r2frida v6.2.2

r2frida Radare2 and Frida better together Description Self-contained plugin for radare2 that ships frida and allows to instrument local or remote processes using r2 commands instead but not limited to Frida scripts. The radare project provides a complete toolchain for reverse engineering, it's...

AVP-Inspect: Coordinated Cyber-Physical Testing for Privacy Analysis of COTS Apple Vision Pro Applications

XR devices introduce substantial privacy concerns due to their comprehensive data collection capabilities that surpass traditional computing platforms. While existing works have demonstrated privacy concerns on Android-based XR devices such as Meta Quest series by performing network traffic...

strix v1.6.1

Strix The open-source AI pentesting tool. Autonomous AI hackers that find and fix your app’s vulnerabilities. !TIP New! Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilities on every pull request and block insecure cod...

Mobile-Security-Framework-MobSF v4.5.2

Mobile Security Framework MobSF Mobile Security Framework MobSF is a security research platform for mobile applications in Android, iOS and Windows Mobile. MobSF can be used for a variety of use cases such as mobile application security, penetration testing, malware analysis, and privacy analysis...

Exploring Privacy Leakage and Data Disclosure Violations in the MacOS Application Ecosystem

The systematic and excessive data collection practices of tech companies have rendered online privacy both a necessity and a sought-after commodity. However, while the privacy risks of the web, mobile, and IoT ecosystems have been extensively examined, desktop environments have been largely...

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...

angr 9.3.1

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

emba v2.0.3-legacy-time

EMBA The security analyzer for firmware of embedded devices EMBA is designed as the central firmware analysis and SBOM tool for penetration testers, product security teams, developers and responsible product managers. It supports the complete security analysis process starting with firmware...

ProfMalPlus: Agent-Coordinated Detection of Malicious NPM Packages Via Static-Dynamic Analysis Synergy

Open source software is vulnerable to supply-chain attacks through transitive dependencies, especially malicious code injected into NPM packages. Existing detectors often inadequately model obfuscated behavior, overlook JavaScript's object-centric features, poorly coordinate static and dynamic...

Rethinking MCP Security: A Large-Scale Study of Runtime MCP Servers and Security Scanner Reliability

The Model Context Protocol MCP has rapidly established itself as a standard interface for enabling LLM-based agents to interact with external tools and services. As MCP servers are increasingly entrusted with security-sensitive operations, understanding their real-world risks has become critical...

MobSF Stored Cross-Site Scripting (XSS)

Product: MobSFVersion: 4.3.1CWE-ID: CWE-79: Improper Neutralization of Input During Web Page Generation 'Cross-site Scripting'CVSS vector v.4.0: 8.5 AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:NCVSS vector v.3.1: 8.1 AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:NDescription: Stored XSS in the iOS...

PYSEC-2026-1673 MobSF Stored Cross-Site Scripting (XSS)

Product: MobSF Version: CFBundleIdentifier value. In the dynamicanalysis.html file you do not sanitize...

AI-Generated PowerShell Malware: An Experimental Framework and Dataset

Generative AI has emerged as a significant cybersecurity threat, with several recent attack campaigns leveraging LLMs to generate code for malicious purposes via scripting languages such as PowerShell. Consequently, for cybersecurity analysts, it is imperative to investigate the offensive...

angr 9.2.222

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

Runtime Skill Audit: Targeted Runtime Probing for Agent Skill Security

Agent skills let LLM agents reuse instructions, resources, tools, and workflows, but they also create a new place for malicious behavior to hide. A skill may look benign in its documentation or code while becoming harmful only when it is invoked with particular user requests, local assets,...

angr 9.2.221

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

How to Compare the Security of Code Written by Humans to LLM-Generated Code

Large language models LLMs are rapidly transforming how software is created and maintained. Comparing LLM-generated code against human-written standards is essential to determine whether these new tools uphold or erode the security baselines established by professional developers. Yet, we lack a...

angr 9.2.219

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

angr 9.2.216

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

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...