A Python package with 30 low-high level honeypots for monitoring network traffic, bots, and credential attacks.
Honeypots is a Python package that provides 30 different honeypots and emulators for network protocols like SSH, HTTP, FTP, and databases. It allows security teams to deploy deceptive services that log attack attempts, monitor for malicious bots, and capture stolen credentials across a wide range of services in a single, unified toolkit.
Security researchers, network administrators, and DevOps engineers who need to monitor their networks for intrusion attempts, analyze attack patterns, or gather threat intelligence.
It offers the broadest protocol coverage in a single package, is extremely quick to deploy, and provides flexible logging options, making it a comprehensive alternative to running multiple separate honeypot solutions.
30 different honeypots in one package! (dhcp, dns, elastic, ftp, http proxy, https proxy, http, https, imap, ipp, irc, ldap, memcache, mssql, mysql, ntp, oracle, pjl, pop3, postgres, rdp, redis, sip, smb, smtp, snmp, socks5, ssh, telnet, vnc)
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Includes 30 honeypots for SSH, HTTP, databases, and niche protocols like PJL and IPP, offering the widest range in a single package as per the README list.
Can spin up honeypots in 1-2 seconds using auto-configure scripts, with support for multiple instances and random ports to avoid privilege issues.
Outputs logs to files, terminal, Syslog, PostgreSQL, or SQLite, demonstrated in config.json examples for easy SIEM or database integration.
Honeypots can be imported as Python objects for custom use, with non-blocking servers and test functions, allowing for tailored security workflows.
The README notes servers are 'stripped-down', which may lack realism for advanced attacks, limiting effectiveness against sophisticated threat actors.
Relies on many external libraries like Twisted and impacket, acknowledged in the license terms, complicating installation and maintenance.
Requires command-line or config file management, lacking a GUI or centralized dashboard, which can hinder operational monitoring for larger deployments.