🛡️ Advanced Threat Intelligence Platform 🛡️

📝 Overview

Welcome to the Advanced Threat Intelligence Platform! This platform is designed to analyze and classify real-time threats based on various intelligence feeds, IP reputation, and malware characteristics. It includes the following features:

• Real-Time Threat Feed
• IP Reputation Analysis
• Malware Classification
• Threat Intelligence Dashboard

🛠️ Features

• Real-Time Threat Feed: Fetches live threat data from an external feed URL.
• IP Reputation Analysis: Analyzes IP addresses to determine their reputation (safe or malicious).
• Malware Classification: Classifies files as either malware or safe based on predefined features.
• Threat Intelligence Dashboard: Visualizes threat trends such as phishing, ransomware, and nation-state attacks.

Prerequisites

Ensure the following dependencies are installed:

• Python 3.8 or higher
• pip package manager

🤖 Installation

1. Clone the repository:

   git clone https://github.com/yourusername/Advanced-Threat-Intelligence-Platform.git
   cd Advanced-Threat-Intelligence-Platform
   

2. Create a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate   # On Windows, use `venv\Scripts\activate`
   

3. Install required libraries:

   pip install -r requirements.txt
   

4. Download or train the machine learning models (malware_model.pkl, ip_reputation_model.pkl) and place them in the same directory as the script.

🧑‍💻 Usage

Launch the Streamlit app:

• Run the following command to start the application:

  streamlit run app.py
  

💻 Features in Detail ⚡

1. Real-Time Threat Feed

• Fetches real-time threat intelligence data from an external feed URL (JSON format). The data can be visualized and analyzed within the platform.

2. IP Reputation Analysis

• Enter an IP address to analyze its reputation. The app uses a machine learning model to predict whether the IP is safe or malicious and assigns a threat score.

3. Malware Classification

• Enter comma-separated file features for classification. The app uses a pre-trained machine learning model to predict whether the file is malware or safe.

4. Threat Intelligence Dashboard

• The dashboard visualizes various threat categories, such as phishing campaigns, ransomware activity, and nation-state attacks. The data is presented in line charts and bar charts for easy analysis.

🤝 Contributing

• We welcome contributions! If you would like to improve or add new features to this project, please fork the repository and submit a pull request.

Connect with Me 🌐

• 📧 Email
• 💼 LinkedIn