Official repo of "EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)"

Kuzushi — Agentic SAST scanner with AI triage

Analytical portfolio demonstrating transaction monitoring, judgment-based alert review, and Excel-driven risk analysis across fraud, AML, and KYC workflows, with a focus on regulator-safe decisioning and operational consistency.

GUARDIUM is an intelligent Wazuh rule optimization framework designed to reduce false positives, improve alert accuracy, and assist SOC teams in maintaining high-quality SIEM detections. GUARDIUM combines rule analysis, threat context, and Large Language Models (LLMs) to automatically evaluate, explain, and optimize Wazuh rules.

Python security gate with intelligent ML scoring that reduces false positives by 95%. Orchestrates Bandit, pip-audit, and Semgrep into a unified CI/CD pipeline. Includes baseline management, policy enforcement, and explainable predictions. Production-ready with comprehensive tests.

🚀 SmartAlert AI - Production-ready adaptive ML system for intelligent incident prediction. Achieves 44% F1-Score on challenging datasets with 75% false alarm reduction. Features 118 sophisticated features and real-time adaptive learning.

Lightweight network based host & service watchdog - very smart check definitions to cut down on false positives. Eight different nest-able, AND/OR-able health check types. Email, Signal and Webhook alerts. SOC/NOC wallboard, SLA tracking and more.

🔍 Analyze transaction data to identify fraud risks, streamline alert reviews, and ensure compliance in AML and KYC contexts using Excel-driven techniques.