Sentinel AI

Explainable AI for Counter-Strike 2 Match Intelligence

Analyze CS2 demos, reconstruct player behavior, generate explainable evidence and detect statistical anomalies using modern behavioral analytics.

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Overview

Sentinel AI is an open-source behavioral analysis platform for Counter-Strike 2.

Unlike traditional anti-cheat systems, Sentinel never injects into the game, never reads process memory and never interferes with gameplay.

Instead it reconstructs an entire match from a demo file and performs explainable statistical analysis of player behavior.

The result is a transparent report describing why specific actions appear unusual instead of producing an opaque "cheater / not cheater" verdict.

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Philosophy

Sentinel is not another anti-cheat.

It is a behavioral intelligence platform.

CS2 Demo
      │
      ▼
World Reconstruction
      │
      ▼
Feature Extraction
      │
      ▼
Behavior Analysis
      │
      ▼
Evidence Engine
      │
      ▼
Explainable Report

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Features

Source 2 Demo Support

• Source 2 parsing
• zstd compressed demos
• entity tracking
• round reconstruction
• event extraction

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World Reconstruction

Sentinel rebuilds the entire match state.

✔ Players

✔ Teams

✔ Weapons

✔ Tick timeline

✔ Round information

✔ Event graph

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Feature Extraction

Current implementation computes dozens of behavioral metrics including:

• Aim Velocity
• Hidden Tracking
• Rotation Justification
• Information Availability
• Solo Playstyle Index
• Team Proximity
• Trade Participation
• Utility Support
• Decision Timing
• Movement Statistics

Feature vectors are generated for every player across the entire match.

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Explainable AI

Instead of:

Player is cheating

Sentinel produces:

Round 18

Hidden Tracking

Visibility:
No

Audio:
No

Radar:
No

Tracking Duration:
1.42 seconds

Confidence:
92%

Every anomaly is backed by evidence.

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Pipeline

Source2 Demo
      │
      ▼
Demo Parser
      │
      ▼
Entity Tracking
      │
      ▼
Event Extraction
      │
      ▼
World Reconstruction
      │
      ▼
Feature Extraction
      │
      ▼
Bayesian Analysis
      │
      ▼
Evidence Engine
      │
      ▼
HTML / JSON Report

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Current Capabilities

✔ Source2 demo parsing

✔ Event extraction

✔ World reconstruction

✔ Feature engine

✔ Bayesian scoring

✔ Evidence generation

✔ HTML reports

✔ JSON reports

✔ CLI

✔ Dataset calibration

✔ Golden testing

✔ Statistical models

✔ Ensemble models

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Analysis Example

Match

Duration:
40 minutes

Ticks:
156,422

Players:
10

Events:
5,354

Feature vectors:
87,990

Evidence:
329/player

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Player example

SV4RiC

Aim
0.119

Movement
0.192

Wall
0.369

Overall
0.225

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Report

Sentinel generates

• HTML Report
• JSON Report

The HTML report includes

• score visualization
• category breakdown
• evidence
• player comparison
• anomaly summaries

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Repository Structure

sentinel/

crates/

    sentinel-core

    sentinel-demo

    sentinel-events

    sentinel-world

    sentinel-map

    sentinel-geometry

    sentinel-visibility

    sentinel-features

    sentinel-analysis

    sentinel-evidence

    sentinel-report

    sentinel-cli

    sentinel-ui

datasets/

docs/

examples/

tests/

assets/

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Installation

Clone

git clone https://github.com/YOUR_NAME/sentinel.git

cd sentinel

Build

cargo build --release

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CLI

Analyze

sentinel analyze match.dem

Calibration

sentinel calibrate calibration.json

Statistics

sentinel stats vectors.json

Verification

sentinel verify

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Output

reports/

match.html

match.json

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Design Principles

Sentinel follows six core principles.

Deterministic

Same input.

Same output.

Always.

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Explainable

Every score must have evidence.

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Modular

Every subsystem is an independent Rust crate.

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Testable

Golden tests

Regression tests

Calibration datasets

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Reproducible

Results can be reproduced across machines.

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Research Friendly

Designed for experimentation and statistical validation.

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Performance

Typical Premier Match

Ticks

156,000+

Players

10

Events

5,000+

Feature vectors

80,000+

Analysis

<10 seconds

(depending on hardware)

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Roadmap

Phase 1

Core Architecture

✅

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Phase 2

Source2 Integration

✅

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Phase 3

Behavior Analysis

✅

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Phase 4

Evidence Engine

✅

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Phase 5

Calibration

✅

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Phase 6

Visibility Engine

🚧

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Phase 7

Interactive Replay Viewer

🚧

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Phase 8

Machine Learning Validation

🚧

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Why Sentinel?

Traditional anti-cheats answer:

Is there a cheat running?

Sentinel asks:

Does this player's behavior statistically deviate from legitimate gameplay?

That distinction enables transparent, reproducible, and explainable analysis.

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Disclaimer

Sentinel is a research and analytics platform.

It does not:

• inject into Counter-Strike 2
• modify gameplay
• bypass Valve Anti-Cheat
• inspect process memory

Anomaly scores are statistical indicators intended to assist analysis. They are not definitive proof of cheating.

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Contributing

Contributions are welcome.

Please read

• CONTRIBUTING.md
• CODE_OF_CONDUCT.md

before opening a Pull Request.

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License

MIT License

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Acknowledgements

Valve

Rust Community

Open Source Contributors

Counter-Strike Community

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Built with Rust.

Designed for explainable behavioral intelligence.