{"repo":"keusuanl-sec/WebApp-Log-Analysis","free":true,"listed":false,"github":"https://github.com/keusuanl-sec/WebApp-Log-Analysis","clone":"git clone https://github.com/keusuanl-sec/WebApp-Log-Analysis.git","description":"This project uses the ELK Stack (Elasticsearch, Logstash, and Kibana) to analyze web application logs. It tracks user activities such as logins, registrations, password resets, and failed login attempts. Interactive dashboards built using Kibana provide insights and detect anomalies.","language":"JavaScript","stars":12,"topics":["anomalies","dashboards","elasticsearch","elk","elk-stack","logstash","web-app","web-app-log-analysis","web-app-logging","kibrana"],"license":"MIT","category":"dashboards-admin","readme_excerpt":"Log Analysis with ELK Stack for Web Application Monitoring Description This project uses the ELK Stack (Elasticsearch, Logstash, and Kibana) to analyze web application logs. It tracks user activities such as logins, registrations, password resets, and failed login attempts. Interactive dashboards built using Kibana provide insights and detect anomalies. Key Features - Real-time log ingestion and parsing using Logstash. - Visualization of user activity trends and failed logins. - Interactive dashboards for event-specific analysis. - Randomized log generation script for testing. Technologies Used - Elasticsearch : For storing and indexing logs. - Logstash : For log parsing and transformation. - Kibana : For visualizing and analyzing logs. - Flask/Express.js : Web application generating logs. - PowerShell : Script for generating randomized web requests. Installation and Setup 1. Environment Setup - Install Elasticsearch, Logstash, and Kibana. - Install Python (for Flask) or Node.js (for Express.js). 2. Configuration - Set up logstash.conf for parsing logs and sending them to Elasticsearch. - Ensure the webapp.log file path is correctly set in the Logstash configuration. - Import the Kibana dashboard ( .ndjson file). 3. Running the Project 1. Start Elasticsearch : 2. Run Logstash : 3. Start the Web Application : - For Flask: - For Express.js: 4. Access Kibana : - Open http://localhost:5601 in your browser. Usage - Use the provided PowerShell script to generate random logs: - View","default_branch":null,"files":null,"tree":[],"storefront":"/r/keusuanl-sec","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/keusuanl-sec/WebApp-Log-Analysis/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}