Freelancers using Docker in PunjabFreelancers using Docker in Punjab
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Ahmed Khan's avatar
Ahmed Khan
Lahore, Pakistan
Cybersecurity specialist with ability to identify flaws
Cybersecurity specialist with ability to identify flaws
Cover image for I simulated a real-world Active
I simulated a real-world Active Directory (AD) attack to identify and exploit misconfigurations within a Windows domain environment. The goal was to practice enumeration techniques, escalate privileges to domain admin, and establish persistent access. I started with LDAP enumeration using ldapsearch to map domain users and groups. Using BloodHound, I visualized attack paths and identified a Kerberoastable service account — a weak SPN tied to an outdated service. I extracted the hash using GetUserSPNs.py (http://GetUserSPNs.py) and cracked it with Hashcat, revealing the cleartext password. I then used Pass-the-Hash to authenticate as a domain admin using PsExec. To maintain persistence, I added a domain admin backdoor account using Mimikatz. Finally, I cleared event logs to avoid detection and exported a full attack report for remediation. Tools Used: ldapsearch, BloodHound, Hashcat, GetUserSPNs.py (http://GetUserSPNs.py), PsExec, Mimikatz, eventlog (for cleanup) Deliverable: Full attack timeline with screenshots, enumeration outputs, and security recommendations.
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Cover image for I conducted a complete web
I conducted a complete web application security assessment on Damn Vulnerable Web Application (DVWA) using manual and automated testing techniques. The goal was to identify and exploit OWASP Top 10 vulnerabilities. I mapped the application using Burp Suite and discovered multiple injection points. I exploited SQL Injection to bypass authentication and extract sensitive data from the database using sqlmap. I also tested for Cross-Site Scripting (XSS) with custom payloads and successfully hijacked session cookies using document.cookie injection. I chained a file upload vulnerability with a PHP reverse shell to gain remote access to the server. All findings were documented with proof-of-concept screenshots and step-by-step remediation guidance. Tools Used: Burp Suite, sqlmap, OWASP ZAP, curl, custom payloads Deliverable: A detailed report including vulnerability exploitation steps, proof-of-concept, and mitigation strategies.
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Cover image for I performed a complete network
I performed a complete network penetration test on a deliberately vulnerable Linux machine (Metasploitable2) to simulate a real-world attacker scenario. The objective was to identify exploitable services, gain initial access, escalate privileges to root, and extract sensitive data. I started with reconnaissance using nmap to discover open ports and services. I identified outdated and vulnerable services including vsftpd 2.3.4 and Samba 3.0.20. Using Metasploit, I exploited the vsftpd backdoor to gain initial shell access. I then used shell_to_meterpreter to upgrade my session to a Meterpreter shell, giving me greater control. I dumped password hashes from /etc/shadow and cracked them using John the Ripper. Finally, I escalated privileges to root using the Samba usermap_script exploit and documented the entire process with screenshots. Tools Used: nmap, Metasploit, Meterpreter, John the Ripper, searchsploit Deliverable: A comprehensive report including attack timeline, exploited CVEs, and remediation recommendations.
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Cover image for I discovered a stored cross-site
I discovered a stored cross-site scripting (XSS) vulnerability in a practice web application's comment section that allowed me to inject malicious JavaScript that would execute in any user's browser. By submitting a comment containing a script payload, I successfully stole session cookies from other users and could have hijacked their accounts, performed actions on their behalf, or defaced the website. This finding was documented in a comprehensive report including proof-of-concept screenshots showing cookie theft, CVSS risk scoring of 6.5 (Medium), and step-by-step remediation guidance including input sanitization and output encoding. This assessment demonstrates my ability to find client-side vulnerabilities that can compromise every user visiting the site.
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Docker(3)
abdullah masood's avatar
abdullah masood
Lahore, Pakistan
AI & Full-Stack Engineer | Building Production AI SaaS, APIs
New to Contra
AI & Full-Stack Engineer | Building Production AI SaaS, APIs
Cover image for A Kubernetes deployment should be
A Kubernetes deployment should be easy to trace: what changed, who changed it, and why. That’s what interests me about GitOps. With GitOps, the desired state of your infrastructure and applications lives in Git. Changes go through commits and pull requests, while a controller such as Argo CD or Flux continuously reconciles the running environment with that desired state. A typical workflow looks like this: • Build and test the application through CI. • Push the Docker image to a registry. • Update the image version in the Git configuration. • Review and merge the change. • Let the GitOps controller reconcile the cluster. The benefits go beyond automated deployments: ✅ A versioned history of configuration changes ✅ Reviewable changes before deployment ✅ Visibility into configuration drift ✅ A repeatable way to manage environments One important detail: reverting a Git commit can restore an earlier configuration, but database migrations and changes to application data still need their own recovery plan. For me, GitOps connects development and operations through a workflow both teams already understand: Git. Are you using Argo CD, Flux, or CI-driven deployments for your Kubernetes workloads?
