mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2.9 KiB
2.9 KiB
| name | description | domain | subdomain | tags | version | author | license | nist_csf | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| implementing-network-deception-with-honeypots | Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance. | cybersecurity | deception-technology |
|
1.0 | mahipal | Apache-2.0 |
|
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
- Plan Deployment: Select honeypot types and network placement strategy.
- Install Honeypot: Deploy OpenCanary, Cowrie, or T-Pot on dedicated host.
- Configure Services: Enable emulated services (SSH, HTTP, SMB, FTP, RDP).
- Set Up Alerting: Configure log forwarding to SIEM and alert channels.
- Deploy Canary Tokens: Place credential files, shares, and DNS entries.
- Monitor Interactions: Analyze honeypot logs for attacker activity.
- Tune and Maintain: Update configurations based on detection results.
Key Concepts
| Concept | Description |
|---|---|
| OpenCanary | Lightweight Python honeypot with modular service emulation |
| Cowrie | Medium-interaction SSH/Telnet honeypot capturing commands |
| T-Pot | Multi-honeypot platform with ELK stack visualization |
| Canary Token | Tripwire credential or file that alerts when accessed |
| Low-Interaction | Emulates services at protocol level without full OS |
| High-Interaction | Full OS honeypot capturing complete attacker sessions |
Tools & Systems
| Tool | Purpose |
|---|---|
| OpenCanary | Modular honeypot daemon with service emulation |
| Cowrie | SSH/Telnet honeypot with session recording |
| T-Pot | All-in-one multi-honeypot platform |
| Dionaea | Malware-capturing honeypot for exploit detection |
| Splunk/Elastic | SIEM for honeypot alert aggregation |
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]