Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Most healthcare AI systems rely on Retrieval-Augmented Generation (RAG) and vector databases to search millions of insurance claims, physician notes, lab reports, billing documents, and customer records. But what happens before those documents become searchable? In this Short, we explain how embedding models convert raw healthcare documents into vectors—and why patient names, medical record numbers (MRNs), diagnoses, and Social Security numbers can end up stored inside your vector database if data isn't protected before ingestion.

One platform to discover, monitor, and remediate data and identity risks across your environment. More visibility. More control. Fast setup.

AI Led Pentesting is redefining how organizations approach application security. As software development accelerates with AI-assisted coding, cloud-native applications, and rapidly evolving attack surfaces, traditional penetration testing is struggling to keep pace. In this detailed video, we explore why the future of security testing needs to be continuous, intelligent, and autonomous led by AI.

CVE of the day - CVE-2026-69198.

A criminal talked commercial AI models past their guardrails. Then stood up a "company" of AI agents that engineered, tested and refined malware. It began when Sophos analysts found a folder named "test" on an endpoint nobody recognised. Inside was the front end of a machine: Cobalt Strike profiles, a Telegram command channel, a hidden Sliver server behind Cloudflare and scripts written with the help of AI.