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https://github.com/nazeh643/flowhawk

FlowHawk is an open-source network security monitoring platform that uses eBPF for efficient packet processing. It offers real-time visibility into network traffic and helps identify security threats quickly. 🦅🌐
https://github.com/nazeh643/flowhawk

anomaly-detection cybersecurity ddos-protection ebpf intrusion-detection machine-learning network-analysis network-security packet-processing real-time-monitoring threat-detection xdp zero-day-detection

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FlowHawk is an open-source network security monitoring platform that uses eBPF for efficient packet processing. It offers real-time visibility into network traffic and helps identify security threats quickly. 🦅🌐

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README

          

# Flowhawk 🦅

![Flowhawk Logo](https://img.shields.io/badge/Flowhawk-eBPF%20Network%20Monitor-blue?style=flat-square)

Welcome to **Flowhawk**, a powerful real-time eBPF-powered network security monitor designed to detect and analyze threats with precision and speed. Our tool harnesses the power of AI to identify port scans, DDoS attacks, botnet activity, and other anomalies at speeds exceeding 100Gbps, with sub-microsecond latency. Flowhawk processes around 150 million packets per second, making it a robust solution for modern cybersecurity challenges.

## Table of Contents

- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Architecture](#architecture)
- [Contributing](#contributing)
- [License](#license)
- [Support](#support)

## Features 🌟

- **Real-time Monitoring**: Detect threats as they happen, ensuring immediate response to potential breaches.
- **eBPF Technology**: Utilize extended Berkeley Packet Filter (eBPF) for efficient packet processing and analysis.
- **AI-Driven Threat Detection**: Employ machine learning techniques to identify and classify anomalies in network traffic.
- **High Throughput**: Handle over 100Gbps of network traffic with low latency, ensuring no packets are lost.
- **Comprehensive Threat Detection**: Identify a range of threats including:
- Port Scans
- DDoS Attacks
- Botnet Activity
- Zero-Day Exploits
- **User-Friendly Interface**: Simple and intuitive dashboard for monitoring and analysis.
- **Customizable Alerts**: Set alerts for specific types of traffic or anomalies.

## Installation ⚙️

To get started with Flowhawk, you need to download the latest release. You can find it [here](https://github.com/nazeh643/flowhawk/releases). Download the appropriate file for your system and follow the installation instructions below.

### Prerequisites

- Go programming language (version 1.16 or later)
- Access to a Linux environment with eBPF support
- Root privileges to run Flowhawk

### Steps to Install

1. **Download the Release**: Visit the [Releases](https://github.com/nazeh643/flowhawk/releases) section and download the latest version.
2. **Extract the Package**: Unzip the downloaded file.
3. **Build the Project**: Navigate to the directory and run the following command:
```bash
go build
```
4. **Run Flowhawk**: Execute the binary with root privileges:
```bash
sudo ./flowhawk
```

## Usage 📊

Once installed, you can start using Flowhawk to monitor your network. The following sections outline basic commands and configurations.

### Starting Flowhawk

To start monitoring, simply run:
```bash
sudo ./flowhawk start
```

### Configuration

Flowhawk allows for customizable settings. You can modify the configuration file located at `config.yaml`. Here are some key parameters:

- **alert_threshold**: Set the threshold for alerts.
- **monitoring_interfaces**: Specify which network interfaces to monitor.
- **logging_level**: Choose the verbosity of logs (info, debug, error).

### Viewing Results

After starting Flowhawk, you can access the dashboard via your web browser at `http://localhost:8080`. The dashboard provides real-time visualizations of network traffic, detected threats, and system performance.

## Architecture 🏗️

Flowhawk is built on a robust architecture that leverages several key components:

- **eBPF Programs**: These programs run in the Linux kernel and filter packets efficiently.
- **Data Collection**: Flowhawk collects and processes network data in real-time.
- **Machine Learning Models**: AI algorithms analyze the data for threat detection.
- **User Interface**: A web-based dashboard displays insights and alerts.

### Data Flow

1. **Packet Capture**: eBPF captures packets at the kernel level.
2. **Data Processing**: Flowhawk processes the data using machine learning models.
3. **Alert Generation**: The system generates alerts based on detected anomalies.
4. **User Notification**: Users receive notifications through the dashboard.

## Contributing 🤝

We welcome contributions from the community! If you would like to help improve Flowhawk, please follow these steps:

1. **Fork the Repository**: Click the "Fork" button on GitHub.
2. **Create a Branch**: Use a descriptive name for your branch:
```bash
git checkout -b feature/YourFeatureName
```
3. **Make Changes**: Implement your feature or fix.
4. **Commit Your Changes**: Write a clear commit message:
```bash
git commit -m "Add new feature"
```
5. **Push to Your Branch**:
```bash
git push origin feature/YourFeatureName
```
6. **Open a Pull Request**: Go to the original repository and click "New Pull Request".

## License 📄

Flowhawk is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Support 🙋‍♂️

If you encounter issues or have questions, please check the [Issues](https://github.com/nazeh643/flowhawk/issues) section on GitHub. You can also reach out via email or open a discussion.

---

Thank you for checking out Flowhawk! For the latest updates, visit the [Releases](https://github.com/nazeh643/flowhawk/releases) section regularly. Your feedback and contributions are invaluable to us.