CVE-2019-6447-in-Mobile-Application

CVE-2019-6447-in-Mobile-Application In this research report you can get completly idea about the CVE 2019-6447 in the real world application and explotations with example. If you want to created video for the exploitation please use below mentions link...

fuzzbench

FuzzBench: Evaluación Comparativa de Fuzzers como Servicio FuzzBench es un servicio gratuito que evalúa fuzzers en una amplia variedad de referencias del mundo real, a escala de Google. El objetivo de FuzzBench es facilitar la evaluación rigurosa de la investigación en fuzzing y hacer que dicha...

clusterfuzz

ClusterFuzz ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features which help seamlessly integrate fuzzing into a softwar...

CVE-2026-41096-Attack-Surface

CVE-2026-41096 Real World Attack Surface Attack surface in the real-world environment of CVE-2026-41096 Links Detailed analytical article Author: Two Seven One Three...

pantagrule

Pantagrule gargantuan hashcat rulesets generated from compromised passwords Project maintenance warning : This project is deemed completed. No pull requests or changes will be made to this project in the future unless they are actual bugs or migrations to allow these rules to work with newer...

exploitgym

ExploitGym ExploitGym is a large-scale, realistic benchmark built from real-world vulnerabilities across userspace programs, Google's V8 engine, and the Linux kernel, designed to evaluate AI agents' ability to develop exploits. Quick start root@kitploit: 1. Python deps uv sync --extra proxy 2...

Piggybacking on Perception: Stealthy Concurrent Audio Prompt Injections against Multimodal LLM Agents

Large Language Model LLM-driven multimodal agents are increasingly deployed to execute autonomous tasks via continuous audio interaction. While this paradigm enhances interaction naturalness, it introduces a critical yet under-explored attack surface, as audio inputs inevitably contain...

CVE-2026-43499: A Critical Analysis of the "Zero-Self" Fallacy

This document presents a comprehensive technical analysis refuting the claim that CVE-2026-43499 GhostLock constitutes "no real vulnerability" due to its requirement for local access and user interaction. Through rigorous examination of the attack surface, exploitation vectors, and real-world...

EternalBlue-MS17-010-Vulnerability

EternalBlue MS17-010 Vulnerability Analysis This repository...

MacBook Neo vs Windows Laptops for Cybersecurity Tasks

There is no one-size-fits-all cybersecurity laptop. We’ll examine real-world work scenarios, tool compatibility, and trade-offs that impact a security professional’s day-to-day work...

Nuclei 3.9.0

Nuclei is a modern, high-performance vulnerability scanner that leverages simple YAML-based templates. It empowers you to design custom vulnerability detection scenarios that mimic real-world conditions, leading to zero false positives...

The Chronicles of Radio Frequency Fingerprinting

Radio Frequency Fingerprinting RFF has evolved from an early idea for radar emitter identification into a broad research field for wireless device identification and spectrum monitoring for security. Rather than presenting a conventional literature survey, this work provides a critical historical...

ExploitGym AI Exploit Benchmark Tool

ExploitGym is a large-scale, realistic benchmark built from real-world vulnerabilities designed to evaluate AI agents' ability to develop exploits...

CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-To-End Cybersecurity Capabilities

AI has the potential to transform cybersecurity by enabling systems that can autonomously detect, analyze, and remediate software vulnerabilities. However, existing cybersecurity evaluations of AI systems are limited in scale or scope, and fail to capture the end-to-end lifecycle of real-world...

The Role of Domain-Specific Features in Malware Detection: A MacOS Case Study

Despite the growing popularity of macOS among end users and enterprise systems, malware research has primarily focused on Windows and Android operating systems, leaving the problem of macOS malware detection relatively unexplored. Indeed, the specificity of the operating system and the unique...

Less panic patching, more precision

Welcome to this week's edition of the Threat Source newsletter. Recently, Martin closed his introduction with a warning: Ready or not, the time of much patching is coming. I've been chewing on that one for a while because I'm rethinking my own enrichment pipelines along these lines, and the...

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...

Measuring Real-World Prompt Injection Attacks in LLM-Based Resume Screening

LLMs are vulnerable to prompt injection attacks. However, this vulnerability has been primarily demonstrated conceptually in academic studies or through a few anecdotal case studies. Its prevalence and impact in real-world LLM-based applications are largely unexplored. In this work, we present th...

VIPER-MCP: Detecting and Exploiting Taint-Style Vulnerabilities in Model Context Protocol Servers

Model Context Protocol MCP has emerged as a standard interface for connecting LLM agents to external tools. Because MCP servers expose privileged operations such as shell execution, network access, and file-system manipulation to agent-driven invocation, implementation flaws in tool handlers can...

Agent Security Is a Systems Problem

We take the position that agent security must be approached as a systems problem: the AI model powering the agent must be treated as an untrusted component, and security invariants must be enforced at the system level. Through this lens, efforts to increase model robustness the dominant viewpoint...