Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Kubernetes security refers to practices, tools, and configurations that protect Kubernetes clusters and workloads from unauthorized access, vulnerabilities, and runtime threats. It involves securing all components of the Kubernetes environment—including the control plane, worker nodes, pods, container images, networking, and storage.

Recently, the EU officially launched its vulnerability catalog: the European Vulnerability Database (EUVD). This move has sparked a discussion about the future of global vulnerability tracking. Are we headed toward fragmentation, or is this a healthy step toward decentralization?

MCP adoption is surging across industries, fundamentally reshaping how systems connect to AI models. By establishing a universal protocol for data exchange, MCP simplifies integration complexity, empowering developers to build sophisticated AI capabilities in a fraction of the traditional development time. However, this streamlined connectivity to AI tools introduces significant security risks.

AI red teaming is the process of simulating adversarial behavior to test the safety, security, and robustness of artificial intelligence systems. It draws inspiration from traditional cybersecurity red teaming (where ethical hackers emulate real attackers to expose flaws) but applies that mindset to machine learning models, data pipelines, and the broader AI stack.

Linux distributions, such as Red Hat Enterprise Linux (RHEL), dominate the enterprise and cloud computing sectors. One of the many reasons for the success and popularity of Linux is its support of convenient and straightforward remote access protocols, such as Secure Shell (SSH). In the right hands, SSH’s ability to securely access remote servers enables access to any Linux server, regardless of the environment. The problem is that, in the wrong hands, SSH can be a security nightmare.