https://github.com/dikayx/elk-siem
A lightweight SIEM solution using the ELK stack, Docker, Winlogbeat and Sysmon for efficient log collection and analysis.
https://github.com/dikayx/elk-siem
docker elk siem sysmon windows winlogbeat
Last synced: 6 months ago
JSON representation
A lightweight SIEM solution using the ELK stack, Docker, Winlogbeat and Sysmon for efficient log collection and analysis.
- Host: GitHub
- URL: https://github.com/dikayx/elk-siem
- Owner: dikayx
- License: mit
- Archived: true
- Created: 2024-10-10T11:34:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-02T13:42:36.000Z (over 1 year ago)
- Last Synced: 2025-02-26T05:21:09.742Z (about 1 year ago)
- Topics: docker, elk, siem, sysmon, windows, winlogbeat
- Language: Shell
- Homepage:
- Size: 1010 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# elk-siem





This project is a simple ELK stack-based SIEM (_Security Information and Event Management_) system for Windows endpoints. It is designed to collect, parse, and visualize Windows endpoint logs in a centralized manner by utilizing Sysmon and Winlogbeat.

## Architecture
The overall architecture is based on the ELK stack, which consists of Elasticsearch, Logstash, and Kibana. It uses **[Beats](https://www.elastic.co/beats)** as a data shipper to collect logs from several endpoints. In this case, **[Winlogbeat](https://www.elastic.co/beats/winlogbeat)** is used to collect Windows event logs.
> _On Linux, you can use **[Filebeat](https://www.elastic.co/beats/filebeat)** or **[Metricbeat](https://www.elastic.co/beats/metricbeat)** to collect logs and metrics from the operating system and services. For MacOS, **[Auditbeat](https://www.elastic.co/beats/auditbeat)** is available to collect audit events._

- Via **Winlogbeat**, relay gathers activity information from **sysmon** on the Windows endpoint to **Logstash** on ELK server.
- **Logstash** reads, parses, transforms, and relays the data to **Elasticsearch**.
- **Kibana** searches and visualizes the information from **Elasticsearch**.
## Getting Started
This project is designed to be used with [Docker](https://www.docker.com/). To get started, clone this repository and follow the instructions in the [installation guide](./_guides/INSTALLATION.md).
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Inspired from
- https://github.com/KnightChaser/KnightChaser
- https://github.com/deviantony/docker-elk