Cybersecurity (SOC) Learner | Python Automation | Applying ML to Security & Threat Detection
I’m a B.Tech student specializing in AI & Data Science, focused on building a career in cybersecurity—especially SOC operations, threat detection, and Python-based automation. I actively build security tools, experiment with ML models for anomaly detection, and study log analysis, SIEM workflows, and web security.
Alongside cybersecurity, I work on full-stack development to stay industry-ready and deliver real, deployable projects. My goal is to combine security, automation, and machine learning to create efficient, scalable, and practical solutions for real-world environments.
An intelligent automation tool designed to assist SOC teams with faster alert handling.
Includes modules for log parsing, IOC enrichment, case tagging, alert triage, and planned ML-based anomaly scoring.
Tech: Python, Pandas, Regex, REST APIs, Scikit-Learn
Focus: SOC workflow automation, alert reduction, ML-assisted triage
A machine-learning model that analyzes URLs and predicts whether they are legitimate or phishing using feature extraction and classification algorithms.
Tech: Python, Scikit-Learn, Pandas, Feature Engineering, Flask (optional API)
Focus: ML security application, threat detection, automation for Blue Team
A lightweight log monitoring system that ingests and analyzes system logs, auth logs, and network logs, with alert rules and basic correlation engine.
Tech: Python, Regex, JSON, Filebeat-style parser
Focus: Blue Team operations, log analysis, SIEM fundamentals
- Strengthening SOC analysis skills and real-time security monitoring
- Improving incident response methodology and threat investigation workflow
- Building Python tools for security automation and log analysis
- Enhancing skills in network security, vulnerability assessment, and hardening
- Expanding knowledge in threat intelligence and adversary behavior patterns