Projects
Technical work at the intersection of security and infrastructure
ML-Based Anomaly Detection in DevSecOps Pipelines
Built a Python service that applies machine learning to real-time log analysis, detecting security threats that rule-based approaches miss.
Tech Stack
Key Features
- Real-time anomaly detection with 30-second detection windows
- 10 attack scenarios designed to evaluate ML detection vs rule-based approaches
- Measuring precision, recall, and false positive rates
- Focus on reducing false positives while maintaining high threat detection
A Python service that reads log data from Graylog, scores it with an Isolation Forest model, and flags anomalous pipeline activity that rule-based alerting was never written to catch.
Secure Auto-Scaling AWS Infrastructure
Production-ready AWS infrastructure using modular Terraform: VPC, load balancing, auto-scaling, and monitoring, all as code.
Tech Stack
Key Features
- Multi-AZ VPC with public/private subnets
- Application Load Balancer distributing traffic
- Auto Scaling Group with Launch Templates
- CloudWatch alarms + SNS notifications
- Modular code structure (vpc, ec2, alb, asg, monitoring modules)
- Stress testing to validate auto-scaling behaviour
Demonstrates security-first infrastructure design with proper network segmentation, least-privilege IAM, and comprehensive monitoring.
More Projects Coming
Working on further infrastructure and security projects. Check back soon or follow my writing for updates.