The article discusses the potential risks of AI skills that operate with system access, highlighting how they can execute harmful commands before any review. It emphasizes the importance of treating these skills as executable code, especially in environments where trust relationships exist, making lateral movement and persistence possible. Non-technical users need to be cautious when granting permissions to ensure security.

This article outlines various security risks associated with AI agents and their infrastructure, including issues like chat history exfiltration and prompt injection. It emphasizes the need for a comprehensive security platform to monitor and govern AI operations effectively.

This article explores how new diagnostic codes and AI-driven solutions are reshaping healthcare operations, from billing to patient care. It also discusses the convergence of cyber and physical security in public and private sectors, emphasizing the need for unified systems to enhance safety and efficiency.

Microsoft announced new features at Ignite 2025, focusing on Azure Copilot, which automates cloud management tasks like migration and optimization. The updates also highlight advancements in Azure's AI infrastructure, enhancing performance and scalability across services.

The article discusses the security challenges of AI agents, likening them to early e-commerce risks. It outlines necessary layers of security—like supply chain integrity and prompt injection defense—to make AI interactions trustworthy and safe.

The article discusses Stakpak's efforts to simplify DevOps by addressing the challenges developers face with infrastructure management. CEO George Fahmy highlights the shortcomings of current AI tools in automating tasks that developers dislike and outlines Stakpak's solutions for security, tool fragmentation, and knowledge sharing.

Security researchers found serious vulnerabilities in Ollama and NVIDIA Triton Inference Server that could allow remote code execution. Although these flaws have been patched, they highlight growing security concerns around AI infrastructure and the shift in focus from model exploitation to infrastructure vulnerabilities.

Only 8% of enterprises possess a highly mature cloud strategy capable of addressing the security and infrastructure demands of the AI era. The article discusses the importance of assessing cloud maturity and provides insights on organizational practices that can enhance cloud agility and readiness for AI-focused products.