All news with #model context protocol tag

Securing and Governing Autonomous AI Agents in Business

🔐 Microsoft outlines practical guidance for securing and governing the emerging class of autonomous agents. Igor Sakhnov explains how agents—now moving from experimentation into deployment—introduce risks such as task drift, Cross Prompt Injection Attacks (XPIA), hallucinations, and data exfiltration. Microsoft recommends starting with a unified agent inventory and layered controls across identity, access, data, posture, threat, network, and compliance. It introduces Entra Agent ID and an agent registry concept to enable auditable, just-in-time identities and improved observability.

SASE Best Practices for Securing Generative AI Deployments

🔒 Cloudflare outlines practical steps to secure generative AI adoption using its SASE platform, combining SWG, CASB, Access, DLP, MCP controls and AI infrastructure. The post introduces new AI Security Posture Management (AI‑SPM) features — shadow AI reporting, provider confidence scoring, prompt protection, and API CASB integrations — to improve visibility, risk management, and data protection without blocking innovation. These controls are integrated into a single dashboard to simplify enforcement and protect internal and third‑party LLMs.

Agent Factory: Build Your First AI Agent with Tools

🔧 This Microsoft Azure blog post, the second entry in the six-part Agent Factory series, explains how tool ecosystems are defining the next wave of agentic AI. It argues the industry is moving from single-model prompts to extensible platforms that let agents discover and invoke a broad set of capabilities at runtime. The piece highlights the Model Context Protocol (MCP) and Azure AI Foundry for secure, enterprise-grade tool integration, and summarizes five best practices for governance, identity, and observability to achieve scalable, production-ready agents.