WAF-A-MoLE

WAF-A-MoLE A guided mutation-based fuzzer for ML-based Web Application Firewalls, inspired by AFL and based on the FuzzingBook by Andreas Zeller et al. Given an input SQL injection query, it tries to produce a semantic invariant query that is able to bypass the target WAF. You can use this tool f...

API-attack-detection-with-AI

Detection of SQL/XSS Attacks on Web API with Artificial Intelligence / Machine Learning This project aims to detect SQL and XSS injections in API requests/params using machine learning. Project Overview This project aims to detect SQL and XSS injections in API requests and parameters using Machin...

secretflow

简体中文｜English SecretFlow es un marco unificado para la inteligencia de datos y el aprendizaje automático con preservación de la privacidad. Para lograr este objetivo, proporciona: Una capa abstracta de dispositivos que consta de dispositivos simples y dispositivos secretos que encapsulan varios...

Log4Shell-vulnerability-CVE-2021-44228-

Log4Shell Threat Detection CVE-2021-44228 Overview This repository provides an in-depth analysis and implementation of a Machine Learning-based Log4Shell CVE-2021-44228 Threat Detection System. It includes: Understanding Log4Shell : What it is and why it is dangerous Dataset Collection : Sources...

columbo

Columbo Columbo es una herramienta de análisis forense informático utilizada para simplificar e identificar patrones específicos en conjuntos de datos comprometidos. Descompone los datos en secciones pequeñas y utiliza reconocimiento de patrones y modelos de aprendizaje automático para identifica...

pulsar

PULSAR Aprendizaje de Protocolos, Simulación y Fuzzer con Estado Pulsar es un fuzzer de red con capacidades automáticas de aprendizaje y simulación de protocolos. La herramienta permite modelar un protocolo mediante técnicas de aprendizaje automático, como clustering y modelos de Markov. Estos...

OMLASP

OMLASP | | | | | | || | | || | | | | | | | | OMLASP - Open Machine Learning Application Security Project is intended to become a standard for auditing Machine Learning algorithms. It will not only focus on the security of the algorithms but also on their biases. Typically, when applications that...

twebit

Análisis de Bitcoin con aprendizaje automático ¿Cómo funciona? 1- Obtener tweets de Twitter 2- Filtrar tweets 3- Clasificación de tweets con algoritmo Naive Bayes Positivo, negativo y neutro Instalación git clone https://github.com/omergunal/twebit cd twebit pip3 install -r requirements.txt...

logparser

Logparser Logparser fornisce un toolkit di machine learning e benchmark per il parsing automatico dei log, un passaggio fondamentale per l'analisi strutturata dei log. Applicando logparser, gli utenti possono estrarre automaticamente modelli di eventi da log non strutturati e convertire i messagg...

pcfg_cracker

PCFG = Probabilistic Context Free Grammar PCFG = Pretty Cool Fuzzy Guesser En resumen: Una colección de herramientas para investigar cómo los humanos generan contraseñas. Se pueden usar para descifrar hashes de contraseñas, pero también para crear contraseñas sintéticas honeywords o ayudar a...

deep-pwning

Deep-pwning è un framework leggero per sperimentare con modelli di machine learning, con l'obiettivo di valutarne la robustezza contro un avversario motivato. Si noti che deep-pwning nel suo stato attuale è lontano dall'essere maturo o completo. È pensato per essere sperimentato, ampliato ed este...

foolbox

home: true heroImage: /logo.png heroText: Foolbox tagline: "Foolbox: attacchi adversarial veloci per valutare la robustezza dei modelli di machine learning in PyTorch, TensorFlow e JAX" actionText: Inizia → actionLink: /guide/ features: title: Prestazioni native details: Foolbox 3 è basata su...

ai-security-battle

🤖 AI Security Battle System Red Team vs Blue Team: Adversarial ML Combat Simulation A comprehensive adversarial machine learning security simulation where Red Team attackers battle against Blue Team defenders in a 30-minute AI/ML security warfare scenario. 🎯 Project Overview This system simulates...

ML-for-RNGs

ML-for-RNGs Using Machine Learning to predict RNGs sequences...

AI_Security_Top

🛡️ AI-Security-Knowledge-Base This is a systematic AI security research project, covering a complete knowledge system from foundational machine learning algorithm theory to cutting-edge large model injection attacks, AI evasion countermeasures, and Deepfake. 🏗️ Knowledge System Architecture The...

BlueBox

BlueBox Malware analysis Box and Cyber threat Hunting What is it? Threat intelligence data about a malware, an IP or a domain , URL ? a Quick Analysis suspicious File or Malware ! BlueBox is an Open Source Intelligence, or OSINT solution to get threat intelligence data about a specific file, an I...

Damn-Vulnerable-ML-Model

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rulesfinder

rulesfinder Machine-learn password mangling rules! This tool finds efficient password mangling rules for John the Ripper or Hashcat for a given dictionary and a list of passwords. The tool is currently alpha quality. tl;dr You need the rust toolchain to build this tool. You can either directly...

URL_CHECKER

URL Phishing Checker A lightweight, web-based tool that detects whether a URL is likely phishing or safe using a hybrid approach of Machine Learning Random Forest/SVM and heuristic rule-based analysis. Built for educational purposes and experimentation in cybersecurity and applied AI. Overview...

ThreatSentry-AI

ThreatSentry AI: AI-Powered Threat Hunting Tool Automate external asset discovery, intelligently enrich with multi-source data, and leverage ensemble machine learning to predict and prioritize risk. Transform alert fatigue into actionable intelligence. 🚀 Mission Statement ThreatSentry AI eliminat...