SIEM Log Analysis Tool

A lightweight, event-driven Security Information and Event Management (SIEM) prototype designed to collect, normalize, and analyze Linux system logs with intelligent rule-based detection for security threats.

📋 Table of Contents

• Overview
• Key Features
• Security Capabilities
• System Architecture
• Requirements
• Installation
• Configuration
• Usage
• Supported Log Sources
• Detection Rules
• Performance
• Contributing
• License

🎯 Overview

This SIEM prototype provides enterprises with a lightweight alternative to traditional enterprise SIEM solutions. Built with TypeScript and Python, it offers real-time log collection, normalization, and threat detection specifically optimized for Linux environments. The tool implements event-driven architecture for efficient processing of high-volume security events.

Use Cases

• Incident Detection: Identify suspicious activities in real-time
• Compliance Monitoring: Track and audit system activities for regulatory requirements
• Threat Intelligence: Correlate events to identify attack patterns
• Operational Security: Monitor privileged access and system changes
• Network Security: Detect and alert on network-based attacks

🔒 Security Capabilities

1. Brute-Force Attack Detection

• Real-time monitoring of authentication failures
• Configurable threshold-based alerts
• Automatic IP reputation tracking
• Pattern recognition for distributed attack scenarios
• Timestamp-based correlation across multiple login attempts

2. Privilege Abuse Detection

• Tracks unauthorized sudo and su command execution
• Monitors user privilege escalation attempts
• Detects anomalous privilege usage patterns
• Alerts on privilege boundary violations
• User-to-privilege mapping analysis

3. Cron Misuse Detection

• Monitors cron job execution anomalies
• Detects unauthorized cron modifications
• Tracks suspicious cron-based command execution
• Identifies persistence mechanisms using cron jobs
• Timing-based anomaly detection for cron activities

4. Network Attack Detection

• Integration with Suricata IDS for signature-based detection
• Deep packet inspection capabilities
• Real-time network threat identification
• Protocol anomaly detection
• Malware traffic pattern recognition

5. Log Normalization

• Unified event format for heterogeneous log sources
• Standardized timestamp processing
• Field extraction and parsing
• Data enrichment and context addition
• Schema-based validation

6. Rule-Based Detection Engine

• Flexible, extensible detection rule framework
• Multi-step correlation rules
• Temporal and statistical analysis
• Custom alert routing and severity classification
• Rule versioning and audit trails

🏗️ System Architecture

┌─────────────────────────────────────────────┐
│      Log Sources                            │
│  ├─ Linux Authentication (auth.log)         │
│  ├─ System Logs (syslog)                    │
│  ├─ Network Detection (Suricata)            │
│  └─ Application Logs                        │
└────────────┬────────────────────────────────┘
             │
┌────────────▼────────────────────────────────┐
│      Log Collection & Ingestion             │
│  ├─ File Monitoring                         │
│  ├─ Real-time Parsing                       │
│  └─ Event Queuing                           │
└────────────┬────────────────────────────────┘
             │
┌────────────▼────────────────────────────────┐
│      Log Normalization Engine               │
│  ├─ Format Standardization                  │
│  ├─ Field Extraction                        │
│  ├─ Data Enrichment                         │
│  └─ Schema Validation                       │
└────────────┬────────────────────────────────┘
             │
┌────────────▼────────────────────────────────┐
│      Detection & Correlation Engine         │
│  ├─ Rule Evaluation                         │
│  ├─ Event Correlation                       │
│  ├─ Threshold Analysis                      │
│  └─ Alert Generation                        │
└────────────┬────────────────────────────────┘
             │
┌────────────▼────────────────────────────────┐
│      Alert & Response Management            │
│  ├─ Severity Classification                 │
│  ├─ Alert Routing                           │
│  ├─ Investigation UI                        │
│  └─ Response Actions                        │
└─────────────────────────────────────────────┘

📋 Requirements

System Requirements

• OS: Linux (Ubuntu 20.04+, CentOS 8+, or equivalent)
• CPU: 2+ cores
• RAM: 4GB minimum (8GB recommended)
• Disk: 20GB+ for log storage (depends on log volume)

Software Dependencies

• Python 3.8 or higher
• Node.js 16.0 or higher
• npm 8.0 or higher

Supported Log Sources

• Authentication Logs: /var/log/auth.log, /var/log/secure
• System Logs: /var/log/syslog, /var/log/messages
• IDS/IPS: Suricata EVE JSON output (optional)
• Custom Sources: Syslog protocol support

⚙️ Installation

1. Clone the Repository

git clone https://github.com/future1245/SIEM-log-analysis-tool.git
cd SIEM-log-analysis-tool

2. Create and Activate Virtual Environment

# Create Python virtual environment
python3 -m venv venv

# Activate virtual environment
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Python Dependencies

pip install -r requirements.txt

4. Install Frontend Dependencies

cd FRONT_END
npm install
cd ..

