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ShaySapozhnikov/README.md

πŸ‘‹ Hi, I'm Shay Sapozhnikov!

Computer Science Student and Math Minor @ University of Winnipeg
Founder @ GlitchLabs


About Me

I'm a Computer Science student with a deep curiosity for how mathematics underpins modern security systems. I'm especially passionate about leveraging cryptographic theory and analytical thinking to understand, break down, and strengthen how we protect digital systems.

Currently building tools at the intersection of security research and mathematical modeling β€” from analyzing vulnerabilities to exploring the formal structures behind encryption and network protocols.

Founder of GlitchLabs β€” a gamified cybersecurity learning platform designed to make security education hands-on, engaging, and accessible. Think capture-the-flag meets structured curriculum.

Pursuing a minor in Mathematics to sharpen my foundation in number theory, discrete math, and the formal reasoning that cybersecurity is built on.

My mission: To bridge rigorous mathematical thinking with applied security, and build platforms that make that knowledge available to everyone.


Cybersecurity & Math Stack

  • Languages – Python, Go, Bash, JavaScript, TypeScript, C
  • Frameworks & Web – Svelte, SvelteKit, React, Next.js, Node.js, Express, Fiber (Go)
  • Penetration Testing – Metasploit / msfconsole, msfvenom, Netcat, Hydra, SQLmap
  • Reconnaissance & Analysis – Nmap, Wireshark, Burp Suite, Gobuster, theHarvester
  • Cryptography & Security – RSA, AES, hashing algorithms, PKI, TLS/SSL
  • Mathematics – Number theory, linear algebra, discrete math, probability
  • Scripting & Automation – Python, Go, Bash, Scapy, socket programming
  • Data & Modeling – NumPy, SciPy, Matplotlib, Jupyter Notebooks

Projects & Research

GlitchLabs (Currently Building)

A gamified cybersecurity learning platform built to make security education hands-on and fun. Features CTF-style challenges, structured learning paths, and real-world scenarios β€” designed for beginners and seasoned hackers alike.
Role: Founder & Lead Developer

An ML-driven tool for classifying elemental signatures using random forest models and spectral data. Combines physics, machine learning, and scientific computing in one pipeline.

More coming soon β€” stay tuned!


Tech Interests

  • Penetration Testing – Metasploit Framework, exploit development, post-exploitation, pivoting
  • Cybersecurity – Network security, vulnerability analysis, CTF competitions
  • Applied Math – Cryptographic algorithms, graph theory, formal proofs
  • EdTech & Gamification – Building engaging, interactive learning experiences
  • Security Scripting – Python, Go, Bash, packet crafting, payload generation
  • Web Dev – Svelte, SvelteKit, React, Next.js, Node.js, Express
  • General – Git/GitHub, VSCode, Linux, Docker, Kali Linux

Let's Connect

I'm always open to chatting about security, math, software, or research.

GlitchLabs
LinkedIn
Email


"Security without mathematics is just wishful thinking." – Bruce Schneier

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  1. PlasmaSpec-V1.0 PlasmaSpec-V1.0 Public

    tool for analyzing and visualizing elemental plasma spectra using multiple machine learning models. It processes spectral data, predicts elemental composition, compares results to reference spectr…

    Python

  2. Lift-off-ctf Lift-off-ctf Public

    JavaScript