Cowrie SSH/Telnet Honeypot https://docs.cowrie.org/
Discontinued. Fork at your will.
Malware written in bash to serve as an initial dropper script that will provide a strong foothold on the target device via reverse shells and persistence techniques, can be set to run via user interaction or coupled with a bot.
Parse cowrie honeypot logs into a neo4j database
A script using Docker to quickly bring up some honeypots exposing lots of services. For research, reconnaissance, and fun. (DISCLAIMER may not be fun, not to be taken internally, aim away from face)
Kubernetes for Cowrie
The goal of Engaged Threat is to provide honeypot researchers the ability to hold the attention of an attacker or to induce the attacker to participate in some sort of increased activity.
🛡️A machine learning-based Intrusion Detection System that uses the Cowrie honeypot to collect attack data in a Debian VMware setup. Data is stored in MongoDB and analyzed using the AdaBoost algorithm ⚙️ to detect threats. This project shows how honeypots and ML can enhance cybersecurity.
An automated honeypot network using Ansible.
The National Cyber Threat Intelligence Hub collects, processes, and visualizes cyber threat data in real time.
Multi-task NLP on Cowrie honeypot attacker-session logs—classification, QA, summarization & remediation; Flask/Django integration.
A cloud-native honeypot system built using Cowrie on Amazon EC2, designed to attract, log, and analyze malicious behavior. Leveraging AWS services including S3, CloudWatch, Lambda, and DynamoDB.
Hands-on Cowrie SSH honeypot project capturing attacker behavior and SSH intrusion attempts. Built for learning threat detection, logging, and security analytics.
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