flowchart TD
    subgraph Capture & Ingestion
        A[Network Interface / Packet Simulator] -->|Raw Traffic Events| B(Lightweight Event Bus)
        B -->|Packet Stream| C[Flow Aggregation Engine]
    end

    subgraph Deep Learning Inference
        C -->|Aggregated Telemetry Vectors| D[PyTorch TrafficAutoencoder]
        D -->|MSE Reconstruction Loss| E{Threshold Evaluation}
    end

    subgraph Alert Dispatch
        E -->|No Anomaly| F[Status: Optimal]
        E -->|Anomaly Detected| G[FastAPI BackgroundTasks]
        G -->|Save Event| H[(SQLite Datastore)]
        G -->|Broadcast WebSocket| I[HTML Live Dashboard]
        G -->|Dispatch Webhooks| J[Slack / Discord / Custom Webhook]
        G -->|Dispatch SMTP| K[Email Alerting]
    end

    style D fill:#EE4C2C,stroke:#fff,stroke-width:2px,color:#fff
    style I fill:#005571,stroke:#fff,stroke-width:2px,color:#fff
    style G fill:#00bf8f,stroke:#fff,stroke-width:2px,color:#fff

NetSentryx/
├── config/
│   ├── config.yaml          # System, dashboard, and alerting channel configurations
│   └── rules.yaml           # Threat detection thresholds and rule properties
├── src/
│   ├── alerts/
│   │   ├── ml_detection.py  # PyTorch TrafficAutoencoder & feature scaling
│   │   ├── manager.py       # Async alert dispatcher (Discord, Slack, Email)
│   │   └── detection.py     # Rule-based packet signature detection engine
│   ├── core/
│   │   ├── config_loader.py # Configuration loader utilities
│   │   ├── logger.py        # Database-integrated system logger
│   │   └── time_utils.py    # Timezone-aware timestamp utilities
│   ├── dashboard/
│   │   ├── templates/
│   │   │   └── index.html   # Live HTML5 Dashboard template
│   │   └── server.py        # FastAPI API Router and WebSocket broadcast controller
│   ├── database/
│   │   ├── manager.py       # SQLite connection & database actions
│   │   └── models.py        # SQLAlchemy schema definitions (Alerts, Logs, Flows)
│   ├── flows/
│   │   ├── capture.py       # Scapy packet sniffer thread
│   │   └── processor.py     # Flow aggregation and metric extractor
│   └── main.py              # Application entrypoint
└── main.py                  # Root script runner

# Clone the repository
git clone https://github.com/yourusername/netsentryx.git
cd netsentryx

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install requirements
pip install -r requirements.txt

# Discord Configuration
DISCORD_ENABLED=true
DISCORD_WEBHOOK_URL="https://discord.com/api/webhooks/your-webhook-id/your-webhook-token"

# Slack Configuration
SLACK_ENABLED=true
SLACK_WEBHOOK_URL="https://hooks.slack.com/services/YOUR_WORKSPACE_ID/YOUR_CHANNEL_ID/YOUR_SECRET_TOKEN"

# SMTP Email Configuration
SMTP_ENABLED=true
SMTP_SERVER="smtp.gmail.com"
SMTP_PORT=587
SMTP_USERNAME="[email protected]"
SMTP_PASSWORD="your-app-password"
SMTP_FROM_EMAIL="[email protected]"
SMTP_TO_EMAIL="[email protected]"

python main.py --simulate

python main.py

{
  "packet_count": 550,
  "byte_count": 850000,
  "flow_duration": 4.5,
  "syn_flag_ratio": 0.85,
  "port_entropy": 3.2,
  "byte_rate": 188888.8,
  "source_ip": "192.168.1.120",
  "dest_ip": "10.0.0.5",
  "protocol": "TCP"
}

{
  "status": "NORMAL",
  "threat_level": "low",
  "anomaly_score": 0.3083,
  "threshold": 2.1319
}

{
  "status": "ANOMALOUS",
  "threat_level": "critical",
  "anomaly_score": 117999.03,
  "threshold": 2.1319,
  "alert": {
    "id": 12,
    "timestamp": "2026-08-05T14:13:31.373Z",
    "rule_id": "ml_autoencoder_anomaly",
    "rule_name": "ML Autoencoder Anomaly",
    "source_ip": "192.168.1.120",
    "severity": "critical",
    "description": "Deep autoencoder reconstruction error exceeded anomaly threshold (score: 117999.0300, threshold: 2.1320).",
    "metrics": { ... }
  }
}