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Cover image for Production Kubernetes & Cloud Deployment
Production Kubernetes & Cloud Deployment
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Cover image for 🚀 Introducing GraphBridge – Turn
🚀 Introducing GraphBridge – Turn JSON into Grafana Dashboards One thing I've noticed while working on different projects is that applications already have valuable metrics, but getting those metrics into Grafana often requires exporters, custom integrations, or additional setup. I wanted something much simpler. So I built GraphBridge. The idea is straightforward: Your Application ↓ Send JSON ↓ GraphBridge ↓ Prometheus ↓ Grafana Instead of writing custom exporters, your application simply sends JSON metrics to GraphBridge. For example: { "active_users": 85, "orders_today": 42, "revenue_today": 9840, "failed_jobs": 3, "latency_ms": 210 } GraphBridge automatically converts the data into Prometheus metrics, making it immediately available for Grafana dashboards. Current features ✅ JSON Webhook API ✅ REST API polling ✅ JSON & CSV data sources ✅ Prometheus /metrics endpoint ✅ Docker Compose deployment ✅ Auto-configured Grafana dashboard ✅ Example integrations for Laravel, FastAPI, Node.js, and custom applications Possible use cases • Application monitoring • Queue & background job metrics • Business dashboards • API performance monitoring • FFmpeg streaming statistics • IoT sensor metrics • Internal analytics • Custom operational dashboards The goal is simple: Send JSON. Visualize everything. This is the first public MVP, and I'm planning to continue improving it with additional integrations and monitoring templates. I'd love your feedback and suggestions! ⭐ GitHub: https://lnkd.in/dAYdNJxg
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Cover image for 🚀 Building a Graph-Based Fraud
🚀 Building a Graph-Based Fraud Detection System with Neo4j A single transaction may look normal. Its connections can tell a different story. I’m building a learning project using Neo4j and Cypher to explore relationships between customers, accounts, transactions, and devices—and flag patterns worth investigating. 🔍 Patterns I’m exploring: • Multiple customers sharing the same device • Unusually large transactions • Rapid transactions within a short period • Multiple accounts sending money to one account • Circular transfers between connected accounts The focus is explainability: showing the relationships behind each flag so the suspicious activity is easier to understand. Through this project, I’m strengthening my graph data modelling, Cypher queries, and rule-based detection skills. Next: FastAPI integration, transaction risk scores, fraud alerts, and an interactive monitoring dashboard. 🛠️ Currently a learning prototype, with more updates coming as I build. What would you investigate first: shared devices or circular transfers? #Neo4j #GraphDatabase #FraudDetection #Cypher #BackendDevelopment #LearningInPublic
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Docker(2)
Hamza Hameed's avatar
Hamza Hameed
Lahore, Pakistan
Backend Python Engineer | Django, FastAPI, REST APIs & Cloud
New to Contra
Backend Python Engineer | Django, FastAPI, REST APIs & Cloud
Cover image for Fashion Studio is an AI-powered
Fashion Studio is an AI-powered fashion creation platform designed to help fashion brands and creators generate professional product visuals without traditional photoshoots. The platform combines virtual try-on, AI model generation, image generation, video generation, face swapping, and quality assurance into a single workflow. I worked on the backend and AI integration layer, building APIs and workflows that connect the platform with multiple AI services and handle the generation lifecycle from user input to final output. Key features include: 👗 Virtual Try-On — Apply garments and accessories to generated or uploaded models. 🧑‍🎨 AI Model Generation — Create realistic fashion models with configurable gender, appearance, measurements, poses, and backgrounds. 🖼️ AI Image Generation — Generate fashion campaigns and product visuals from prompts and references. 🎬 AI Video Generation — Turn generated fashion imagery into promotional videos. 🔄 Face Swap — Generate customized fashion content using face-swapping workflows. 🛡️ AI Quality Assurance — Automatically evaluate generated results and retry failed generations when necessary. 📚 Generation Library — Track and manage generated assets and their parameters. 💳 Credits & Billing — Manage generation credits, subscriptions, usage, and add-on credits. ⚙️ Generation Parameters — Store model configuration, garments, poses, backgrounds, aspect ratios, and generation metadata. Technology Python · Django · FastAPI · PostgreSQL · REST APIs · Replicate · OpenAI · Docker · AI Image Generation · AI Video Generation My Role Backend Engineer / AI Integration Engineer I focused on designing the backend APIs, integrating AI generation services, building generation workflows, handling asynchronous processing and failures, and connecting the AI capabilities with the product's user-facing workflows.