5. Verify Installation

# Check Python dependencies
pip list

# Check Node dependencies
cd FRONT_END && npm list && cd ..

🔧 Configuration

Main Configuration

The application automatically detects and processes logs from:

• /var/log/auth.log - Authentication events
• /var/log/syslog - System events
• Suricata EVE JSON (if enabled)

Custom Log Paths

Edit the respective processor files to configure custom log locations:

• auth_processor.py - Authentication log paths
• syslog_processor.py - System log paths
• suricata_processor.py - Suricata log paths

Rule Configuration

Detection rules are managed through the analyzer. See SIMULATION_GUIDE.md for detailed rule configuration examples.

🚀 Usage

Quick Start (Recommended)

After completing installation, start the entire application with a single command:

# Make the script executable (first time only)
chmod +x run.sh

# Start SIEM and frontend together
./run.sh

This will:

1. ✅ Activate the Python virtual environment
2. ✅ Start the backend analyzer
3. ✅ Start the frontend development server
4. ✅ Automatically open the dashboard in your browser at http://127.0.0.1:8080

Manual Startup (Advanced)

Terminal 1 - Start the backend analyzer:

source venv/bin/activate
python backend.py

Terminal 2 - Start the SIEM engine and frontend:

source venv/bin/activate
python main.py

The frontend will be available at http://127.0.0.1:8080

Running Individual Components

Run SIEM analyzer only:

source venv/bin/activate
python ULM.py

Run backend API only:

source venv/bin/activate
python backend.py

Run frontend development server only:

cd FRONT_END
npm run dev

View Dashboard

Once running, access the web dashboard:

http://127.0.0.1:8080

📊 Supported Log Sources

Source	File Path	Purpose
Auth Logs	/var/log/auth.log	Authentication events, login attempts, privilege escalation
System Logs	/var/log/syslog	System events, service changes, cron execution
Suricata	/var/log/suricata/eve.json	Network intrusion detection, protocol anomalies

🎯 Detection Rules

Pre-Built Detection Rules

1. Brute-Force Detection

• Monitors repeated authentication failures
• Configurable failure threshold
• IP-based and user-based correlation
• Automatic blocking recommendations

2. Privilege Escalation Detection

• Tracks sudo command execution with suspicious patterns
• Detects su usage anomalies
• Monitors privilege boundary violations
• Alerts on unauthorized privilege changes

3. Cron Abuse Detection

• Identifies unauthorized cron job creation
• Detects suspicious cron-based commands
• Monitors cron file modifications
• Tracks timing anomalies

4. Network Threat Detection

• Detects known attack signatures
• Identifies protocol violations
• Alerts on suspicious network patterns

📈 Performance

Benchmarks

• Log Ingestion: Up to 10,000 events per second
• Detection Latency: <500ms average
• Memory Footprint: 200-500MB (configurable)
• Storage: 1-2GB per day (depends on configuration)

Optimization Tips

1. Configure appropriate log retention policies
2. Enable only necessary log sources
3. Tune analyzer batch processing sizes
4. Use the run.sh script for optimal resource management

🛠️ Troubleshooting

Common Issues

Issue: Virtual environment not found

# Recreate the virtual environment
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Issue: Port 8080 already in use

# Kill the process using the port (Linux)
lsof -ti:8080 | xargs kill -9

Issue: Permission denied on run.sh

chmod +x run.sh
./run.sh

Issue: Frontend not starting

cd FRONT_END
npm install
npm run dev

📚 Technology Stack

Component	Technology
Backend	Python 3.8+
API Server	Python (Flask/FastAPI)
Frontend	Node.js, npm, Vite
UI Framework	TypeScript
Styling	CSS
SIEM Core	Python event processing
Integration	Suricata IDS/IPS

📖 Additional Resources

• Simulation & Testing: See SIMULATION_GUIDE.md for attack simulation scenarios
• Component Details:
  • ULM.py - Main SIEM analyzer
  • auth_processor.py - Authentication log analysis
  • syslog_processor.py - System log analysis
  • suricata_processor.py - Network threat detection
  • backend.py - REST API backend

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Guidelines

• Follow existing code style
• Test your changes thoroughly
• Update documentation
• Include security considerations

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

📞 Support

For issues, questions, or contributions:

• GitHub Issues: Create an issue
• Documentation: Check the markdown files in root directory
• Security Concerns: Please report privately to maintainers

🎓 Learn More

• SIEM Best Practices
• Linux Log Formats
• Suricata Documentation

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Last Updated: June 2026

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