Use Cases
From academic research to enterprise SOCs, threat.gg powers threat intelligence across disciplines.
Security Research
Academic and independent researchers use threat.gg to study attack patterns at scale. Deploy honeypots across multiple regions and protocols to collect real-world attack data without building custom infrastructure.
Export data via the REST API for statistical analysis, feed it into machine learning pipelines, or use the MCP integration for AI-assisted research. Full command logs and credential captures provide rich datasets for published research.
Rich Datasets
Full command sessions, credential pairs, and raw payloads ready for analysis and publication.
Multi-region Deployment
Deploy nodes globally to compare attack patterns across geographies and network segments.
API-first Data Access
Export everything via REST API. Integrate with Jupyter, R, or any analysis tool.
Threat Intelligence
SOC teams and threat hunters build indicator-of-compromise (IOC) feeds from live honeypot data. Track attacker IPs, malware samples, and credential campaigns as they evolve.
Correlate honeypot data with your existing threat intelligence platform. threat.gg's IP lookup and reputation scoring provide additional context for triage and investigation workflows.
IOC Generation
Automatically identify malicious IPs, credential patterns, and malware hashes from live attack data.
SIEM Integration
Feed threat data into Splunk, Elastic, or your SIEM of choice via the REST API.
Malware Collection
Capture and catalog malware samples dropped by attackers across all honeypot protocols.
Network Defense
Blue teams deploy honeypots as early-warning systems inside their network perimeter. Any connection to a honeypot is, by definition, suspicious — giving you high-confidence alerts with near-zero false positives.
Use internal honeypots to detect lateral movement, credential stuffing, and reconnaissance activity that bypasses traditional network monitoring.
Zero False Positives
Any interaction with a honeypot is inherently suspicious. No tuning, no noise, just real signals.
Early Warning
Detect attackers during reconnaissance before they reach production systems.
Lateral Movement Detection
Internal honeypots catch credential reuse and network scanning from compromised hosts.
Education
Cybersecurity instructors use threat.gg to bring real attack data into the classroom. Students can observe live attacks, analyze patterns, and practice incident response with genuine threat data.
The dashboard provides an intuitive interface for beginners, while the API gives advanced students the tools to build custom analysis pipelines and automate threat hunting workflows.
Live Attack Data
Show students real attacks in real time — far more engaging than static datasets or simulations.
Lab Environments
Set up isolated honeypot labs for hands-on exercises in attack analysis and incident response.
Curriculum Ready
REST API and dashboard work out of the box for assignments, capstones, and research projects.
Build Your Threat Intelligence
Whatever your use case, threat.gg gives you the data you need.