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Cover image for DarrenCaddle is a recruitment-focused CRM
DarrenCaddle is a recruitment-focused CRM and lead management platform designed to help recruitment teams organize large volumes of leads, companies, candidates, job opportunities, and sales activities in one centralized system. I worked on the backend development and business logic, building the systems required to manage recruitment data, lead workflows, company assignments, sales tasks, and administrative operations. Key Features Lead Management — Create, track, search, filter, and manage large volumes of recruitment leads. Advanced Lead Filtering — Filter leads by source, team, assigned user, country, status, sales task, outreach activity, and other attributes. Company Management — Maintain company records, domains, assignments, statuses, and associated recruitment activity. Candidate & Person Management — Organize candidate/person information and connect it with companies, jobs, and leads. Sales Workflow Management — Track sales tasks, responses, resume submissions, interest, contracts, and other recruitment stages. Job Management — Associate leads and candidates with relevant job opportunities. Lead Assignment — Assign companies and leads to specific team members and manage ownership across the recruitment workflow. Search & Reporting — Provide administrative tools for quickly finding and managing large datasets. Scalable Data Management — Built the backend around high-volume recruitment data, with the interface showing 250K+ leads and 200K+ company records. Admin Operations — Developed interfaces and backend functionality for managing the recruitment operation from a centralized platform. My Role Backend Engineer / Django Developer I was responsible for the backend development, including: Designing and developing backend APIs and business logic Building lead and company management workflows Implementing search, filtering, assignment, and status-management functionality Designing data relationships between leads, companies, people, jobs, and sales activities Building administrative workflows for managing large datasets Supporting recruitment and sales operations through custom backend functionality Technology Python · Django · Django REST Framework · PostgreSQL · REST APIs · Database Design · Backend Development
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Cover image for Fynite is a data-driven SaaS
Fynite is a data-driven SaaS platform designed to help businesses manage products, analyze market data, integrate external data sources, and create intelligent pricing strategies. I worked on the backend and data engineering side of the platform, building APIs, integrations, data pipelines, pricing workflows, and the infrastructure required to process and manage large volumes of product and pricing data. Key Features Dynamic Pricing Engine — Create and apply pricing strategies based on stock, demand, promotions, competitors, volume, and time-based rules. Product Management — Manage product catalogs, variations, SKUs, pricing, inventory, POS data, and dynamic pricing status. Competitor Pricing Intelligence — Collect and compare competitor pricing data to support data-driven pricing decisions. ETL & Data Pipelines — Ingest, transform, and synchronize data from multiple external sources. Third-Party Integrations — Built integrations with platforms such as Shopify, Square, Toast, Clover, NCR, and other data sources. Analytics & Dashboards — Provide revenue, net-value, price-index, competitor, and business performance insights. Pricing Strategies — Support promotion-based, stock-based, volume, time-based, demand-based, competitor-based, and fixed-markup pricing. Lead & Company Management — Manage leads, companies, assignments, sales tasks, and recruitment/business workflows within the broader platform. API Integrations — Connect external services and data providers through backend APIs and integration workflows. Scalable Data Architecture — Designed backend workflows for handling large datasets and continuously synchronized business data. My Role Backend Engineer / Python & Django Developer I focused primarily on the backend architecture and data layer, including: Designing and developing Django/REST APIs Building data ingestion and ETL workflows Integrating third-party platforms and APIs Implementing dynamic pricing logic and business rules Working with relational databases and analytical data stores Building automated data synchronization workflows Developing backend services for dashboards and analytics Handling product, pricing, inventory, competitor, and integration data Supporting cloud-based data processing and deployment Technology Python · Django · Django REST Framework · PostgreSQL · Amazon Redshift · AWS · Docker · REST APIs · Celery · ETL · Data Pipelines · Third-Party APIs
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Cover image for Django - SkillSwap
Django - SkillSwap
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Docker(1)
Muhammad Luqman's avatar
Muhammad Luqman
Lahore, Pakistan
Helping Startups & SMBs to build Scalable, Impactful Product
5.0
Rating
6
Followers
Helping Startups & SMBs to build Scalable, Impactful Product
Cover image for Financial Accounting Assistant – SaaS Web Application
Financial Accounting Assistant – SaaS Web Application
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Cover image for QuoteSmith
QuoteSmith
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Cover image for Development of Healing Mosaic Emotional Well-being App
Development of Healing Mosaic Emotional Well-being App
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Cover image for YouTube Influencer Analytics & Automation Platform
YouTube Influencer Analytics & Automation Platform
