RAG/LLM Security Scanner identifies critical vulnerabilities in AI-powered applications, including chatbots, virtual assistants, and knowledge retrieval systems.

Local RAG system with a built-in governance agent that filters sensitive or restricted information with separated agent logging systems to keep privacy and security

Complete roadmap to become an AI Security Engineer from zero to advanced — covering Python, ML, Deep Learning, LLM Engineering, RAG Security, Intrusion Detection, Anomaly Detection, and a full Master Project (AI-Powered Security Analyst).

AI Operations Security Maturity Model and toolkit to secure AI/ML systems across 11 domains and 5 levels—aligned to NIST AI RMF, SAIF, OWASP LLM Top 10, MITRE ATLAS. Practical AI security maturity model with assessment questions, CI/CD policy gates, LLM/RAG controls, infra/accelerator hardening, monitoring, IR, and red teaming.