Back to projects

Security systems / anti-cheat infrastructure

SentinelAC

AI-assisted anti-cheat and detection infrastructure for multiplayer game environments.

SentinelAC combines telemetry collection, heuristic detection, backend enforcement, and machine-learning experimentation through AI Internal-Cheat Detection (AIICD). The work spans client/server security assumptions, event pipelines, false-positive tradeoffs, and operator-facing review workflows.

Node 01

Game telemetry

Node 02

Detection services

Node 03

AIICD analysis

Node 04

Operator review

Distributed detection backend

AIICD machine-learning experiments

Operator review and moderation workflow

Tech Stack

TypeScriptNode.jsPythonLuaMongoDBDockerML pipelines

Engineering Challenges

Designing detection rules that catch abuse while respecting false-positive risk.

Coordinating telemetry, backend state, and enforcement paths across services.

Making security logic understandable enough for operators to trust.

Impact / Scale

Built as a serious security engineering project, not a toy demo: the system emphasizes detection infrastructure, reviewability, and scalable operations.

Screenshots / Video Slots

Detection dashboard screenshot

AIICD experiment capture

Operator review flow video