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Docker(1)
Usama Zulfiqar's avatar
Usama Zulfiqar
Gujranwala, Pakistan
A senior full-stack developer and AI/ML specialist
A senior full-stack developer and AI/ML specialist
Cover image for VendorInvoiceHub (VIH) is an enterprise-grade
VendorInvoiceHub (VIH) is an enterprise-grade SaaS platform built to streamline vendor invoice acquisition, processing, and contract cost validation for retail chains and convenience store operators. The platform eliminates manual invoice reconciliation by automating invoice ingestion, extracting line-item data, and validating vendor pricing against negotiated contracts. This helps businesses detect overbilling, reduce operational overhead, and gain full transparency into vendor performance while managing multiple organizations within a secure multi-tenant environment. Designed for finance teams, store managers, and operations leaders, VendorInvoiceHub provides a centralized system to manage invoices, vendors, stores, and pricing agreements in one place. The platform supports high-volume invoice processing, AI-powered data extraction, and real-time analytics, allowing businesses to track compliance, identify cost discrepancies, and improve procurement decisions. With cloud-based deployment and scalable architecture, the solution supports enterprise-level workloads while maintaining performance and data isolation across tenants. The system includes automated invoice ingestion via file upload or integrations, AI-powered OCR extraction of invoice data, contract cost validation with variance detection, vendor and store management, proof-of-delivery reconciliation, real-time dashboards and analytics, role-based user access, multi-tenant configuration, exception reporting, Excel and PDF exports, background processing for large workloads, error tracking, and audit logging to ensure reliability and compliance. Built using React, TypeScript, Tailwind CSS, Material UI, Django, Django REST Framework, PostgreSQL, Redis, Celery, AWS S3, Docker, and cloud deployment . A scalable financial operations platform that helps retail businesses reduce vendor overbilling, automate invoice workflows, and gain real-time visibility into procurement and cost performance. #SaaS #EnterpriseSoftware #React #Django #FinTech #RetailTech #InvoiceAutomation #B2BSoftware #CloudApplications #MultiTenant #AIProcessing #BusinessAutomation
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Cover image for Twin Frontend (Lyona App) is
Twin Frontend (Lyona App) is a dual-platform conversational AI application designed to power both web and mobile experiences from a single shared codebase. Built with a modern monorepo architecture, the platform enables real-time AI conversations, voice interactions, and dynamic interface rendering, allowing businesses to deploy scalable conversational products quickly. The system addresses the challenge of building and maintaining separate applications by unifying business logic, UI behavior, and communication layers across platforms, reducing development time while ensuring consistent user experiences. The platform is built for organizations developing AI assistants, customer support tools, SaaS dashboards, or conversational applications that require real-time responsiveness and cross-device synchronization. Users can interact with AI through text or voice, while the interface dynamically adapts based on backend-driven UI configurations. With enterprise-grade performance, secure authentication, and real-time updates, the application supports scalable deployments and continuous feature expansion without rebuilding separate frontends. The application includes real-time AI chat with streaming responses, voice recording and playback for conversational interaction, dynamic UI rendering with dashboards, forms, tables, charts, and interactive components, cross-platform synchronization between web and mobile, push and in-app notifications, secure authentication and session handling, role-based access control, performance optimization with lazy loading and memoization, automatic reconnection and error handling, and shared state management ensuring consistent behavior across devices. Built using React, React Native, TypeScript, Tailwind CSS, Ant Design, Material UI, Redux Toolkit, Socket.IO (http://Socket.IO), Docker, Kubernetes, and modern CI/CD infrastructure. A scalable conversational AI foundation designed to accelerate development of real-time, cross-platform AI applications for enterprise and SaaS environments. #ConversationalAI #React #ReactNative #SaaSDevelopment #AIApplications #RealtimeApps #TypeScript #WebDevelopment #MobileDevelopment #EnterpriseSoftware #Monorepo #ReduxToolkit
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Cover image for Kua Sky is a niche
Kua Sky is a niche e-commerce brand built exclusively for the skydiving community, offering premium performance clothing and gear designed for athletes who demand both function and style in the air. The platform solves a real gap in the market skydiving apparel has historically been generic or limited by delivering sport-specific gear, from freefly jumpsuits to outerwear and accessories, all tailored to the demands of the sport and the identity of the athlete wearing it. What sets this project apart is the custom suit designer, a live interactive coloring application that lets customers design their own jumpsuit and visualize the final product in real time before placing an order. This eliminates purchase hesitation and dramatically improves buyer confidence for high-ticket items. The store also supports custom jersey and face shield orders, a curated catalog of in-stock and sublimated jumpsuits, free shipping incentives, international shipping, gift cards, and a brand ambassador program that drives community-led growth. The platform is built on WordPress with WooCommerce handling the full e-commerce experience, supported by a custom visual product configurator, wishlist functionality, and an integrated account and order management system. Kua Sky is a strong example of a vertical commerce build purpose-built for a passionate niche, with the kind of customization tooling and brand depth that turns first-time buyers into loyal community members. #ecommerce #woocommerce #wordpress #customproductdesigner #nicheecommerce #sportswear #outdoorapparel #skydiving #customclothing #visualconfigurator #brandbuilding #onlineshop #performancegear #webdevelopment #shopdesign
