ML-Based Registration Abuse Detection
ML-based scoring engine identifying bot/fraud-driven account registrations via structural pattern analysis.
Engineering solutions for operational security problems
ML-based scoring engine identifying bot/fraud-driven account registrations via structural pattern analysis.
Extended an open MCP server to analyze internal SIEM detections alongside public rule sets, enabling automated MITRE ATT&CK coverage tracking and gap analysis.
Falco-based runtime detection stack converting syscall alerts into enriched, investigation-ready insights through AI-assisted analysis.
Built a fully automated CI/CD pipeline for SIEM applications delivery. Eliminated manual packaging and testing , reduced deployment time from hours to minutes.