Implementing Network Deception with Honeypots

When to Use

• When deploying deception technology to detect lateral movement
• To create early warning indicators for network intrusion
• During security architecture design to add detection depth
• When monitoring for unauthorized internal scanning or credential theft
• To gather threat intelligence on attacker techniques and tools

Prerequisites

• Linux server or VM for honeypot deployment (Ubuntu 22.04+ recommended)
• Python 3.8+ with pip for OpenCanary installation
• Docker for T-Pot or containerized deployment
• Network segment with appropriate VLAN configuration
• SIEM integration for alert forwarding (syslog, webhook, or file-based)
• Firewall rules allowing inbound connections to honeypot services

Workflow

1. Plan Deployment: Select honeypot types and network placement strategy.
2. Install Honeypot: Deploy OpenCanary, Cowrie, or T-Pot on dedicated host.
3. Configure Services: Enable emulated services (SSH, HTTP, SMB, FTP, RDP).
4. Set Up Alerting: Configure log forwarding to SIEM and alert channels.
5. Deploy Canary Tokens: Place credential files, shares, and DNS entries.
6. Monitor Interactions: Analyze honeypot logs for attacker activity.
7. Tune and Maintain: Update configurations based on detection results.

Key Concepts

Tools & Systems

Output Format

Alert: HONEYPOT-[SERVICE]-[DATE]-[SEQ]
Honeypot: [Hostname/IP]
Service: [SSH/HTTP/SMB/FTP/RDP]
Source IP: [Attacker IP]
Interaction: [Login attempt/Port scan/File access]
Credentials Used: [Username:Password if applicable]
Commands Executed: [For SSH honeypots]
Risk Level: [Critical/High/Medium/Low]