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Cover image for ExpenseMate is a full-stack personal
ExpenseMate is a full-stack personal finance and expense tracking application designed to help individuals manage all their finances in one place. The platform allows users to create multiple accounts, track income and expenses, monitor balances in real time, and visualize spending patterns through interactive dashboards. It solves the common problem of scattered financial tracking by bringing bank accounts, cash, investments, and loans into a single, organized system that is easy to use and accessible from anywhere. The application is built for everyday users, freelancers, and small business owners who need better visibility into their financial activity. With secure user authentication and isolated data, ExpenseMate provides a reliable way to monitor financial health, identify spending trends, and make informed decisions. The clean dashboard, responsive interface, and real-time calculations create a smooth experience while maintaining accuracy across accounts and transactions. Users can create multiple accounts with different currencies, track income and expenses, transfer funds between accounts, manage personal loans, and organize transactions using hierarchical categories. The platform includes advanced filtering, search, and CSV export capabilities, along with interactive charts showing monthly trends and category-based spending. Additional features include drill-down analytics, account balance tracking, dark and light themes, secure authentication, and a responsive data table for managing transactions efficiently. Built using Next.js, TypeScript, Tailwind CSS, shadcn/ui, Supabase, PostgreSQL, Zustand, TanStack Table, and Recharts. A scalable and user-friendly finance tracking solution designed to simplify money management and provide clear financial insights for real-world use. #NextJS #Fintech #ExpenseTracker #PersonalFinance #WebApplication #FullStackDevelopment #TypeScript #Supabase #DashboardDesign #SaaSDevelopment
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Docker(2)
Arham Malik's avatar
Arham Malik
Rawalpindi, Pakistan
Backend & AI engineer who ships systems fast and scale.
New to Contra
Backend & AI engineer who ships systems fast and scale.
Cover image for Imagine having over 100 different
Imagine having over 100 different data sources all over the place. That was the problem Apex Analytics solved. I built this big data platform on Google Cloud using BigQuery and ETL pipelines that clean, transform, and unify everything. The frontend is React based, so stakeholders can see real time KPIs without waiting forever. Queries come back in under a second even with millions of records. It felt like solving a giant puzzle, but the result was a super reliable analytics hub that the entire company trusted. For more details, please visit: https://arham-nexus.vercel.app/work/apexanalytics
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Cover image for This is a classic enterprise
This is a classic enterprise academic portal, but built solid. It uses  Web Forms, ASP.NET, C#, and SQL Server. The main challenge was role based access control because you have admins, faculty, TAs, and lab demonstrators all needing different permissions. I designed a three tier architecture with stored procedures and optimistic concurrency control so data doesn’t get messed up when people edit at the same time. Over 200 users per semester use it for task assignments and progress tracking. It’s not flashy, but it works perfectly. For more details, please visit: https://arham-nexus.vercel.app/work/talabportal
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Cover image for Skill Swap is a peer
Skill Swap is a peer to peer learning platform where you can be both a student and a teacher. I built the backend with Java Spring Boot, real time chat with WebSockets, and video calls with WebRTC. The matching algorithm finds people based on skills, ratings, and availability. You can switch roles anytime. It also has a trust based review system so fake reviews don’t ruin it. This was an MVP, but it proved that real time learning communities can work really well. For more details, please visit: https://arham-nexus.vercel.app/work/skillswap
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Cover image for This is a native Android
This is a native Android app I built with Kotlin and Firebase. It connects tourists with verified local guides in real time. You open the app, see nearby guides, book a tour, and then you can track each other’s location live using Google Maps. I also added offline support because travel doesn’t always have perfect internet. Over 100 active users ended up using it,during the MVP. The best part? Battery usage was optimized so your phone doesn’t die halfway through the day. Really proud of how smooth it turned out. For more details, please visit: https://arham-nexus.vercel.app/work/raaheraast
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Docker(1)