Mephala: An ML-Powered Intelligent Honeypot System to Expose All Cyber Threats

Mephala is an open-source honeypot system that combines machine learning technology to achieve real-time threat detection. It supports multi-protocol traps such as SSH, HTTP, and FTP, provides 24/7 monitoring and a visualization interface, helping security teams proactively identify and defend against attacks. Suitable for scenarios like enterprise protection and security research, it is open-source (MIT License) and welcomes community contributions.

Traditional firewalls and intrusion detection systems are mostly passive response-based, waiting for attacks to occur before blocking them. Honeypot technology, however, proactively deploys decoy systems to lure attackers into exposing their methods and intentions, thereby obtaining threat intelligence. Mephala is a modern implementation of this concept, integrating machine learning to enhance threat detection capabilities.

Traditional honeypots rely on static rules or signatures to identify attacks. Mephala's machine learning engine learns abnormal behavior patterns from historical data, enabling it to capture traces of unknown zero-day attacks, improve detection accuracy, and reduce false positive rates.

Mephala supports flexible configuration of multiple service traps:

• SSH trap: Simulates an SSH server, records login attempts and command executions
• HTTP trap: Disguises as a web service, captures web application attack payloads
• FTP trap: Simulates a file transfer service, monitors file system intrusion attempts Multi-protocol support adapts to the needs of different network environments.

Mephala provides 24/7 round-the-clock monitoring, displaying real-time alerts and analysis data through an intuitive dashboard, allowing non-technical users to understand the security situation easily. Deployment is simple: downloading the installation package takes only a few minutes to complete. Advanced users can deploy via Docker containerization to achieve isolation, testing, and expansion.

Mephala is suitable for multiple scenarios:

• Enterprise network protection: Internal deployment to detect lateral movement attacks
• Security research: Provides real attack data samples
• Threat intelligence collection: Understand attackers' TTPs (Tactics, Techniques, Procedures)
• Security training: Serves as a red-blue team exercise target environment

Mephala represents a new direction of combining honeypot technology with AI, enhancing threat detection capabilities. As an open-source project under the MIT License, it welcomes community contributions: report vulnerabilities, suggest new features, or improve documentation to jointly perfect the project. For teams looking to enhance their cybersecurity protection, it is a proactive defense tool worth paying attention to.