sshesame is a free honeypots & deception tool. Manuka by Andew Michael Smith is a free honeypots & deception tool. Compare features, ratings, integrations, and community reviews side by side to find the best honeypots & deception fit for your security stack.
Based on our analysis of available product data, here is our conclusion:
Security teams that need to observe SSH attack patterns without investing in expensive infrastructure will get immediate value from sshesame; it's genuinely trivial to deploy and starts capturing brute-force attempts and reconnaissance activity within minutes. The 1,716 GitHub stars reflect active use in real environments, and the zero cost means you can run multiple instances across network segments without budget negotiation. Skip this if your threat model requires honeypots that simulate full application stacks or if you need managed alerting and incident response integration; sshesame logs activity but leaves analysis and response entirely to you.
Security teams building internal honeypot infrastructure on limited budgets will appreciate Manuka by Andew Michael Smith for how quickly it spins up dionaea and kippo instances without wrestling Docker configuration. The script approach cuts setup time from hours to minutes, which matters when you're running honeypots as a learning tool or low-cost early warning system. Skip this if you need managed honeypot infrastructure, commercial-grade alert tuning, or support beyond what the 26-star GitHub community provides; Manuka assumes you're comfortable maintaining your own Docker environment and interpreting raw honeypot data.
An easy to set up SSH honeypot for logging SSH connections and activity.
A script for setting up a dionaea and kippo honeypot using Docker images.
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Common questions about comparing sshesame vs Manuka by Andew Michael Smith for your honeypots & deception needs.
sshesame: An easy to set up SSH honeypot for logging SSH connections and activity..
Manuka by Andew Michael Smith: A script for setting up a dionaea and kippo honeypot using Docker images..
Both serve the Honeypots & Deception market but differ in approach, feature depth, and target audience.
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