Tirreno: Open-source Free Fraud Prevention Platform

Tirreno is an open-source fraud prevention platform designed as a universal analytics tool to monitor online platforms, web applications, SaaS products, digital communities, mobile apps, intranets, and e-commerce websites.

🔗 GitHub: https://lnkd.in/dfsVR-fR
🔗 Demo: https://play.tirreno.com/

You Should Know:

1. Installation & Setup

To deploy Tirreno locally, follow these steps:

Prerequisites:

Docker installed
Git for cloning the repository

 Clone the repository 
git clone https://github.com/tirreno/fraud-prevention-platform.git

Navigate to the project directory 
cd fraud-prevention-platform

Start the Docker containers 
docker-compose up -d

Verify Installation:

 Check running containers 
docker ps

Access the dashboard 
curl http://localhost:3000

2. Key Features & Commands

Tirreno provides fraud detection via:

IP Reputation Analysis
User Behavior Monitoring
Bot Detection

Example: Block Suspicious IPs

 Use Tirreno API to block an IP 
curl -X POST http://localhost:3000/api/block-ip \ 
-H "Content-Type: application/json" \ 
-d '{"ip": "192.168.1.100", "reason": "Suspicious activity"}'

Log Analysis with Linux Commands

 Monitor Tirreno logs in real-time 
tail -f /var/log/tirreno/fraud.log

Filter high-risk events 
grep "HIGH_RISK" /var/log/tirreno/fraud.log | awk '{print $1, $4}'

3. Integration with SIEM Tools

Tirreno can forward logs to Splunk, ELK, or Graylog.

Example: Forward Logs to Syslog

 Configure rsyslog to forward Tirreno logs 
echo "local6. @<SIEM_IP>:514" >> /etc/rsyslog.conf

Restart rsyslog 
systemctl restart rsyslog

4. Automated Fraud Detection Rules

Customize detection rules in `config/rules.yaml`:

rules: 
- name: "Multiple Failed Logins" 
condition: "login_attempts > 5 within 1m" 
action: "block_user"

5. Windows Event Log Integration

For Windows-based fraud detection:

 Export Windows security logs for analysis 
wevtutil epl Security C:\FraudLogs\security.evtx /q:"[System[(EventID=4625)]]"

What Undercode Say

Tirreno is a powerful open-source fraud prevention tool that integrates well with existing security infrastructures. By leveraging Docker, Linux log analysis, and SIEM integrations, it provides a scalable solution for detecting fraudulent activities.

For advanced users, consider:

Enhancing rules with machine learning
Integrating with threat intelligence feeds
Automating responses using webhooks

Expected Output:

A fully functional fraud detection system with real-time monitoring, automated blocking, and seamless SIEM integration.