Open security analytics. Understand, monitor, and protect your product from cyber threats, account takeovers, bots and abuse.

Cloud Security Operations Orchestrator

vPrioritizer enables us to understand the contextualized risk (vPRisk) on asset-vulnerability relationship level across the organization, for teams to make more informed decision about what (vulnerability/ties) they should remediate (or can afford not to) and on which (asset/s)

Security Analytics Engine - Anomaly Detection in Web Traffic

Detection of network traffic anomalies using unsupervised machine learning

Digital Twin Driven Security Analytics for the Industrial Internet of Things.

Plug into extended SecOps: Bring Google Cloud's analytics to your local network. tshark captures on-prem, GCP transforms to UDM. Scalable, event-driven, via Terraform.

This repository contains an end-to-end walkthrough to leverage Google Cloud services to demonstrate Solution Accelerators for few business domains

Production-ready authentication framework that saves you weeks of development. Features enterprise-grade security: 2FA/TOTP, LDAP integration, intelligent rate limiting, session fingerprinting, brute-force protection, security analytics dashboard, comprehensive audit logging, and granular role-based access control.

Splunk project analyzing simulated Linux syslog data to detect brute-force login attempts, error rate anomalies, escalated warnings, and correlated security events. Demonstrates advanced SPL, time-window correlation, lookup-based classification, and real-world SOC/SRE insights through storytelling dashboards.

Research SOC testbed for alert correlation and noise reduction. Zeek + Wazuh + Elastic. Includes generated attack telemetry, detections, metrics, and reproducible experiments

🛡️ CyberSentinel – Threat Intel + Log Correlation Dashboard. An analyst-grade security tool that ingests threat intelligence, parses SSH/Apache logs, correlates IOCs, and generates real-time alerts.

Python tool for turning noisy system logs into actionable security intelligence.

🔐 Malware Detection System using classical ML models to classify and detect malicious software based on behavior and feature patterns.

Offline-first, budget-aware log+CTI pipeline with optional LLM enrichment; grouping/sampling gates, strong CTI cache, reproducible reports, Streamlit UI.

⚠️ Description only - code is confidential. AI-powered threat intelligence aggregator for OSINT and dark web data, with ML-based IOC classification.

ML-based Intrusion Detection System using NSL-KDD. Includes preprocessing, feature engineering, Random Forest model (AUC 0.96), ROC curve, FastAPI prediction API, and a real-time intrusion analysis dashboard.

Hands-on Cowrie SSH honeypot project capturing attacker behavior and SSH intrusion attempts. Built for learning threat detection, logging, and security analytics.