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window red team in tamil

Windows Persistence Techniques (MITRE ATT&CK Mapped) – Complete Red Team Course Windows persistence is one of the most important topics for red teamers, malware analysts, DFIR professionals, and cybersecurity students. Understanding persistence techniques helps both attackers simulate real-world threats and defenders detect and respond to them. This article accompanies my full YouTube course, which covers Windows internals, persistence mechanisms, privilege escalation, post-exploitation concepts, and digital forensics in a controlled lab environment. 📺 Full Video What You'll Learn Windows Boot Process Windows Architecture Windows System Calls Windows Memory Management PEB & TEB Structures Windows Persistence Techniques Registry-Based Persistence DLL Hijacking Windows Services Scheduled Tasks Digital Forensics Registry Analysis Privilege Escalation Concepts Post-Exploitation Techniques MITRE ATT&CK Mapping Tools Covered Mimikatz AccessChk PowerUp PrivescCheck SharpUp RegRipper Registry Explorer Regshot SessionGopher LaZagne PSRecon Frogman Tool LogonTracer credump Course Structure Windows Internals Persistence Techniques Digital Forensics Privilege Escalation Post Exploitation MITRE ATT&CK Mapping GitHub Resources Windows Persistence Repository https://github.com/manikandantn68/window-persistence-Privilege-Escalation Frogman Tool https://github.com/manikandantn68/frogman-tool Intended Audience Cybersecurity Students SOC Analysts Blue Team Engineers Red Team Operators Malware Analysts Digital Forensics Investigators Penetration Testers Educational Disclaimer This course is intended solely for educational purposes and demonstrates techniques within an authorized lab environment. Always obtain proper permission before testing or assessing systems you do not own or administer.

2026-06-29 原文 →
AI 资讯

Anthropic’s Fable and the State of AI

On June 9th, Anthropic released its Fable generative AI model. Three days later, the US government classified it as a dangerous munition, and used its export-control authority to prohibit any foreign nationals from accessing it. Unable to differentiate between Americans and foreigners, the company shut off access for everyone. The government’s actions won’t help . The problem isn’t any one particular model; it’s the general trend of increasing AI capabilities. And any real solution requires the sort of collective action that just isn’t possible right now...

2026-06-19 原文 →
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🗺️ The Ultimate Cybersecurity Roadmap (Momentum-First Learning System)

Most cybersecurity roadmaps fail beginners. They give you a long list of topics like Linux, Networking, Python, and Security tools without any order or direction. This makes people confused, overwhelmed, and they usually quit early. This roadmap is different. It follows a momentum-first learning system, where every step builds on the previous one. You don’t just learn topics — you grow step by step like a system. The goal is simple: You always know what to learn next and why you are learning it. 🧠 How This Roadmap Works Instead of random learning, this roadmap is divided into phases. Each phase: builds real skills connects with the next phase moves from basic → advanced focuses on practical understanding By the end, you will understand how systems work, how they are built, how they are tested, and how they are secured. 🟢 PHASE 1: 🧠 The Signal Awakening Protocol (System Basics) Goal: Understand how computers and the internet actually work. Topics Google Dorking Using advanced search techniques to find specific information on the internet. You learn how search engines work beyond normal searches. OSINT (Open Source Intelligence) Collecting information from public sources like websites, social media, and forums. You learn how to gather data like a digital investigator. How Web Browsers Work Understanding how a browser sends requests and receives data from servers. This helps you understand what happens behind every website you open. Introduction to Computers & Operating Systems Basic understanding of CPU, RAM, storage, and how operating systems manage everything. This is the foundation of all cybersecurity. Virtualization (VirtualBox / VMware) Running a virtual computer inside your main computer. You use this to create a safe lab for practice. Linux Basics Learning how to use Linux systems. Most servers and cybersecurity tools run on Linux, so this is important. Bash Scripting Writing simple scripts to automate tasks in Linux. You move from manual work to automation. O

2026-06-12 原文 →
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Build Your Own "Longevity Scientist": A Paper-to-Action Agent using LangGraph & Mistral-7B

We live in an era where scientific breakthroughs are published faster than we can read them. For the biohacking community, the gap between a new PubMed study on NAD+ precursors and actually knowing what dose to take is a chasm of manual research. What if you could build an LLM Agent that monitors research papers, processes them through a RAG (Retrieval-Augmented Generation) pipeline, and maps findings to your specific health profile? In this tutorial, we are building Paper-to-Action , a state-of-the-art agentic workflow using LangGraph , ChromaDB , and Mistral-7B . This isn't just a simple bot; it's a multi-stage reasoning engine designed to turn raw academic data into actionable health interventions. If you've been looking to master AI agents and personalized medicine automation, you’re in the right place. 🚀 The Architecture: From Raw Paper to Personalized Habit Traditional RAG pipelines are linear. To handle the nuance of medical research, we need a "looping" logic. We use LangGraph to manage the state of our agent, allowing it to decide if a paper is relevant before attempting to extract a protocol. System Flow graph TD A[Start: Keyword Trigger] --> B[Search PubMed/Arxiv API] B --> C{Relevance Filter} C -- No --> B C -- Yes --> D[Store in ChromaDB] D --> E[RAG: Extract Intervention Protocol] E --> F[Cross-Reference with User Profile] F --> G[Generate Personalized Action Plan] G --> H[End: Push to Health Checklist] Prerequisites To follow this advanced guide, you'll need: LangGraph : For the agentic state machine. ChromaDB : As our high-performance vector store. Mistral-7B : Running via Ollama or vLLM for local, private inference. Python 3.10+ Step 1: Defining the Agent State In LangGraph, everything revolves around the State . We need to track the fetched papers, the extracted data, and the final recommendation. from typing import Annotated , List , TypedDict from langgraph.graph import StateGraph , END class AgentState ( TypedDict ): keywords : List [ str ] user

2026-06-06 原文 →
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Hacking Meta’s AI Chatbot

Hackers are convincing Meta’s AI support chatbot to let them take over other peoples’ accounts: A video posted on X showed the step-by-step process to hack someone’s Instagram account. The hacker allegedly used a VPN to spoof the targets’ presumed location to avoid triggering Instagram’s automated account protections. Then, the hacker opened a chat with Meta AI Support Assistant and asked the bot to add a new email address to the target’s account. The chatbot can be seen sending a verification code to the email address provided by the hacker; the hacker then shares the verification code with the chatbot, which prompts the chatbot to show a button to “Reset Password.” The hacker enters a new password and takes over the victim’s account...

2026-06-04 原文 →