Other products that read as similar to this one : 192 launches clear the similarity bar, closest 8 shown.

Attention rank: #72 of 193 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 327 days after the earliest competitor.

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