🔒 This project aims to develop an open-source Security Information and Event Management (SIEM) solution to collect, analyze, and correlate security event data from multiple sources.
🔒 The goal is to provide enhanced threat detection, incident response, and improve overall security posture.
🔒 You'll be using Splunk Enterprise, Splunk Universal Forwarder, Nmap, and Docker to implement a robust SIEM solution.
🔒 This project offers flexible components, thorough documentation, and user-friendly interfaces for both beginner and advanced security professionals.
🔹 Collects and ingests log data from multiple sources (servers, network devices, applications) using Splunk Universal Forwarder.
🔹 Correlates security event data and identifies potential threats using Splunk Enterprise.
🔹 Implements real-time monitoring and alerting based on defined SIEM rules.
🔹 Designed for both scalability and flexibility, making it adaptable to various environments.
🔹 Includes the use of Nmap with Docker to perform credential scanning tests, simulating an attacker attempting to access sensitive data.
🔹 Linux
🔹 Ubuntu (for deploying SIEM systems)
🔹 Splunk Enterprise (for log ingestion, analysis, and correlation)
🔹 Splunk Universal Forwarder (for remote log forwarding)
🔹 Programming Language: Python
🔹 Log Management Best Practices: Effective log organization, filtering, and event correlation
🔹 Security Best Practices: SIEM configuration, alerting, and event correlation
🔹 Nmap with Docker: Used to test and simulate credential scans as part of the vulnerability assessment for the SIEM system.
🔹 PREREQUISITES 🔹
🔹 A working Linux or Ubuntu system.
🔹 Splunk Enterprise and Splunk Universal Forwarder installed.
🔹 Basic understanding of network protocols and log management.
🔹 Nmap and Docker installed for testing credential scan simulations.
Steps: ➡️❗ Click Here To View Detailed Visual Steps ❗⬅️
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Set up Splunk Enterprise on your central server.
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Install Splunk Universal Forwarder on remote systems to send logs to your Splunk server.
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Configure data inputs to collect logs from various sources (network devices, applications, servers).
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Develop custom event correlation rules for identifying potential threats.
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Implement real-time alerting to notify of suspicious activities or anomalies.
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Test your SIEM system by simulating a credential scan using Nmap with Docker.
🔹 Building a custom SIEM solution with Splunk Enterprise.
🔹 Effective use of log data and network analysis tools for threat detection.
🔹 Applying SIEM best practices for system security, alerting, and data correlation.
🔹 Using Nmap with Docker to simulate real-world attacks like credential scanning and analyzing the results in the SIEM system.
🔹 Use a network anaylsis tool for further investigation.
🔹 Add support for additional data sources (e.g., cloud services, endpoints).
🔹 Implement machine learning algorithms to improve threat detection accuracy.
🔹 Expand the system to handle large-scale enterprise environments.
🔹 Integrate with external security tools for advanced monitoring and reporting.