
cowrie2neo parses Cowrie honeypot logs and imports the data into Neo4j databases for graph-based analysis and visualization of honeypot interactions.
Checked October 2026.
cowrie2neo is a specialized tool designed to parse log files generated by Cowrie honeypots and import the extracted data into Neo4j graph databases.
The tool processes honeypot interaction logs to transform raw log data into structured formats suitable for graph database storage. It enables security researchers and analysts to leverage Neo4j's graph capabilities for examining attack patterns, relationships between attackers, and behavioral analysis of malicious activities captured by Cowrie honeypots.
The tool facilitates the conversion of linear log data into interconnected graph structures, allowing for advanced querying and visualization of honeypot data. This transformation enables users to identify attack chains, correlate events, and perform complex analysis on honeypot interactions that would be difficult to achieve with traditional log analysis methods.
cowrie2neo supports the integration of honeypot data with Neo4j's ecosystem, enabling users to apply graph algorithms and create custom visualizations for threat intelligence and security research purposes.
No core features are listed for this product yet, so check the vendor's documentation for the full feature list.
No integrations are listed for this product yet. Check the vendor's documentation, or ask the vendor which integrations and APIs it supports.
Common questions about cowrie2neo: features, pricing and alternatives.
cowrie2neo is a product in the Honeypots & Deception category. It covers Neo4j, Visualization and Security Research.
cowrie2neo is free. Download and setup instructions are at https://github.com/xlfe/cowrie2neo/.
Alternatives to cowrie2neo listed on CybersecTools:
Compare all cowrie2neo alternatives at https://cybersectools.com/alternatives/cowrie2neo
cowrie2neo is available as on-premises software. It is listed for mid-market companies and enterprises. It is free.
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