I investigate breaches, reverse-engineer malware, and build tools that turn invisible threats into something you can actually see.
I graduated with First Class Honours in Cybersecurity & Forensic Computing from the University of Portsmouth in 2026. Along the way, I reverse-engineered malware, built OSINT tools from scratch, and spent plenty of time breaking vulnerable web apps before learning how to fix them properly.
The thing I enjoy most is the investigative side of security, where you're pulling apart evidence to understand what actually happened, whether it's hidden inside a binary, buried in a network capture, or buried in a dodgy crypto website. I also spent a summer interning with a cybersecurity and information systems team in Saudi Arabia, and I'm currently working through my CompTIA Security+.
Final year dissertation · 2026
A four-layer OSINT framework, covering infrastructure, content, social footprint, and blockchain, that investigates suspicious crypto websites and scores them with a trained classifier instead of a black-box yes or no.
Malware forensics coursework · 2025
Full static, dynamic, and reverse-engineering analysis of a live malware sample. Uncovered its C2 channel, registry persistence, and screen-capture spyware behaviour, then mapped each capability to its exact API call.
IoT security build · 2026
A low-cost Arduino device that turns invisible network attacks into something you can see and hear, with an LED, an LCD readout, and a buzzer that go off the moment a port scan or rogue device hits the network.
Vulnerability research · 2025
Fixed a real command-injection bug, used Google dorking for OSINT recon, chained a file-upload flaw into a reverse shell, and mapped three live WooCommerce CVEs to the OWASP Top 10, then rooted a TryHackMe box end to end.
Independent research · Part 1 of 2
A diagnostic evaluation of current phishing detection tools against authentic Arabic-language phishing content. Tested 100 verified Arabic phishing samples across VirusTotal, Google Safe Browsing, heuristic keyword filters, and a BERT-based NLP classifier, revealing critical detection gaps that leave 300M+ Arabic speakers exposed.
Independent research · Part 2 of 2
A national-scale impact analysis extending the Part 1 findings to Saudi Arabia's Vision 2030 digital transformation. Examines the specific risks to government digital platforms, financial services, and critical infrastructure as the Kingdom's SAR 15.2 billion cybersecurity market faces an expanding attack surface with inadequate linguistic defences.
A short essay on how whaling attacks, phishing aimed at executives, can be prosecuted under UK fraud law, with real cases including Ubiquiti Networks and Mattel.
Read PDF ↗A critical review of the human rights concerns raised by AI-driven content moderation on social media, covering freedom of expression, privacy, and bias.
Read PDF ↗A reflective comparison of ChatGPT and Qwen for SME-focused cybersecurity advisory tasks, covering prompting technique, hallucination risk, and where each model held up.
Read PDF ↗