https://github.com/alexgoodison/danphobic

AI-powered NGINX log analysis dashboard with anomaly detection (Winner of UCC ACM Hackathon '25) 🏆
https://github.com/alexgoodison/danphobic

fastapi gemini nextjs nginx python

Last synced: 11 months ago
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AI-powered NGINX log analysis dashboard with anomaly detection (Winner of UCC ACM Hackathon '25) 🏆

• Host: GitHub
• URL: https://github.com/alexgoodison/danphobic
• Owner: alexgoodison
• Created: 2025-05-17T09:02:08.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-03T20:48:53.000Z (about 1 year ago)
• Last Synced: 2025-06-04T05:18:24.367Z (about 1 year ago)
• Topics: fastapi, gemini, nextjs, nginx, python
• Language: TypeScript
• Homepage:
• Size: 97.1 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Danphobic - NGINX Log Analysis Dashboard 🏆

**Winner of the UCC ACM Hackathon sponsored by NGINX**

Created by Alex Goodison & Suneet Mahajan.

Danphobic is a powerful web-based dashboard for analyzing NGINX access logs. It provides insights into web server traffic patterns, detects anomalies, and helps identify potential security threats through advanced log analysis.

## 🎥 Demo

[![Danphobic Demo](https://img.youtube.com/vi/aNV8Q0hqLG8/maxresdefault.jpg)](https://www.youtube.com/watch?v=aNV8Q0hqLG8)

Click thumbail above to [watch on Youtube](https://www.youtube.com/watch?v=aNV8Q0hqLG8)

## 🚀 Features

- **Interactive Dashboard**: Clean, modern interface for visualising log data

- **AI-Powered Analysis**: Leverages Google's Gemini LLM for intelligent log querying and analysis

- **Anomaly Detection**: Identifies suspicious patterns including:

  - High-frequency IP requests

  - Suspicious user agents

  - Sensitive endpoint access attempts

  - Burst requests

  - Error rate spikes

  - Bot vs. human traffic analysis

- **Geographic Visualisation**: Map view of request origins

- **Advanced Analytics**:

  - Request patterns over time

  - Status code distribution

  - HTTP method analysis

  - Most accessed paths

  - Error path analysis

  - Traffic pattern insights

## 🛠️ Tech Stack

- **Frontend**: Next.js with modern UI components

- **Backend**: FastAPI (Python)

- **Search Engine**: Elasticsearch for efficient log storage and querying

- **AI Integration**: Google Gemini LLM for intelligent log analysis

- **Data Processing**: Custom Python parser for NGINX log analysis

## 🎯 Problem Statement

The project addresses the challenge of making sense of NGINX access logs by:

1. Reading and parsing NGINX access logs

2. Identifying unusual patterns and potential security threats

3. Presenting insights through an intuitive dashboard interface

## 🏆 Achievement

This project won the UCC ACM Hackathon sponsored by NGINX, demonstrating excellence in:

- Technical implementation

- User experience design

- Problem-solving approach

- Innovation in log analysis

## 🔍 Key Features in Detail

### Anomaly Detection

- Identifies blacklisted IPs

- Detects unusual request patterns

- Monitors sensitive endpoint access

- Analyses user agent patterns

- Tracks error rates and spikes

### Data Visualisation

- Interactive charts and graphs

- Geographic request distribution

- Real-time traffic monitoring

- Error pattern analysis

- Traffic pattern insights

### AI Integration

- Natural language querying of logs

- Intelligent pattern recognition

- Automated anomaly detection

- Smart insights generation