SOC Analyst (Apprenticeship)
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I’m a Cybersecurity and Computer Forensics graduate with First Class Honours and currently working as a SOC Analyst Apprentice. My focus is on threat detection, incident response, and using AI-driven automation to make security operations more efficient.
In the past month, I’ve been developing projects with Microsoft Sentinel, Sumo Logic, Suricata IDS, and custom threat intelligence workflows. These include integrating APIs, AI models, and automation tools to reduce investigation time and improve SOC efficiency. I enjoy blending technical depth with creative problem-solving, whether that means analysing malware or building streamlined workflows.
I’m always open to connecting with others in cybersecurity, AI, and tech to share knowledge, collaborate, or exchange ideas.
I am a Cybersecurity and Computer Forensics graduate with First Class Honours, currently gaining hands-on experience as a SOC Analyst Apprentice. My work centres on threat detection, incident response, and security monitoring, with a growing specialisation in SIEM platforms such as Microsoft Sentinel and Sumo Logic.
Over the past month, I have developed and deployed projects involving:
Threat Intelligence & Automation – building AI-driven workflows that collect, enrich, and analyse IOCs from sources like VirusTotal, AbuseIPDB, GreyNoise, and ThreatFox.
SIEM & Detection Engineering – writing and tuning custom KQL detection rules, creating scheduled rules, and streamlining triage in Microsoft Sentinel.
Network & Host Security – analysing traffic with Wireshark and Suricata IDS, deploying honeypots (Cowrie) and Canarytokens, and integrating findings into detection pipelines.
Vulnerability Management – using Nessus/Tenable to scan and prioritise risks with CVSS scoring.
My approach combines technical depth with automation to cut investigation times and reduce manual workloads, while keeping humans in the loop for accuracy.
BSc (Hons) Computer Forensics and Security – First Class Honours, Canterbury Christ Church University.
This degree provided a strong foundation in digital forensics, cybersecurity, and computer science. Key areas included malware analysis, ethical hacking, network security, and cryptography. My final-year dissertation focused on detecting deepfake images created by AI generative models, combining research, dataset development, and applied machine learning.
