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Denis Aptula's avatar
Denis Aptula
London, UK
🌐 Expert Cloud Security Solutions
🌐 Expert Cloud Security Solutions
Cover image for Azure Sentinel Security Monitoring
Azure Sentinel Security Monitoring
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Cover image for Comprehensive Azure and SIEM Deployment
Comprehensive Azure and SIEM Deployment
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12
Cover image for Implementation of Cloud Security Controls
Implementation of Cloud Security Controls
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ibukun Babalola's avatar
ibukun Babalola
Lagos, Nigeria
SOC Analyst |M365 · SIEM · Security Engineer · AI Automation
SOC Analyst |M365 · SIEM · Security Engineer · AI Automation
Cover image for Deployed a cloud-native SIEM integrating
Deployed a cloud-native SIEM integrating Microsoft Azure infrastructure, Windows endpoints, Microsoft 365, and Defender XDR telemetry into a unified detection and response platform. Wrote KQL analytics rules for real-time threat detection covering: privilege escalation, suspicious PowerShell execution, lateral movement via RDP and SMB, anomalous Azure AD sign-ins, and malware execution patterns. Automated incident response using Azure Logic Apps. Reduced log ingestion costs by 20% through optimised data collection, balancing coverage against cost without losing detection fidelity. Published full write-up on Medium: medium.com/@babsib2dk
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Cover image for Performed a read-only Microsoft 365
Performed a read-only Microsoft 365 security assessment for an 11-user UK logistics company, uncovering two Critical findings: MFA disabled on Global Administrator accounts and an active email forwarding rule on the Finance Manager's mailbox consistent with Business Email Compromise. Delivered a clear priority action plan, all remediable within 72 hours using tools already included in the client's existing M365 licence along with SharePoint sharing controls and Conditional Access policy configuration to close legacy authentication gaps.
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Cover image for Conducted a full cybersecurity risk
Conducted a full cybersecurity risk assessment for NexaSoft's AWS EKS-hosted Employee Self-Service HR Portal, processing sensitive employee PII including payroll, health records, and government-issued ID. Identified three Critical and five High risks across Azure AD SSO, cloud IAM configuration, and insider privilege controls, aligned to ISO 27001. Delivered a prioritised 90-day remediation roadmap using native AWS and Azure tooling, reducing all Critical risks before go-live and supporting the client's ongoing ISO 27001 certification obligations under Australia's Privacy Act 1988.
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Cover image for Delivered a GRC-aligned cybersecurity risk
Delivered a GRC-aligned cybersecurity risk assessment for an Azure-hosted AI-Driven HR Analytics Service processing employee PII and behavioural data. This engagement went beyond conventional security reviews to address AI-specific risks including data poisoning and model bias that carry direct legal exposure under the Canadian Human Rights Act and the proposed AI and Data Act (AIDA). Identified five High risks and produced a mitigation strategy using Azure-native controls, alongside governance recommendations to ensure compliant and auditable AI decision-making ahead of AIDA enforcement.
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Ahmad Mustafa's avatar
Ahmad Mustafa
Lahore, Pakistan
GIS & Python Developer | Geospatial AI Specialist
New to Contra
GIS & Python Developer | Geospatial AI Specialist
Cover image for Built a modern Web GIS
Built a modern Web GIS application for interactive spatial analysis, map visualization, and geospatial data comparison. The platform integrates mapping technologies, satellite imagery, and location-based analytics to help users explore geographic data and make informed decisions. Developed using GIS workflows, Python, and web mapping technologies for a responsive and user-friendly experience.
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Cover image for 🗺️ Web GIS for Field
🗺️ Web GIS for Field Operations & Location-Based Data Collection I developed an interactive geospatial platform designed to help teams visualize, manage and update field-work information directly on a map. The application combines Web GIS, satellite imagery, spatial data management and field reporting in a single workflow. Key capabilities include: • Interactive field map with spatial work areas • Color-coded work / prescription classifications • Multiple GIS sub-maps and project views • Satellite and OpenStreetMap basemap switching • Work completion and status tracking • Location-based field-point creation • GPS coordinate capture • Field categorization and notes • Photo attachment support for field observations • Map-based project and team workflows The goal is to replace disconnected field records with a centralized spatial workflow, where teams can see exactly where work is required, record observations from the field, and maintain geographically accurate project information. Built around Web GIS, spatial databases and interactive mapping. Interested in projects involving GIS development, field-data collection, asset management, spatial dashboards and geospatial workflow automation.
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Cover image for 🚗🌍 Can a navigation system
🚗🌍 Can a navigation system recommend the most fuel-efficient route instead of simply the shortest one? This project was developed as part of my MPhil Remote Sensing & GIS thesis. I designed and developed an intelligent Web GIS routing system that generates and compares four alternative routes between an origin and destination and recommends the most suitable route using a Multi-Criteria Decision-Making (MCDM) approach. Instead of considering only distance, the system evaluates multiple factors such as: • 🌱 Fuel-efficiency / environmental suitability • ⏱ Travel duration • 🚧 Road hurdles and route conditions • 📏 Travel distance The alternatives are evaluated using a TOPSIS-based decision model, allowing the system to identify the route with the best overall balance rather than simply choosing the shortest path. I also integrated an AI assistant that explains route recommendations in natural language, helping users understand why one route is preferable to the alternatives. Key features: • Interactive Web GIS navigation • Four-route generation and comparison • MCDM/TOPSIS route ranking • Fuel-efficient route recommendation • Route distance and travel-time analysis • Road-condition / hurdle consideration • AI-generated route explanations • Interactive route visualization • Decision-support interface for sustainable mobility Built with Python, Django, GIS, Leaflet/OpenStreetMap, MCDM and AI integration. This research explores how GIS + decision science + AI can support smarter and more sustainable urban mobility.
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Cover image for 🛰️ AI-Powered Building Detection &
🛰️ AI-Powered Building Detection & Human-in-the-Loop GIS A look at a geospatial AI platform I developed for detecting, reviewing, and managing building footprints from satellite imagery. The workflow combines GeoAI, GIS and human validation to turn AI predictions into reliable geospatial datasets. In this demo: • AI-based building footprint detection • Interactive satellite imagery and GIS mapping • Building polygon visualization • Confidence-based AI predictions • Accept / reject prediction workflow • Manual correction of detected footprints • Human-reviewed labels for future model improvement • Geospatial coordinates and building-level data management The goal is to create a scalable workflow where AI performs the initial mapping while human review improves accuracy and provides better training data for subsequent model versions. Built around GIS + GeoAI + computer vision + satellite imagery. Always interested in connecting with people working in GIS, GeoAI, remote sensing, mapping and spatial AI.
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