Behavioral User-driven Deceptive Activities Framework
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Updated
Mar 15, 2025 - Python
Behavioral User-driven Deceptive Activities Framework
Deceptive Operations: Lure, Observe, and Secure Tool
A distributed, AI-powered honeypot system for Kubernetes. Uses OpenRouter to access 100+ LLMs (GPT-4o, Claude, Gemini) for generating realistic, context-aware vulnerable server responses. Features advanced scanner detection, session memory, and detailed artifact logging to trick attackers and capture threat intelligence.
A portable active cyber defense tool that uses decoy-based delaying tactics to mislead and restrain attackers in untrusted networks.
A fork of the original mailhoney SMTP honeypot rewritten due to library deprecation
Multi-protocol authentication honeypot framework with advanced evasion, fake success responses, and Docker deployment. Captures SSH, FTP, Telnet, HTTP/HTTPS, MySQL, RDP, and SMB attacks.
Advanced deception framework for security testing, digital forensics, and red teaming. Generates realistic fake data including SSH keys, web history, documents, API keys, source code, and system logs.
A specialized deception engineering tool mimicking SAP NetWeaver login interfaces to capture threat intelligence and detect credential harvesting attacks.
A novel adaptive security and deception platform using biological metaphors (protein folding, enzyme kinetics, immune response) with real cryptography, high-interaction honeypots, and Prometheus monitoring. Designed for biotech, pharma, and clinical research defense.
> Intelligent ML-powered honeypot infrastructure that captures, classifies, visualizes cyber attacks in real-time using Python, FastAPI, and scikit-learn.
A real-world, open-source Defense-in-Depth security framework built through CI/CD in production by security professionals.
🛡️ Detect and analyze authentication attacks with a robust honeypot framework that simulates real services across multiple protocols.
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