Cloud Security Operations Orchestrator

Security Analytics Engine - Anomaly Detection in Web Traffic

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

Autonomous Python-based offensive security engine for AI-driven attack path prediction, multi-agent red team simulation, and risk scoring.

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.

🛡️ 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.

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

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

Server sizing and log ingestion monitoring for Wazuh with automated HTML reports and graphs.

Defensive detection pipeline for abnormal account behavior (ATO, token abuse)

Offline-first RMF / NIST 800-53 log detection and executive reporting pipeline (auditable outputs).

Full Splunk App for Bitsight Security Ratings. Monitor and visualize security ratings, portfolio companies, alerts, findings, exposed credentials, users, and threat intelligence from the Bitsight API.

AI-powered dashboard for global cyber threats, trends, and defense.

Azure SDK-compliant Python client library for aggregating logs from multiple Microsoft Sentinel workspace

SOC-style Django app to ingest auth logs, detect brute-force attacks, generate alerts with MITRE mapping, export PDF incident reports, and serve an API.

AI-driven cybersecurity research project combining machine learning–based anomaly detection with a blockchain-backed threat intelligence system for secure, transparent, and reproducible cyber threat analysis.

Audit-ready security analytics on encrypted telemetry with hardware-backed isolation, attestation-gated keys, and immutable query logs. Alpha demo ready.

A hands-on project focused on detection-driven threat hunting using hypothesis-based analysis and log-derived signals.