MOSAIC

🎯 MOSAIC — v1.0.0-alpha Behavioral Intelligence Across Platforms A privacy-first, multi-platform framework for behavioral and sociodynamic analysis 📺 Demo 🧭 What is MOSAIC? MOSAIC is not a simple OSINT aggregator. It is a behavioral analysis framework designed to help researchers, analysts, and...

cuckoo-modified

This is a heavily modified version of Cuckoo Sandbox provided under the GPL. It offers a number of advantages over the upstream Cuckoo: Fully-normalized file and registry names 64-bit analysis Handling of WoW64 filesystem redirection Many additional API hooks Service monitoring Correlates API cal...

tcpflow

TCPFLOW 1.5.0 Downloads directory: http://digitalcorpora.org/downloads/tcpflow/ Installation Most common GNU/Linux distributions ship tcpflow in their repositories. So on Debian/Ubuntu/etc you can say root@kitploit: sudo apt-get install tcpflow and on Fedora/RedHat/CentOS/etc you can say...

BerrySentinel

🫐 Berry Sentinel Real-time behavioral C2 Command & Control connection detector Zero-signature · Bulletproof Collection · Deep Scan · Kill Engine What is it? Berry Sentinel monitors all active network connections on your system and analyzes the behavior of the processes that generate them to detec...

Pegasus-Malware-Scan

pegasus-malware-scan Description Pegasus Malware Scan is a comprehensive cybersecurity solution designed for advanced threat detection and malware analysis. Built with Python, this powerful tool employs multi-layered detection techniques to identify and neutralize a wide range of malicious...

EmailXpose

EmailXpose 规格说明 AI 驱动的电子邮件清晰度分析 HTML 镜像：https://roxanneardary.com/emailxpose-specification/ 规格概述 EmailXpose 是一个开源、模块化的 AI 电子邮件安全与情报系统，旨在分析电子邮件内容、发件人身份、链接、附件、图片和视频，以识别网络钓鱼、垃圾邮件、诈骗、恶意软件、社会工程、欺骗行为及上下文异常。 EmailXpose 将传统电子邮件安全分析与自然语言处理、计算机视觉、多模态智能、行为分析、威胁情报和符号学解读相结合。该系统旨在解释其发现，而非仅仅给出威胁分类。...

Kaonashi

Kaonashi Project: RootedCON 2019 This repository contains several directories: Sorted Masks for hashcat Advanced Rules for hashcat Links to download the Kaonishi's Wordlists Slides used in our talk I know your p4$$w0rd and if I don't, I will guess it... at RootedCON 2019 A clone may not be...

DrSemu

Dr.Semu Dr.Semu runs executables in an isolated environment, monitors the behavior of a process, and based on Dr.Semu rules created by you or the community, detects if the process is malicious or not. The tool is in the early development stage whoami: @qazqaz With Dr.Semu you can create rules to...

windows-malware-behavioral-analysis

Análisis de comportamiento de malware con REMnux y FLARE-VM Una investigación práctica de malware para el equipo azul que demuestra cómo se pueden analizar ejecutables sospechosos de Windows de forma segura dentro de un laboratorio aislado mediante técnicas de análisis de comportamiento. En lugar...

vi-bot

BotDetect v2 — Production Bot Detection Library Client-side bot and automation detection library with weighted scoring, behavioral analysis, browser fingerprinting, and configurable thresholds. Detects headless browsers, Selenium, Puppeteer, Playwright, CDP-based tools, and stealth automation...

VISION-ProcMon

About VISION-ProcMon is a tool dedicated for malware analysis and specifically when performing behavioral analysis. VISION-ProcMon is using a combination of the rust and web technologies in order to provide a fast and better visualization of the behavior of a malware after capturing its activity...

fnprint

fnprint empareja funciones en binarios por lo que hacen , no por cómo se ven sus bytes o sus grafos de flujo de control. ejecuta cada función en un pequeño emulador con entradas inventadas, registra los efectos secundarios que produce y convierte ese comportamiento en una huella digital. dos...

Detecting Data Exfiltration through I2P Anonymity Networks: A Two-Phase Machine Learning Approach

The Invisible Internet Project I2P provides strong anonymity through garlic routing and distributed network architecture, making it attractive for legitimate privacy needs. Nevertheless, the same properties can be exploited by malicious actors to steal sensitive information from corporate network...

📄 HEUR.Backdoor.Win32.Poison.gen DLL Hijacking

This code implements an advanced WININET.dll proxy via DLL hijacking that is designed as a defensive countermeasure against malware such as HEUR.Backdoor.Win32.Poison.gen. The malware family Poison loads a 32‑bit WININET.dll from its current directory, which enables execution flow hijacking MITRE...

Techniques of Modern Attacks

The techniques used in modern attacks have become an important factor for investigation. As we advance further into the digital age, cyber attackers are employing increasingly sophisticated and highly threatening methods. These attacks target not only organizations and governments but also extend...

BEACON: A Unified Behavioral-Tactical Framework for Explainable Cybercrime Analysis with Large Language Models

Cybercrime increasingly exploits human cognitive biases in addition to technical vulnerabilities, yet most existing analytical frameworks focus primarily on operational aspects and overlook psychological manipulation. This paper proposes BEACON, a unified dual-dimension framework that integrates...

CVE-2025-61301

Denial-of-analysis in reporting/mongodb.py and reporting/jsondump.py in CAPEv2 commit 52e4b43, on 2025-05-17 allows attackers who can submit samples to cause incomplete or missing behavioral analysis reports by generating deeply nested or oversized behavior data that trigger MongoDB BSON limits o...

CVE-2025-61303

CVE-2025-61303 concerns a vulnerability in the Windows behavioral analysis engine used by Hatching Triage Sandbox (Windows 10 build 2004 and Windows 10 LTSC 2021). The issue arises when a sample recursively spawns a very large number of child processes, producing an extreme log volume and exhaust...

Cyber Attack Mitigation Framework for Denial of Service (DoS) Attacks in Fog Computing

Innovative solutions to cyber security issues are shaped by the ever-changing landscape of cyber threats. Automating the mitigation of these threats can be achieved through a new methodology that addresses the domain of mitigation automation, which is often overlooked. This literature overview...

RADEP: a Resilient Adaptive Defense Framework against Model Extraction Attacks

Machine Learning as a Service MLaaS enables users to leverage powerful machine learning models through cloud-based APIs, offering scalability and ease of deployment. However, these services are vulnerable to model extraction attacks, where adversaries repeatedly query the application programming...