Welcome to my GitHub profile! I’m a Senior Software Engineer at QLAB ENTERPRISE SOLUTIONS with a focus on developing scalable, secure, and efficient applications across various domains, including cybersecurity, machine learning, IoT, and full-stack development. I’m driven by solving complex challenges and pushing the boundaries of software to create impactful solutions.
- Python: Machine Learning, Data Science, Scripting, Web Development (Django, Flask)
- JavaScript/TypeScript: Full-stack development (Node.js, NestJS), Frontend (React, Next.js)
- Dart: Mobile app development (Flutter)
- SQL & NoSQL: Database design and management with PostgreSQL, MySQL, MongoDB
- Other: C/C++ for systems programming, Assembly (NASM) for low-level operations
- Backend: NestJS, Express, Django, Flask
- Frontend: React, Next.js
- Mobile: Flutter
- AI/ML: Scikit-learn, TensorFlow, OpenCV, Streamlit
- Data Visualization: Matplotlib, Seaborn, Plotly
- Containers & Orchestration: Docker, Kubernetes
- CI/CD: GitHub Actions, Jenkins
- Cloud Platforms: AWS, DigitalOcean, Heroku
- Server Management: NGINX, Apache
- Offensive Security: CTFs, Web Exploitation, Steganography, Binary Exploitation (ROP, Heap Overflow, Use-After-Free)
- Defensive Security: Secure coding practices, Authentication/Authorization systems, SSL/TLS, encryption protocols
- Tools: Kali Linux, Wireshark, Burp Suite, Metasploit, Ghidra
A full-stack ISP billing solution, built using NestJS for the backend and React for the frontend. The system features:
- Authentication & Authorization: Role-based access control, secure login mechanisms
- Billing & Payments: Integrated with third-party payment APIs for seamless transactions
- Admin Dashboard: User management, financial reporting, and monitoring capabilities
- Database: PostgreSQL for data integrity and scalability
A Flutter-based application that leverages AI for real-time pest recognition to support agricultural monitoring. Key highlights:
- Machine Learning Integration: Uses a custom-trained model with TensorFlow for pest classification
- Role-Based Dashboards: Different interfaces for surveyors, farmers, and administrators
- Data Visualization: Map-based visualization of pest distribution using geolocation data
- Backend & API: Hosted with Streamlit and a RESTful API for model inference
In addition to building software, I’m passionate about knowledge sharing and mentorship:
- Mentorship: Active mentor at WEMA: Work Experience and Mentorship Academy, guiding students in programming, cybersecurity, and ethical hacking.
- CTF Competitions: Regularly participate in and organize Capture the Flag (CTF) events to deepen practical skills in cybersecurity.
- Cybersecurity Training: Conduct workshops on topics such as OSINT, cryptography, web exploitation, and AI prompt injection.
- Developed a Python-based emotion recognition tool that analyzes facial expressions in real-time. Used OpenCV for image capture, TensorFlow for model inference, and matplotlib for data visualization of trends.
- Application: Assists therapists by providing emotional trend data and relapse prediction based on historical emotional patterns.
- In-depth exploration of Return Oriented Programming (ROP), Heap Overflow, and Use-After-Free vulnerabilities on Ubuntu 18.
- Tooling: Utilized GDB, Ghidra, and pwntools for debugging, analyzing, and exploiting binary vulnerabilities.
- Goal: Build a knowledge base and contribute to secure coding practices and countermeasures.
I’m currently developing my blog, where I dive deep into:
- Advanced tutorials on full-stack development, AI, and machine learning
- Insights and write-ups on cybersecurity challenges and CTF solutions
- Personal experiences, case studies, and lessons learned in the industry
Stay tuned for updates on ndegwa.github.io
- Email: ndegwaofficial@gmail.com
- LinkedIn: linkedin.com/in/brianndegwa
- GitHub: Follow my work here on GitHub
I’m open to collaborations, discussions on emerging tech, and sharing insights. Feel free to reach out!