---

Fireshark - Threat Intelligence and Network Analytics Tool

Welcome to the Fireshark - Threat Intelligence and Network Analytics Tool! This project provides a powerful platform to analyze and interpret network flow data, identify potential threats, and gain actionable insights into malicious activities. By combining advanced analytics and AI-driven models, this tool enhances network security and promotes proactive monitoring.

---

Links

• Live Project: Fireshark Application
• GitHub Repository: Fireshark GitHub Repo
• Project Presentation (PPT): Fireshark PPT
• Project Report: Fireshark Report
• Demo Video: Fireshark Demo Video

---

About the Project

The Fireshark Tool is designed for individuals and organizations aiming to maintain robust network security and gain deeper insights into network activities. By integrating AI models, the tool offers real-time analysis and anomaly detection, enabling users to address potential risks before they escalate.

---

Features

1. Threat Lookup

• Assess the security of IP addresses, domain names, and subnets.
• Provides detailed results, including:
  • Threat Scores.
  • Malicious Activity Indicators.
  • Geographic Information.
  • Last Reported Incidents.
• Helps identify potential risks for informed decision-making.

2. AI-Powered Analytics

• Utilizes machine learning models to:
  • Analyze network flow data.
  • Detect anomalies and suspicious patterns.
  • Classify and forecast potential threats.
• Enhances proactive threat detection and network security.

3. Network Flow Visualization

• Visualizes network traffic patterns for easy interpretation.
• Provides insights into historical trends, helping identify anomalies or unusual behaviors over time.

4. Feedback Collection

• Includes a feedback system that:
  • Allows users to provide suggestions for improvement.
  • Ensures the platform evolves based on user needs and feedback.

---

How to Use

1. Access the live project via the provided link or run the tool locally using the GitHub repository.
2. Use the Threat Lookup feature to check IP addresses, domain names, or subnets.
3. Explore the Network Analytics page for detailed traffic visualizations and insights.
4. Provide feedback using the feedback form to help us improve the tool.

---

Technologies Used

• Programming Language: Python
• Framework: Streamlit
• AI Models: Integrated Machine Learning Models for Threat Detection
• Data Visualization: Libraries like Matplotlib and Seaborn for graphical insights

---

Contact Information

For further queries or contributions, please open an issue or reach out via the GitHub repository.

Contributors

Aditya Sharma

Sejal Kaur

Rajan Raj

Nikhil Yadav

---