Watch Cybersecurity Tutorialspoint Pdf Video Tutorials & Courses

In this video, I walk through my Cybersecurity Internship Project — a PDF Malware Analysis Toolkit built in Python, developed as part of my internship with . This toolkit performs static analysis on PDF files to detect malicious content — including embedded JavaScript, obfuscation patterns, suspicious objects, extracted URLs/IPs, and embedded executables — and generates a weighted risk score (Low to Critical) just like a real SOC analyst workflow. 🔗 Live Demo (Deployed App): https://pdf-malware-analysis-toolkit-zpappzmv2mw7nbvgrwtohph.streamlit.app/ 🔗 GitHub Repository (Source Code): https://github.com/Gurkirat-sudo-su/pdf-malware-analysis-toolkit 🔗 Detailed Project Report: https://docs.google.com/document/d/1vwE_v4fZv_ursvLMTYyUnzeJg1ZgMEmz/edit?usp=drive_link ⏱️ Timestamps Introduction What the project does Live demo — clean PDF (Low risk) Live demo — suspicious PDF (Critical risk) Key learnings 🛠️ Tech Stack: Python, Streamlit, pypdf, Regex-based static analysis 📚 What I learned: - How attackers weaponize PDF documents using embedded JavaScript and exploit techniques - Static analysis methods used by SOC analysts and incident responders - Building and deploying a real-world security tool from scratch - Risk scoring and IOC (Indicators of Compromise) extraction This project covers metadata inspection, object enumeration, JavaScript obfuscation detection (eval, unescape, String.fromCharCode), URL/IP extraction, and automated report generation. #Cybersecurity #PDFMalware #PythonProject #MalwareAnalysis #EthicalHacking #CybersecurityInternship #UnifiedMentor #InfoSec #SOCAnalyst #StaticAnalysis Key Highlights & Overview: Learning <strong>Cybersecurity Tutorialspoint Pdf</strong> requires clear step-by-step guidance and practical hands-on visual demonstrations. Follow along with top-rated video tutorials from industry experts today on <strong>TutorTube</strong>.