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.

Honeypot canaries for AI agents. Detect compromised agents via fake credentials that phone home when used.

AIWAF-JS is an adaptive, AI-powered Web Application Firewall for Node.js. It detects anomalies, blocks IPs, stops honeypot and UUID tampering, and evolves using real log data.

Security Project for social media

A sophisticated honeypot system for detecting and classifying AI agents, bots, and automated HTTP clients using behavioral fingerprinting and machine learning.

Professional-grade ERC-20 token security scanner in Rust. Detects honeypots and rug pulls using 16+ API integrations and AI-powered analysis.

Generative AI-driven Honeypot for cybersecurity. Simulates realistic server logs with AI and detects intrusions using unsupervised anomaly detection (Isolation Forest + NLP embeddings). Showcases synthetic data generation, feature engineering, and end-to-end ML workflow.

BlockSafe is an autonomous cognitive firewall protecting the human decision layer. Powered by Groq, it fingerprints text-based scam strategies in real time. Using pre-action Telegram interventions and AI honeypots, it neutralizes active threats and converts every scam attempt into structured intelligence for proactive defense.

Enhancing honeypot deception using AI generated network information

An AI-Powered Advanced Threat Detection System Using Honeypots

AI-powered SSH Honeypot using Go and Gemini 2.5

AI-driven deception technology using honeypots to detect cyber threats

COMP813 AI project to build an adaptive honeypot using Reinforcement Learning

AI-powered SSH honeypot using Gemini API to simulate realistic Linux terminal responses

This project uses Cowrie honeypot logs to parse, cluster, and visualize attacker commands using AI-driven techniques on a linux.

AI-powered honeypot network that captures, analyzes, and predicts cybersecurity threats using machine learning and real-time threat intelligence

We using open-code honeypots and collecting data to watch attackers movements. Also using AI to visualize data. We working on botnet detection on the internet using this project. We install honeypots such as Cowrie and Dionea and run them together.

Welcome to AI-Powered Honeypot , a cutting-edge cybersecurity tool designed to detect and analyze suspicious login attempts using artificial intelligence. This honeypot leverages the power of Streamlit for the frontend and Groq's AI models for real-time threat analysis.

HoneyAI: A distributed honeypot threat analysis platform that collects, parses, and classifies attacker behavior using AI, generating actionable cybersecurity intelligence and attacker profiles.

This project is a self-contained, local honeypot system that deploys decoy network services to attract, log, and analyze attacker behavior using AI techniques.

TID-Recon-Dog is an advanced deception platform built to trap, track, and analyze malicious intrusions using a powerful blend of honeypots and local AI agents.

**Experimental release** This project provides a multi-layered defense strategy against scraping by unauthorized AI bots, specifically adapted for deployment on Windows Server using Internet Information Services (IIS). It includes real-time detection, tarpitting, honeypots, and behavioral analysis with optional AI/LLM integration.

This project implements an Agentic AI Honeypot that: - Detects scam intent using keyword-based analysis - Activates an autonomous AI agent with a human-like persona - Handles multi-turn conversations - Extracts scam intelligence (UPI IDs, phone numbers, links) - Reports final intelligence to the GUVI evaluation endpoint

AI-powered honeypot that detects scam messages, engages scammers using dynamic victim personas, and extracts actionable intelligence (phone numbers, bank accounts, UPI IDs, phishing links) in real time. Built with FastAPI, GPT-4o, and a hybrid ML detection pipeline.

A honeypot in cybersecurity is a decoy system designed to attract and trap malicious actors, allowing security teams to monitor and analyze attack methods. It helps enhance defenses by providing insights into threats. ---- This HonePot is made up by using AI.

Project Phantasm is a high-end, autonomous cybersecurity deception platform designed to combat modern Agentic AI threats and advanced persistent threats (APTs). It moves beyond traditional, static honeypots by creating a "digitally sentient" maze that uses generative AI to interact with, mislead, and profile attackers in real-time.

An AI-powered agentic honeypot system that detects scam messages, engages scammers using a believable human-like persona, handles multi-turn conversations, and secretly extracts intelligence such as UPI IDs, bank accounts, phone numbers, and phishing links. The system exposes this capability through a secure REST API for automated evaluation

AegisGuard is an intelligent network security system that uses multi-agent reinforcement learning to autonomously defend networks. Unlike static firewalls, the system deploys specialized AI agents that collaborate in real-time to detect threats, dynamically reconfigure security protocols, quarantine malicious nodes and deploy adaptive honeypots.

Honeypot implementation using AI

AI-powered Honeypot system using Cowrie honeypot, MITRE ATT&CK mapping, and real-time threat analysis with a dashboard to monitor.