ThreatHound

ThreatHound ThreatHound is an advanced cybersecurity tool designed to facilitate efficient threat detection and analysis, windows events logs. it offers a user-friendly interface for managing and analyzing security data. Key features include log analysis, Sigma rule integration, and real-time...

FalconEye

FalconEye: Real-time detection software for Windows process injections FalconEye is a windows endpoint detection software for real-time process injections. It is a kernel-mode driver that aims to catch process injections as they are happening real-time. Since FalconEye runs in kernel mode, it...

Detect-CVE-2017-0144-attack

Python Program to Detect CVE-2017-0144 Attack Python program tasked with continuously monitoring network traffic in real-time. It will alert on the console when it detects a CVE-2017-0144 EternalBlue attack 1. Lab Model This lab is performed on 3 virtual machines in VMWare. 1 attacker machine Kal...

fibratus

Fibratus Sensor de seguridad para la detección y protección de amenazas en tiempo real Comenzar » Documentación • Reglas • Filaments • Descargas • Debates Fibratus detecta y erradica tácticas avanzadas de atacantes, malware y amenazas emergentes al examinar y contrastar un amplio espectro de...

metlo

Metlo API Security Protege tu API. Metlo es una plataforma de seguridad de API de código abierto Metlo es una herramienta de seguridad de API de código abierto que puedes configurar en menos de 15 minutos, inventaria tus endpoints, detecta actores maliciosos y bloquea tráfico malicioso en tiempo...

reflector

reflector Descripción La extensión de Burp Suite es capaz de encontrar XSS reflejado en la página en tiempo real mientras se navega por el sitio web e incluye algunas características como: Resaltado de la reflexión en la pestaña de respuesta. Prueba de qué símbolos están permitidos en esta...

Introducing Continuous Vulnerability Assessment: Real-Time Defense for the AI Threat Era

Detect exposure to new vulnerabilities the moment they are published with Wiz CVA...

-SQLi-Defender

🛡️ SQLi Defender Real-Time SQL Injection Detection & Prev...

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting in the widespread adoption of mobile applications. Although applications are required to undergo malware screening before being published on officia...

Web-Server-Log-Parser-Threat-Detector

Log threat detector A lightweight Python security tool that pa...

Why Modern SOCs Need Multi-Layered Detections

The cycle is over. For years, cybersecurity followed a familiar pattern: defenses improved, attackers adapted, and the back-and-forth continued. Today, AI-equipped attackers are simply outpacing defenses. Most intrusions now bypass endpoint and malware-based detection entirely. The CrowdStrike...

SingGuard-NSFA: Extensible Guardrails for Agentic AI Via Generative Reasoning and Real-Time Classification

We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive information extraction, malicious code requests, dangerous tool misuse, and resource exhaustion. We first introduce the NSFA taxonomy, which organizes 185...

AI Threat Readiness Pillar 4: Detect and contain threats in real-time

Your guide to operationalizing AI-powered threat detection and response with Wiz to stay ahead of AI-driven attackers...

A Hybrid CNN-LSTM Intrusion Detection Framework for Cybersecurity in Smart Renewable Energy Grids

The accelerated digitalization of renewable energy smart grids through IoT sensors, AMI, and SCADA systems has significantly expanded the attack surface for sophisticated cyberattacks, FDI attacks that stealthily distort state estimation and DoS/DDoS attacks that flood communication channels...

Intelligent Detection and Mitigation of Carpet-Bombing DDoS Attacks in SDN Using Retrieval-Augmented Generation and Large Language Models

Software-Defined Networking SDN provides flexible and programmable network management; however, its centralized control architecture remains highly vulnerable to Distributed Denial-of-Service DDoS attacks, particularly Carpet-Bombing DDoS attacks that distribute malicious traffic across multiple...

Smart Contract Security beyond Detection

Smart contract security has progressed from vulnerability detection toward a broader research agenda that includes semantic reasoning, automated repair, adversarial robustness, and real-time exploit detection. This paper develops a capstone-oriented research narrative around four directions:...

A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation

The proliferation of Internet of Things IoT devices has significantly expanded attack surfaces, making IoT ecosystems particularly susceptible to sophisticated cyber threats. To address this challenge, this work introduces A-THENA, a lightweight early intrusion detection system EIDS that...

RansomTrack: A Hybrid Behavioral Analysis Framework for Ransomware Detection

Ransomware poses a serious and fast-acting threat to critical systems, often encrypting files within seconds of execution. Research indicates that ransomware is the most reported cybercrime in terms of financial damage, highlighting the urgent need for early-stage detection before encryption is...

Next-Generation Cyberattack Detection with Large Language Models: Anomaly Analysis across Heterogeneous Logs

This project explores large language models LLMs for anomaly detection across heterogeneous log sources. Traditional intrusion detection systems suffer from high false positive rates, semantic blindness, and data scarcity, as logs are inherently sensitive, making clean datasets rare. We address...

AI-Powered Algorithms for the Prevention and Detection of Computer Malware Infections

The rise in frequency and complexity of malware attacks are viewed as a major threat to modern digital infrastructure, which means that traditional signature-based detection methods are becoming less effective. As cyber threats continue to evolve, there is a growing need for intelligent systems t...