I secure cloud-connected applications, investigate suspicious activity, and build security automation across cloud and application environments. I maintain live production platforms, build detection and investigation projects, and teach hands-on cybersecurity.
Note
Open to: Cloud Security Engineer and Cloud Security Analyst roles, cloud detection engineering roles, security automation projects, and freelance engagements.
| ☁️ Cloud | AWS, Microsoft Azure |
| 🔍 Detection & investigation | MITRE ATT&CK, SIEM, threat hunting, network forensics |
| 🛡️ Security engineering | Application security, DevSecOps, Kubernetes, WAF |
| ⚙️ Automation | Python, TypeScript, Node.js, REST APIs, CI/CD |
I built and integrated security into three live platforms and maintain them part-time (about 1–3 hours a day): checking availability, troubleshooting technical and security issues, fixing identified flaws, and implementing owner-requested updates.
| Platform | Reach | Security work |
|---|---|---|
| EVS Healthcare Recruitment platform with CV uploads |
10,000+ visitors in ~6 weeks |
Cloudflare WAF, bot and DDoS mitigation, HTTPS/TLS, security headers, input validation, secure CV upload handling, SPF/DKIM/DMARC Repository |
| Rasoaf Travels & Tours Travel platform |
3,000+ visitors in ~8 weeks |
Cloudflare protections, security headers and TLS, Semgrep, Gitleaks, npm audit, OWASP ZAP, GitHub Actions security workflows Repository |
| TV-Tay Donation platform with real transactions |
5,000+ visitors in ~3 months |
Cloudflare WAF, bot mitigation, DDoS protection, rate limiting; application, API and AWS security for the donation workflow Repository |
Personal projects and labs, not client deployments.
A multi-cloud detection pipeline that brings cloud and Kubernetes audit data into one investigation workflow.
- Ingests and normalizes events from AWS CloudTrail, Microsoft Entra ID, and Kubernetes audit logs
- Maps activity to MITRE ATT&CK
- Applies configurable YAML detection rules with severity and confidence scoring
- Exposes results through an API and a PostgreSQL/Supabase dashboard
- Generates recommended response actions
Scope: produces recommendations only; automated remediation is not implemented. ▶ Demo walkthrough
TypeScript Node.js Express React AWS SDK Azure Identity PostgreSQL Supabase
Microsoft Sentinel alerts drive Azure Logic App workflows that call AWS Lambda over OIDC, with no long-lived credentials. Confirmed working end-to-end in lab.
| Azure | AWS |
|---|---|
| Sentinel and KQL for detection | Lambda (Python) for response logic |
| Logic Apps for orchestration | DynamoDB for idempotency |
| Entra ID and Graph for identity response | SES for notifications |
SOC Tier 3-inspired orchestration playbooks, iterated across many versions to explore alert enrichment, investigation, and controlled response.
- Threat-intelligence enrichment with VirusTotal and AbuseIPDB
- Integrations with Azure Key Vault, Service Bus, and ServiceNow
- Approval gates before sensitive identity-containment actions
Status: 🚧 In progress · Live development site
An AI-assisted investigation platform that brings multi-model orchestration, threat intelligence, and controlled tool execution into one workflow for URL and IP investigations. Instead of relying on a single model or an isolated reputation lookup, it coordinates five AI models and grounds their analysis in external evidence, while keeping control over which tools the AI can invoke.
- Multi-model orchestration: coordinates five AI models within the investigation workflow to explore how different models contribute to security analysis
- Threat-intelligence integration: VirusTotal, AbuseIPDB, Censys, ThreatFox, SecurityTrails, IPinfo, ViewDNS, Shodan, and Mozilla Observatory, added incrementally
- Controlled tool execution: a tool registry and tool-use policy define the available tools and govern how the agent invokes them, rather than allowing unrestricted execution
- Evidence-led assessments: tool calls gather observable intelligence, so findings rest on evidence rather than model assertions alone
- Structured output: results are organised so findings can be reviewed alongside their supporting evidence
- Access control: authentication, authorisation, and data-protection considerations built into the platform
JavaScript Node.js REST APIs Tool registry Policy enforcement Threat intelligence
Scope: under active development; integrations are subject to ongoing implementation and validation. It is not a fully autonomous SOC, a production-validated detection platform, or an automated remediation system.
Investigation of packet-capture evidence from a controlled lab, reconstructing a multi-stage attack. ▶ Video walkthrough
- Analysed HTTP, TCP, DNS, and SSH traffic in Wireshark
- Identified reconnaissance, SQL injection attempts, webshell upload, reverse-shell execution, and attempted unauthorised SSH access
- Extracted IOCs, built an event timeline, and mapped techniques to MITRE ATT&CK
- Documented evidence, methodology, and findings in a forensic report
Wireshark Gobuster SQLMap SHA-256 IOC extraction MITRE ATT&CK
Investigation of suspicious network activity and potential data exfiltration, using threat-intelligence enrichment, SIEM techniques, and MITRE ATT&CK mapping.
Educational lab exploring phishing campaign configuration and email delivery. Not an authorised engagement with any organization. ▶ Video demonstration
| Project | What it covers |
|---|---|
| AWS Security Automation | Python/Boto3 checks for insecure IAM, S3, EC2, KMS, and CloudTrail configurations. |
| Secure Kubernetes Deployment | Non-root containers, RBAC, network policies, OPA Gatekeeper admission control, Trivy and Gitleaks scanning, CI/CD validation. |
| PCI-Aware Cloud Security Architecture | Least-privilege IAM, encryption and key management, STRIDE threat modelling, Zero Trust. An architecture project, not a PCI DSS certification or audit. |
| Domain | Technologies |
|---|---|
| Cloud security | AWS (IAM, CloudTrail, KMS, Lambda, API Gateway, S3, Boto3), Azure (Sentinel, KQL, Logic Apps, Entra ID, Key Vault) |
| Detection & investigation | Detection rules, MITRE ATT&CK, alert triage, log analysis, IOC extraction, timeline reconstruction |
| Network forensics | Wireshark, PCAP analysis, HTTP, TCP, DNS, SSH |
| Threat intelligence | VirusTotal, AbuseIPDB, URL and IP reputation analysis |
| Application security | OWASP ZAP, Semgrep, API security, input validation, security headers |
| Web protection | Cloudflare WAF, rate limiting, bot mitigation, DDoS protection, TLS |
| DevSecOps | GitHub Actions, Gitleaks, npm audit, Trivy, CI/CD controls |
| Cloud-native | Kubernetes, container hardening, RBAC, NetworkPolicy, OPA Gatekeeper |
| Automation | Python, TypeScript, Node.js, REST APIs, OIDC |
| Threat modelling | STRIDE, attack-chain analysis |
| Credential | Year |
|---|---|
| Kubernetes and Cloud Native Associate (KCNA) | 2026 |
| Cisco Junior Cybersecurity Analyst Career Path | 2025 |
| HND, Science Laboratory Technology (Chemistry), Upper Credit, Yaba College of Technology | 2023 |
| Ethical Hacking training | 2024 |
Training completed (not certifications): AWS Cloud Practitioner learning path (AWS Skill Builder, 2025) and AWS Solutions Architect Associate preparation (Udemy).
I run Lakewest Cybersecurity Academy, creating hands-on resources on SOC alert investigation, network forensics with Wireshark, and threat detection and incident-investigation methodology.
