#1ML-based security tools, adversarial machine learning, and AI-powered cyber defense.
Kitploit recommended

Demonstrates using machine learning to predict random number generator sequences, highlighting cryptographic weaknesses through adversarial analysis.
A LSTM based framework for handling multiclass imbalance in DGA botnet detection

Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language Models

VEDAS-Driven Autonomous Generation + Community Contributions of Suricata & Nuclei Rules for over 13,000 CVEs

Suppress vulnerabilities applying Kubernetes context to scans

Detection of rootkit file hiding activities through analysis of shifts in kernel function execution times.

Fix-Like Artifacts With Embedded Defects

Cyber Threat Defense World Modeling

A Python library for Secure and Explainable Machine Learning Documentation available @ https://secml.gitlab.io Follow us on Twitter @…

This Repository is created after my own research into malicious browser extensions, by brining the work of many others and news articles into one…

AMBER ICI v5: local-first Ollama investigative command center with case-scoped evidence, agent chains, hybrid retrieval, streaming analysis, graph…

An ML powered Graph-Based Multi-Architecture Approach for ROP Gadget Detection

Self-hosted multi-agent environment for Go with LLM-powered pentesting agents (exploiter, reverser, threathunter, webscanner) that automate…

A Semantics-Enhanced Learnable Vulnerability Detector

DGA-generated domain detection using deep learning models

An interactive CLI application for interacting with authenticated Jupyter instances.

Programmable packet inspection engine with NIDS, DNS classification, frequency analysis, and auto-regex generation. Supports Python/Ruby/Java/Lua…

Step-by-step tutorial on using Google's Gemma 4 E4B local AI model to reverse engineer a Windows crackme with Ghidra, including setup for local…