| name | performing-deception-technology-deployment |
| description | Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing high-fidelity alerts with near-zero false positive rates. Use when SOC teams need early warning of lateral movement, credential abuse, or internal reconnaissance by deploying convincing traps across the network.
|
| domain | cybersecurity |
| tags | ["soc","deception","honeypot","honeytoken","canary","lateral-movement","detection"] |
| subdomain | soc-operations |
| version | 1.0 |
| author | oyi77 |
| license | Apache-2.0 |
| nist_csf | ["DE.CM-01","DE.AE-02","RS.MA-01","DE.AE-06"] |
Performing Deception Technology Deployment
Overview
Cybersecurity skill for performing deception technology deployment. Follows industry best practices and security standards.
When to Use
Trigger phrases:
- "performing deception technology deployment"
- "SOC teams need high-fidelity detection of post-compromise lateral movement with"
- "Existing detection tools miss advanced attackers who avoid triggering threshold-"
- "The organization wants to detect credential abuse by planting fake credentials a"
Use this skill when:
- SOC teams need high-fidelity detection of post-compromise lateral movement with near-zero false positives
- Existing detection tools miss advanced attackers who avoid triggering threshold-based alerts
- The organization wants to detect credential abuse by planting fake credentials as honeytokens
- Network segmentation gaps need compensating detection controls
Do not use as a replacement for fundamental security controls (patching, EDR, network segmentation) — deception is a detection layer, not a prevention mechanism.
When NOT to Use
- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope
Prerequisites
- Network segments identified for honeypot/decoy deployment (server VLANs, DMZ, OT networks)
- Deception platform (Thinkst Canary, Attivo/SentinelOne Hologram, or open-source alternatives)
- SIEM integration for deception alerts (any interaction with deception assets is suspicious)
- Active Directory access for honeytoken account and credential creation
- Network team coordination for IP allocation and traffic routing
Workflow
import re
IOC_PATTERNS = {
"ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
"domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
"hash_md5": r"\b[a-f0-9]{32}\b",
"hash_sha256": r"\b[a-f0-9]{64}\b",
}
def extract_iocs() -> :
{k: re.findall(v, text) k, v IOC_PATTERNS.items()}