$ whoami
Maaz Husain_
// Cybersecurity Analyst
Senior Quality Engineer transitioning into Cybersecurity. 5+ years delivering secure, cloud-native applications at enterprise scale. Currently pursuing MSc Cybersecurity at the University of Surrey. Building hands-on DFIR and SOC tooling along the way.
5+
years exp.
9
certifications
1
published paper
01 / work history
~/experience
Oct 2020
– Dec 2025
– Dec 2025
Senior Quality Engineer
LTIMindtree · Mumbai
- Spearheaded QA & cloud deployment for an American Insurance client – achieved 25% reduction in FTE headcount through process automation.
- Managed Functional, API and Automation test suites; implemented robust pipeline & API workflows increasing system reliability by 45%.
- Led offshore team coordinating with client, cutting requirement turnaround by 2 days per sprint.
- Implemented CI/CD optimisations including automatic trigger mechanisms and environment decoupling – reduced deployment time by 35%.
- Drove a 50% faster issue resolution rate through structured troubleshooting and proactive support.
- Maintained in-depth documentation for cloud infrastructure, APIs and test configurations; streamlined team onboarding.
02 / open work
~/projects
ThreatLens
↗
Full-stack blue-team threat-intelligence platform — ingest, enrich, score, correlate and investigate IOCs end to end. FastAPI backend with JWT auth, role-based access control and audit logging; a React + TypeScript dashboard with an interactive threat graph. Runs fully offline on a deterministic mock feed, with AbuseIPDB, VirusTotal and OTX activating when API keys are set.
Phishing Email Analyzer
↗
CLI tool that pulls apart a suspicious email the way a SOC analyst would: SPF/DKIM/DMARC checks, Received-chain tracing, IOC extraction & defanging, static attachment inspection — and an explainable risk score where every point traces to a named finding. Static analysis only; no link is fetched and no attachment is run.
Docker Security Pipeline
↗
Hands-on DevSecOps pipeline that hardens a Flask app from build to ship: a multi-stage, non-root Docker build on digest-pinned base images, a Trivy CI gate that fails on vulnerable layers, plus SBOM generation with Syft and Docker Scout scanning — security shifted left into the build itself.
Network Segmentation Advisor
↗
Turns an Nmap scan or YAML inventory into a least-privilege segmentation plan. Classifies each host by role and sensitivity, groups them into security zones, and outputs the allow/deny rules needed to enforce them — network threat modelling reduced to a repeatable command.
Memory Forensics Investigation
↗
Repeatable DFIR workflow built on Volatility 3 — memory image in, integrity-verified evidence pack out. Triages captured RAM for malicious processes, injected code, C2 traffic and persistence, then produces MITRE ATT&CK-mapped, evidence-led investigation reports across four worked cases.
03 / capabilities
~/skills
# cybersecurity
# languages
# cloud & devops
# testing & qa
# leadership
# machine learning
04 / credentials
~/certifications
ISC2
CC
CC
ISC2 Certified in Cybersecurity
ISC2
GOOG
CYBER
CYBER
Google Cybersecurity Professional Certificate
Google
THM
SEC1
SEC1
Cyber Security 101 (SEC1)
TryHackMe
AZ
400
400
AZ-400: DevOps Engineer Expert
Microsoft Certified
AWS
SAA
SAA
Solutions Architect – Associate
Amazon Web Services
AZ
104
104
AZ-104: Azure Administrator
Microsoft Certified
DP
203
203
DP-203: Azure Data Engineer
Microsoft Certified
AZ
900
900
AZ-900: Azure Fundamentals
Microsoft Certified
DP
900
900
DP-900: Azure Data Fundamentals
Microsoft Certified
05 / testimonials
~/references
He has great communication skills, and is thorough in troubleshooting the issues that come up in our system. He is reliable and does a consistently good job. I would highly recommend him!
His work in validating/testing applications was top notch — I can always rely on his skills to deploy functionality with the highest quality. He was instrumental in creating automation plans and scripts for multiple applications. A great asset to any team he joins.
Maaz single-handedly drove an entire application's testing across all aspects — database, functional, UI automation and API automation. He was excellent in client communication and built great rapport with the customer within months of joining, while mentoring juniors and taking on work outside his project. His work has been exemplary — a great addition to any team he joins.
Maaz is a very hardworking and dependable QA professional, great at both functional and automation testing. He brings consistency and can always be trusted to deliver high-quality results. What really stands out is his eagerness to learn — always excited to pick up new skills. Helpful, supportive, and with a strong sense of ownership.
Maaz has strong knowledge of automation, performance and manual testing. He's friendly by nature and helps others complete their work — straightforward, honest, and able to handle any kind of pressure while coordinating with the client.
An excellent QA professional with strong attention to detail and a clear understanding of product quality. His dedication helped the team deliver reliable and high-quality releases.
06 / academic
~/education
MSc Cybersecurity
University of Surrey
Feb 2026 – Present
BE Information Technology
M.H. Saboo Siddik College of Engineering, Mumbai
2016 – 2020
// research · Springer 2020
Stock Market Prediction using Machine Learning
Intelligent Computing, Information and Control Systems · ICICCS 2020
LSTM model for stock price prediction combined with NLP-based sentiment analysis, achieving ≤30 RMSE. Co-authored with A. Shaikh, A. Panuganti & P. Singh. Implemented in Python using Jupyter Notebook.
↗ View on SpringerLink