Category: Red Hat Security

Context-aware advisor recommendations in Red Hat Lightspeed

In distributed system management, defining the “ideal state” of a server is rarely black and white. Different operational goals often create tension between performance tuning and security hardening, where optimizing for one can inadvertently break the other. To resolve this…

MCP security: Containerization and Red Hat OpenShift integration

In our previous 3 articles, we laid the groundwork for a protected Model Context Protocol (MCP) ecosystem by analyzing the current threat landscape, implementing robust authentication and authorization, and exploring critical logging and runtime security measures. These focused on who…

MCP security: Logging and runtime security measures

Model Context Protocol (MCP) servers often execute code or commands as instructed by an AI agent, exposing them to various risks. To help mitigate these risks, you should implement strict runtime security measures to contain what the server can do…

4 use cases for AI in cyber security

In product security, AI represents a new and critical frontier. As artificial intelligence becomes mainstream in both defense tools and exploitation methods, security professionals must master these technologies to more effectively protect and enhance their systems.What is AI in cyber…

AI security: Identity and access control

In our first 3 articles, we framed AI security as protecting the system, not just the model, across confidentiality, integrity, and availability, and we showed why the traditional secure development lifecycle (SDLC) discipline still applies to modern AI deployments. We…