Zero Trust

Zero trust is a security framework that assumes no user, device, or system should be automatically trusted, regardless of their location or network position. In AI governance, zero trust principles are critical for protecting sensitive training data, model weights, and inference outputs from unauthorized access or manipulation. Organizations implementing zero trust for AI systems must continuously verify identities, encrypt data in transit and at rest, and monitor all access to AI infrastructure to prevent data breaches and ensure model integrity.

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StandardsGlobal2026-08-18

CSA Zero-Trust Guidance Puts NHI Governance on the Enterprise Control Agenda

The Cloud Security Alliance published guidance on July 8, 2026, requiring agentic systems to apply zero-trust principles to every tool, API, and infrastructure interaction made by non-human identities. The guidance recommends a dedicated mediation layer between agents and external tools, along with pre-validated MCP servers and dependency vetting. Compliance teams deploying agentic AI must now treat agent credentials and tool connections as governed identity assets, not implementation details.

Cloud Security Alliance non-human identity zero trust MCP agentic AI agent credentials tool mediation NHI