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Security Monitoring Dashboard

Python-based cybersecurity monitoring and log analysis project designed to simulate a lightweight Security Operations Center (SOC) workflow for detecting suspicious activities, analyzing security logs, generating dashboard visualizations, and creating automated security reports.


Project Overview

The Security Monitoring Dashboard is a cybersecurity automation project developed using Python.

This project simulates a basic SOC (Security Operations Center) environment where system logs are analyzed to identify suspicious activities, classify event severity levels, estimate security risks, and generate automated monitoring reports.

The dashboard also creates graphical visualizations for better understanding of security events and threat patterns.

This project is suitable for:

  • Cybersecurity portfolio projects
  • SOC analyst practice
  • Threat detection learning
  • Log analysis automation
  • Security monitoring simulation
  • Detection engineering foundations
  • Python cybersecurity development

Features

  • Automated security log analysis
  • Severity-based event classification
  • Suspicious activity detection
  • Risk level estimation
  • Dashboard chart generation
  • Pie chart visualization
  • Automated security report generation
  • SOC-style monitoring workflow
  • Lightweight and beginner-friendly implementation
  • Screenshot documentation support

Severity Levels Detected

The system detects and analyzes the following security log severity levels:

  • INFO
  • WARNING
  • ERROR
  • FAILED

Technologies Used

  • Python
  • File Handling
  • String Processing
  • Log Parsing
  • Matplotlib
  • Cybersecurity Automation
  • Security Monitoring Concepts

Project Structure

Security_Monitoring_Dashboard/
│
├── screenshots/
│   ├── project_folder.png
│   ├── dashboard_chart_view.png
│   ├── pie_chart_view.png
│   ├── report_preview.png
│   └── terminal_execution.png
│
├── dashboard.py
├── .gitignore
├── security_logs.txt
├── dashboard_report.txt
├── dashboard_chart.png
├── pie_chart.png
├── requirements.txt
└── README.md

Installation

Install required libraries using:

pip install -r requirements.txt

Run the Project

Execute the project using:

python dashboard.py

Output

The project automatically generates:

dashboard_report.txt
dashboard_chart.png
pie_chart.png

Example Generated Report

=====================================
 Security Monitoring Dashboard Report
=====================================

Generated: 2026-05-29 07:43:57

Total Logs Analyzed: 12
Total Issues Detected: 9

Severity Count:
INFO: 3
WARNING: 3
ERROR: 4
FAILED: 2

Risk Summary:
Risk Level: HIGH

Example Detection Scenarios

The dashboard can identify security-related events such as:

  • Multiple failed login attempts
  • Unauthorized SSH access attempts
  • Malware detection alerts
  • High CPU usage warnings
  • Database connection failures
  • Remote login blocking events
  • Suspicious PowerShell activity
  • Abnormal system behavior indicators

Risk Level Classification

The project estimates overall system risk based on detected security events.

Possible classifications include:

  • LOW
  • MEDIUM
  • HIGH
  • CRITICAL

Dashboard Visualizations

The project generates visual analytics for security monitoring.

Dashboard Bar Chart

Displays the count of severity-based log events.

Pie Chart Visualization

Displays percentage distribution of detected security events.


Screenshots

Project screenshots are available inside the screenshots folder.

Included screenshots:

  • project_folder structure
  • Dashboard chart visualization
  • Pie chart visualization
  • Report preview
  • Terminal execution

Cybersecurity Concepts Demonstrated

This project demonstrates practical cybersecurity concepts including:

  • Security Operations Center (SOC) workflow
  • Security log monitoring
  • Threat detection basics
  • Event severity analysis
  • Incident reporting
  • Security automation
  • Detection engineering fundamentals

Future Improvements

Planned future enhancements:

  • Real-time log monitoring
  • Live dashboard interface
  • AI-powered threat explanation
  • Email alert integration
  • Threat scoring engine
  • SIEM integration simulation
  • CSV/XLSX export support
  • Flask/Django web dashboard
  • Machine learning anomaly detection

Version

Current Version: v1.0

v1.0 Features

  • Security log analysis
  • Severity counting
  • Risk estimation
  • Dashboard visualization
  • Automated report generation
  • Screenshot documentation

Author

Niher Halder
Cybersecurity Engineer | Threat Detection & Security Automation

About

A Python-based cybersecurity monitoring and log analysis dashboard designed to simulate Security Operations Center (SOC) workflows by detecting suspicious activities, classifying security events, generating automated reports, and visualizing log severity trends through charts and analytics.

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