This project documents how to analyze cybersecurity data with machine learning tools and techniques in python. The tutorials run in Jupyter Notebooks and depend on the environment described in the environment.yml file.

Official GitHub profile of Sagar Biswas (SagarBiswas-MultiHAT) — a CSE student at AIUB, cybersecurity enthusiast, ethical hacker (web application security), and web developer. Showcases open-source tools, learning notebooks, security projects, blogs, and community work.

A curated, well-organized collection of Jupyter notebooks and PDF notes covering Bash, C, C++, CyberSecurity, JavaScript, PHP, Python, React, Tools, Git & GitHub and Tips & Tricks. Each notebook includes runnable code cells, step‑by‑step explanations, examples, exercises, and resources for learners and developers to practice and reuse.

Tool and Jupyter Notebook used in "Enhance Investigations Using LLM, Embeddings, and Clustering" SANS AI Cybersecurity Summit talk.

Personal cybersecurity wiki and lab notebook tracking my journey from zero to junior penetration tester, with structured Markdown notes, labs, and references used daily while studying on TryHackMe, HackTheBox, and other platforms.

Repository of Jupyter notebook tutorials for teaching the Machine Learning in Cybersecurity Course at the Saarland University, WiSe 2025/26

Notebooks exploring the Canadian Institute of Cybersecurity's IoT dataset.

This repository contains hands-on Jupyter notebooks for learning threat intelligence analysis using CIRCL's open source tools and services. The workshop covers essential platforms and APIs for cybersecurity professionals and researchers.

Machine learning notebooks using cybersecurity data

This repository contains the project I developed for the Machine Learning Security course (Cybersecurity Master’s Degree) at Sapienza University of Rome during my Erasmus semester. The full notebook is available on Kaggle: https://www.kaggle.com/code/vaggelisarg13/phishing-emails-gan

personal notebook for cybersecurity research and studies

Cybersecurity Research Jupyter Notebooks for the Community

Notebook for Cybersecurity and Algorithm

Python Notebooks; two companion notebooks: "The Pythonic Odyssey" (core Python: basics → OOP, file I/O, virtualenvs, advanced patterns) and "Python for CyberSecurity" (security tooling + hands-on projects). Includes practical projects (MAC changer, Netcat automation, multi-mode Nmap scanner, educational keylogger, etc).

Analysis of the CICDDoS2019 dataset for studying DDoS attacks. Includes data preprocessing, exploratory data analysis (EDA), CNN model for attack detection, and performance evaluation. The repository provides scripts, notebooks, and results to aid in cybersecurity research.

ML & Security experiments

Practical Cybersecurity Notebook Vault; A curated collection of PDF notebooks and hands-on guides covering networking, DNS, Google Dorks/OSINT, phishing, SOC workflows, red/blue fundamentals, and career paths. Built for beginners→intermediate learners with direct PDF links, study roadmap, example commands, and a GitHub Pages site for easy browsing

Notebooks and projects on cybersecurity in general

A repository to centralise Jupyter Notebook about Cybersecurity

Complete cybersecurity project with machine learning threat detection, data analysis notebooks, and interactive Streamlit dashboard. Includes full dataset and ML models.

This notebook demonstrates creating and working with tuples, including examples of how immutability can help protect data integrity in cybersecurity scenarios like access control lists (ACLs) or trusted software lists.

Exploratory Data Analysis of cybersecurity attack records with visual insights and an interactive Streamlit dashboard. Includes data cleaning, trend analysis, and key attack pattern identification along with dashboard screenshots and analysis notebook

Private repo for my GWU doctoral praxis “Leveraging AutoML for Advanced Network‑Traffic Analysis & Intrusion Detection.” Holds notebooks, code, models, and appendix artifacts. Will become public after my 2025 defense to foster open, reproducible cybersecurity + AutoML research.

🔍 Login Anomaly Detection: Isolation Forest detects brute-force attacks in 1,000 login events. Engineered time gap/user/IP features. Flagged 50 anomalies (5%). Python • pandas • scikit-learn • matplotlib. Cybersecurity ML project for Rapid7 SE-II AI Engineer role. GitHub: full notebook + plot.

Notebook for the sci-MI CSMP cybersecurity lab

Defensive Cybersecurity Notebooks: EN

Ai 4 Cybersecurity Notebooks

Some notebooks on cybersecurity

Machine learning notebooks using cybersecurity data

Jupyter notebooks demonstrating cybersecurity concepts, network scanning, and vulnerability analysis.