AI Cybersecurity Assistant

Real-time threat detection system using machine learning to identify and neutralize malware patterns before they execute.

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Project Overview

AI Cybersecurity Assistant Architecture

Real-Time Threat Detection

Our AI-driven system analyzes network traffic, file behavior, and process activity to detect potential threats with 99.8% accuracy.

  • Autonomous malware response with sandboxing capabilities
  • Multi-platform support for Windows, macOS, and Linux
  • Distributed threat intelligence network with global malware database

Core Features

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Adaptive Monitoring

Continuously monitors network activity, file behavior, and process execution with anomaly detection powered by deep learning.

Instant Response

Quarantines suspicious activity and automatically generates containment strategies within sub-seconds of threat identification.

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Behavioral Modeling

Uses behavioral biometrics to distinguish between normal system activity and potential malicious operations.

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Global Intelligence

Contributes to and receives updates from a decentralized network of threat detection nodes worldwide.

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Privacy-Preserving

All local system analysis remains on-device unless users explicitly opt-into threat intelligence sharing.

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Intelligent Reporting

Generates human-readable threat reports with actionable recommendations for system hardening.

Live Demo

This interactive demo shows the AI detecting a simulated malware attack and automatically isolating the threat.

Built With

Python

Core machine learning models using PyTorch and TensorFlow

Flask

Local threat detection service with API endpoints

MongoDB

Threat intelligence database with real-time updates

React

Dashboard UI with real-time threat visualization

Ready to Get Secure?

Join thousands of users keeping their systems protected from zero-day threats.

🔐 Download Free Version

Enterprise features available with paid subscription