shennina

Shennina 利用人工智能自动化主机漏洞利用 摘要 Shennina 是一个自动化主机漏洞利用框架。该项目的使命是利用人工智能完全自动化扫描、漏洞扫描/分析和漏洞利用。Shennina 集成了 Metasploit 和 Nmap 来执行攻击，并与内部命令与控制服务器集成，自动从被攻陷的机器中窃取数据。 本项目由 Mazin Ahmed 和 Khalid Farah 在 HITB CyberWeek 2019 AI 挑战赛 中开发。项目基于 Isao Takaesu 的 DeepExploit 概念开发。 Shennina 对输入的目标集进行扫描以发现可用网络服务，使用其 AI...

sonicwall-audit-toolkit

Kit de Auditoría de Seguridad de SonicWall Marco de evaluación de seguridad automatizado para dispositivos SonicWall. Solo para compromisos de pruebas de penetración autorizados. Inicio Rápido root@kitploit: Install dependencies pip install -r requirements.txt Run all modules against a target...

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...

IPDevicePenTest

IPDevicePenTest Automated penetration testing framework for...

Automated Framework to Evaluate and Harden LLM System Instructions against Encoding Attacks

System Instructions in Large Language Models LLMs are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational context in agentic AI applications. These instructions may contain sensitive information such as API credentials, internal policies, and...

Exploit for Deserialization of Untrusted Data in Siemens 6Bk1602-0Aa12-0Tp0_Firmware

⚡ Pentest Automation !Versionhttps://img.shields.io/badg...

Breaking the Illusion: Automated Reasoning of GDPR Consent Violations

Recent privacy regulations such as the General Data Protection Regulation GDPR and the California Consumer Privacy Act CCPA have established legal requirements for obtaining user consent regarding the collection, use, and sharing of personal data. These regulations emphasize that consent must be...

Network-Vuln

🔍 Network Vulnerability Scanner !Pythonhttps://img.shiel...

STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents

As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based LLM safety concerns. This paper introduces Sequential Tool Attack Chaining STAC, a novel multi-turn attack framework that exploits agent tool use. STA...

Automatic Red Teaming LLM-Based Agents with Model Context Protocol Tools

The remarkable capability of large language models LLMs has led to the wide application of LLM-based agents in various domains. To standardize interactions between LLM-based agents and their environments, model context protocol MCP tools have become the de facto standard and are now widely...

AutoRAN: Weak-To-Strong Jailbreaking of Large Reasoning Models

This paper presents AutoRAN, the first automated, weak-to-strong jailbreak attack framework targeting large reasoning models LRMs. At its core, AutoRAN leverages a weak, less-aligned reasoning model to simulate the target model's high-level reasoning structures, generates narrative prompts, and...

grapheneX - Automated System Hardening Framework

grapheneX In computing, hardening is usually the process of securing a system by reducing its surface of vulnerability, which is larger when a system performs more functions; in principle a single-function system is more secure than a multipurpose one. Reducing available ways of attack typically...