Agentic AI Module Added To NHI Training Course

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Why do AI agents turn NHI governance into an urgent issue?


(@entro)
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TL;DR: OWASP’s Agentic Top 10 for 2026 maps the main failure modes in AI agents to identity, tool, memory, and supply-chain risk, showing that most incidents start with overprivileged or exposed non-human identities, not with the model alone, according to OWASP. The governance problem is now operational, because agent security collapses when secret sprawl and implicit trust outpace least-privilege control.

NHIMG editorial — based on research published by Entro Security.

By the numbers:

Questions worth separating out

Q: How should security teams govern AI agents without creating excessive friction?

A: Start by treating each agent as a non-human identity with a defined owner, purpose, and access boundary.

Q: Why do AI agents increase NHI governance risk compared with traditional automation?

A: AI agents can interpret context, choose tools, and chain actions dynamically, which means their behaviour is less predictable than scripted automation.

Q: What is the difference between agent security and NHI security?

A: Agent security focuses on what the AI system says or does at runtime, while NHI security governs the identities, secrets, and permissions that let it act in the first place.

Practitioner guidance

Teams need a control plane that combines identity inventory, privilege review, and behaviour monitoring before usage scales further?

👉 Read OWASP’s full analysis of the 2026 Agentic Applications Top 10 →

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