android-kernel-exploitation

Android 커널 익스플로잇 목표 이 워크숍의 목표는 Android 플랫폼에서 커널 취약점 분석 및 익스플로잇 을 시작하는 것입니다. 사용 방법 저장소를 클론합니다 root@kitploit: git clone https://github.com/cloudfuzz/android-kernel-exploitation /workshop Github Pages URL https://cloudfuzz.github.io/android-kernel-exploitation/ 워크숍 스트림 커널 빌드를 위한 Docker root@kitploit...

analise-vulnerabilidades-zabbix-notebooklm

🛡️ Анализ уязвимостей SQLi в Zabbix с помощью NotebookLM Тематический блокнот, разработанный в рамках сдачи проектного задания DIO Используя NotebookLM как инструмент активного ИИ для курирования, синтеза и организации знаний в области кибербезопасности 📋 Содержание Контекст и цели Курирование...

JustALampNothingElse

Full vulnerability analysis and app description can be found here: https://drive.google.com/file/d/14s5rYThOpEbU6KjBNT2D2l65WDcwCDTL/view?usp=drivelink This project was made with SocialTIC and ITESO Cris...

CVE-2025-5548

🛠️ 환경 설정 대상 플랫폼: Windows 이 가이드는 바이너리의 취약점 분석 및 퍼징을 수행하는 데 필요한 모든 도구를 자세히 설명합니다. 모든 것이 올바르게 설정되도록 순서대로 단계를 따르십시오. 🐍 Python 3 다운로드: python.org/downloads/windows Python 3는 퍼징 스크립트 를 작성하는 데 사용할 언어입니다. 단순성과 풍부한 생태계 덕분에 대상 바이너리에 페이로드를 전달하고, 네트워크 연결을 처리하며, 응답을 처리하는 작업을 자동화하는 데 이상적입니다. 설치: 링크에서 .exe 설치...

awesome-list — Updated!

Awesome Cybersecurity List My personal collection of awesome blog posts, write-ups, and papers focusing on cybersecurity. For a deeper dive into cybersecurity-related tools, check out the dedicated Cybersecurity Tools list. Outline 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2014 2011...

linux-privesc-linpeas

🐧 linux-privesc-linpeas End-to-end Linux privilege escalati...

cve-research

CVE Research Personal repository for CVE analysis, proof-of-c...

cybersec-mcp

🛡️ Cybersecurity Professor MCP Server Prof. Null — Tu pro...

Towards Demystifying and Repairing LLM-In-The-Loop Vulnerabilities

Large Language ModelsLLMs have been actively integrated into modern software systems as critical components. LLM-in-the-loop vulnerabilities, where vulnerabilities are introduced by LLMs and their dependent downstream components, such as frameworks, introduce new risks. Although some benchmark...

Exploit for Improper Handling of Exceptional Conditions in Apache Struts

LAB 1 — Apache Struts2 OGNL Injection CVE-2017-5638 / S2-045...

FuzzingBrain V2: A Multi-Agent LLM System for Automated Vulnerability Discovery and Reproduction

Software vulnerabilities pose critical security threats, with nearly 50,000 CVEs reported in 2025. While Large Language Models LLMs show promise for automated vulnerability detection, three key challenges remain. First, LLM-generated vulnerability reports suffer from high false positive rates and...

claude-skills-exploit

Security Research Skills Reusable skills for vulnerability an...

Exploit for SQL Injection in Progress Moveit_Cloud

CVE-2023-34362 MOVEit Transfer Vulnerability Analysis Proj...

cve-deep-dive

Report Bug · Request Feature Table of Contents a...

PatchChain-Multi-Agent-Agentic-Pipeline-for-Autonomous-Code-Vulnerability-Analysis

No d...

Exploit for Deserialization of Untrusted Data in Facebook React

🕵️ CVE-2025-55182 — React Vulnerability Analysis Security...

patchbot

patchbot patchbot is an AI-assisted security reviewer for p...

Time-Domain Voice Identity Morphing (TD-VIM): A Signal-Level Approach to Morphing Attacks on Speaker Verification Systems

In biometric systems, it is a common practice to associate each sample or template with a specific individual. Nevertheless, recent studies have demonstrated the feasibility of generating "morphed" biometric samples capable of matching multiple identities. These morph attacks have been recognized...

METATRON AI Penetration Testing

Metatron is a CLI-based AI penetration testing assistant that runs entirely on your local machine - no cloud, no API keys, no subscriptions. You give it a target IP or domain. It runs real recon tools nmap, whois, whatweb, curl, dig, nikto, feeds all results to a locally running AI model, and the...

SkillAttack: Automated Red Teaming of Agent Skills through Attack Path Refinement

LLM-based agent systems increasingly rely on agent skills sourced from open registries to extend their capabilities, yet the openness of such ecosystems makes skills difficult to thoroughly vet. Existing attacks rely on injecting malicious instructions into skills, making them easily detectable b...