Inspiration

We wanted to create a tool that can automatically detect malware in files, helping users quickly identify threats without manually scanning or relying on multiple tools.

What it does

Scans uploaded files for potential malware, classifies files as safe or malicious, and provides visualizations for detected malware trends.

Offers a streamlined interface via a web app

How we built it

Frameworks: Streamlit for UI, Pandas for data handling, Plotly for charts

AI/ML: Custom model for malware detection, trained on labeled datasets

Version Control: Git & GitHub

AI-powered features including an interactive Chat Bot

Challenges we ran into

Integrating the AI model with the Streamlit frontend and ensuring accurate predictions while keeping inference fast.

Setting up the AI Chat Bot and finding an appropriate API to host it. We preferred a free source over subscription-based models.

Accomplishments that we're proud of

Full end-to-end AI malware detection pipeline, setting up an interactive web app with live charts, and successfully trained and deployed a model with high accuracy.

What we learned

How to integrate AI/ML models with web applications, the importance of clean Git workflow and deployment practices and techniques for handling large and messy datasets. Gained additional front-end development skills, including UI/UX design.

What's next for AI Malware Detector

Expanding dataset to cover more malware types, optimizing the model for real-time scanning, adding user authentication and reporting features, integrating notifications for detected threats.