mirror of
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Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
87 lines
2.9 KiB
Markdown
87 lines
2.9 KiB
Markdown
---
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name: implementing-network-deception-with-honeypots
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description: Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral
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movement, and attacker reconnaissance.
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domain: cybersecurity
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subdomain: deception-technology
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tags:
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- deception
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- honeypot
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- opencanary
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- cowrie
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- t-pot
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- detection
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- lateral-movement
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- network-security
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- DE.CM-01
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- DE.AE-06
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- PR.IR-01
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---
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# Implementing Network Deception with Honeypots
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## When to Use
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- When deploying deception technology to detect lateral movement
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- To create early warning indicators for network intrusion
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- During security architecture design to add detection depth
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- When monitoring for unauthorized internal scanning or credential theft
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- To gather threat intelligence on attacker techniques and tools
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## Prerequisites
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- Linux server or VM for honeypot deployment (Ubuntu 22.04+ recommended)
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- Python 3.8+ with pip for OpenCanary installation
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- Docker for T-Pot or containerized deployment
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- Network segment with appropriate VLAN configuration
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- SIEM integration for alert forwarding (syslog, webhook, or file-based)
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- Firewall rules allowing inbound connections to honeypot services
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## Workflow
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1. **Plan Deployment**: Select honeypot types and network placement strategy.
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2. **Install Honeypot**: Deploy OpenCanary, Cowrie, or T-Pot on dedicated host.
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3. **Configure Services**: Enable emulated services (SSH, HTTP, SMB, FTP, RDP).
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4. **Set Up Alerting**: Configure log forwarding to SIEM and alert channels.
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5. **Deploy Canary Tokens**: Place credential files, shares, and DNS entries.
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6. **Monitor Interactions**: Analyze honeypot logs for attacker activity.
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7. **Tune and Maintain**: Update configurations based on detection results.
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## Key Concepts
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| Concept | Description |
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|---------|-------------|
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| OpenCanary | Lightweight Python honeypot with modular service emulation |
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| Cowrie | Medium-interaction SSH/Telnet honeypot capturing commands |
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| T-Pot | Multi-honeypot platform with ELK stack visualization |
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| Canary Token | Tripwire credential or file that alerts when accessed |
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| Low-Interaction | Emulates services at protocol level without full OS |
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| High-Interaction | Full OS honeypot capturing complete attacker sessions |
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## Tools & Systems
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| Tool | Purpose |
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|------|---------|
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| OpenCanary | Modular honeypot daemon with service emulation |
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| Cowrie | SSH/Telnet honeypot with session recording |
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| T-Pot | All-in-one multi-honeypot platform |
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| Dionaea | Malware-capturing honeypot for exploit detection |
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| Splunk/Elastic | SIEM for honeypot alert aggregation |
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## Output Format
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```
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Alert: HONEYPOT-[SERVICE]-[DATE]-[SEQ]
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Honeypot: [Hostname/IP]
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Service: [SSH/HTTP/SMB/FTP/RDP]
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Source IP: [Attacker IP]
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Interaction: [Login attempt/Port scan/File access]
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Credentials Used: [Username:Password if applicable]
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Commands Executed: [For SSH honeypots]
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Risk Level: [Critical/High/Medium/Low]
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```
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