Dataforge Honeypot

Dataforge Honeypot
honeypot.app.dataforgecanada.comDeploys decoy systems on your LAN to detect internal network probes and lateral movement, alerting you to threats.

Dataforge Honeypot
honeypot.app.dataforgecanada.comDeploys decoy systems on your LAN to detect internal network probes and lateral movement, alerting you to threats.
Deploys decoy systems on your LAN to detect internal network probes and lateral movement, alerting you to threats.
honeypot.app.dataforgecanada.comMomentum rises when people search, view, like, share, claim, or save this profile.
Dataforge Honeypot provides a cybersecurity solution to detect internal network threats by deploying decoy systems that mimic real targets on your LAN. It identifies suspicious activity like scanning or snooping, reporting it to a central web portal for monitoring. Users receive real-time alerts via email or Telegram, allowing them to act before issues escalate. The system is designed for easy deployment using a Docker command and offers both a free Community edition and a paid Standard plan.
IT professionals, network administrators, and security-conscious individuals managing home labs or small to medium-sized business networks who need to detect internal threats.
Dataforge Honeypot offers a focused solution for a critical, often overlooked, aspect of cybersecurity: internal threat detection. Its ease of deployment via Docker, combined with a free community edition, lowers the barrier to adoption. The claim of being tested effectively against professional penetration testers adds significant credibility, suggesting a robust and valuable tool for proactive network defense.
AI-assisted scores estimated from public website information only.
This FounderDeck estimate of $350,000 reflects Dataforge Honeypot's clear value proposition in internal network security, a painkiller use case for many organizations. The product appears polished, offers a clear freemium monetization path, and is easy to deploy. While the solution addresses a real market need, the estimate is not higher due to the absence of explicit user traction, revenue figures, or detailed team information, which would provide stronger signals of market validation and growth.
Valuation date: 2026-06-05. Estimate generated from public signals.
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