Freelancers using Security Onion in Lahore

Freelancers using Security Onion in LahoreFreelancers using Security Onion in Lahore

Projects People

Zeeshan Raza

Lahore, Pakistan

Expert SAAS Developer | Full Stack Developer | Web Designer

Cover image for Social Impact | Non Profit

Social Impact | Non Profit Website

Cover image for Next Quest | Connectivity Through

Next Quest | Connectivity Through Unqiue Team Building Activities

Micheal Mark | Public Speaker

FXGM | Photography Studio

Security Onion(1)

Zuha Junaid

Lahore, Pakistan

AI Engineer & Creative Strategist create Immersive Solutions

New to Contra

AI Engineer & Creative Strategist create Immersive Solutions

Cover image for Executive Summary
The primary objective of

Executive Summary The primary objective of this project was to identify and mitigate security vulnerabilities within a custom-built academic portal. By implementing a defense-in-depth strategy, the assessment utilized multiple security testing methodologies to ensure a robust security posture. The evaluation revealed moderate security risks, primarily involving server misconfigurations and missing security headers.

Zuha Junaid - 3D AI & Software Engineer Portfolio A modern, immersive 3D portfolio website showcasing AI/ML projects, full-stack development expertise, and technical skills. Built with cutting-edge web technologies and designed with glassmorphism aesthetics. 🌐 Live Portfolio: https://zuha3dport-s3994me9.manus.space ✨ Features 🎨 Design & Aesthetics Dark Glassmorphism: Frosted glass cards with backdrop blur effects 3D Animations: Animated particle background with mouse interaction Responsive Design: Fully optimized for desktop, tablet, and mobile devices Smooth Transitions: Elegant page transitions and hover effects Premium Color Palette: Dark blue (#0a0e27) with teal (#1dd1a1) and purple (#a29bfe) accents 📄 4 Complete Pages Home - Hero section with animated 3D background and quick stats About - Technical skills showcase, education, and interests Projects - 4 major projects with detailed descriptions and technologies Contact - Contact form and social media links 🎯 Interactive Elements Animated particle background system Glass card hover effects Staggered entrance animations Smooth page navigation Responsive contact form Social media integration

Cover image for Al-Insaan Care: A Supportive App

Al-Insaan Care: A Supportive App for Illiterate Needy People Al-Insaan Care is a mobile application specifically designed to bridge the accessibility gap for illiterate and needy individuals. By removing traditional text-based barriers, the platform empowers users to request and receive essential financial aid and material donations—including food, clothing, electronics, and blood—with dignity and ease. Project Overview The primary goal of Al-Insaan Care is to provide an inclusive, user-friendly experience for populations that struggle with literacy. The application leverages multimedia tools to ensure that navigating the path to assistance is as intuitive as possible. Key Features Accessibility-First Design: Information is presented through visuals, audio instructions, and videos rather than text. Voice-Activated Requests: Users can submit vital information (CNIC, address, house details) via voice messages or direct calls. Thorough Verification: An administrative department validates all requests to ensure aid reaches those truly in need. Streamlined Distribution: Integrated delivery services handle the distribution of material goods, while money and blood are managed through direct channels. Social & Community Engagement: A social feed allows for community interaction and updates on humanitarian efforts. UI & User Experience The interface is designed to be clean and minimalist, focusing on high-contrast iconography and simple workflows. Main Components Section AND Description Donation Portal: Uses icons (cutlery for food, shirt for clothing, etc.) to help users identify categories without reading. Checkout Flow: A simple process with a 100% discount model for needy recipients, resulting in a total cost of Rs.0. Dashboard: Provides administrators and donors with a visual overview of contributions and user growth through line graphs. Chat Interface: Includes a microphone option for instant voice commands and communication with support staff. Activity Feed: Tracks real-time user interactions, likes, and comments to foster a supportive community. How It Works Request: A user in need accesses the app and submits their details using voice commands or multimedia tools. Verify: The administrative team reviews the voice-submitted data and validates the request. Fulfill: Donors or the organization provide the requested items. Deliver: The delivery department ensures the items reach the verified address via courier or direct distribution.

Cover image for Diabetes Prediction System
Developed a prediction

Diabetes Prediction System Developed a prediction system using Pima Indians dataset, achieving 84% accuracy with Random Forest. Performed comprehensive data cleaning and median imputation for missing values. Implemented feature scaling and model evaluation with cross-validation. 84% Accuracy Data Cleaning Feature Scaling Technologies Python Scikit-learn Pandas Random Forest

Security Onion(1)