Topic starter
15/08/2026 6:06 pm
TL;DR: AI agents now operate with delegated credentials across SaaS and cloud systems, and Obsidian Security argues that prompt injection, token theft, and privilege sprawl make identity-first controls essential. Traditional perimeter security cannot govern autonomous systems that create new execution paths, so runtime monitoring and dynamic authorization become the real control plane.
Editorial analysis by NHI Mgmt Group, based on content published by Obsidian Security: “Security for AI Agents: Protecting Intelligent Systems in 2025”.
Key questions
Q: What breaks when AI agents are given broad standing access?
A: Broad standing access breaks governance because the agent can move from one task to another without a fresh authorization check.
Q: Why do AI agents create more risk when access is scoped once but not rechecked during execution?
A: AI agents can move through many steps in a single task, including prompts, retrieval, tool use, and output.
Q: How can organisations tell whether an AI agent is acting outside its intended scope?
A: Organisations should look for behaviour that crosses expected tool boundaries, generates unusual credentials, or chains actions across systems that are not part of the original task.
Practitioner guidance
- Inventory every AI agent and its effective authority Build a live register of agents, linked credentials, data sources and downstream applications so you can see what each agent can actually reach during runtime.
- Replace static roles with context-aware policy decisions Use attribute-based or policy-based access decisions for agents whose permissions change by task, resource sensitivity and recent behaviour.
- Shorten token lifetime and enforce automated rotation Limit agent tokens to task-scoped lifetimes, store keys outside code and revoke credentials automatically when task context or ownership changes.
Bottom line: AI agents expand the identity problem because delegated credentials can be reused across tools, data sources and workflows without a fresh human control point.
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15/08/2026 6:15 pm
Runtime trust, not static provisioning, is now the governing problem for AI agents. The article shows that agent security cannot be reduced to a one-time access grant because agents continue acting after the initial decision. Once they can create new execution paths across SaaS and cloud systems, the meaningful question becomes what they can reach right now. For identity teams, that means the control plane has shifted from issuance to continuous authority validation.
A few things that frame the scale:
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What should organisations do when AI agent behaviour becomes suspicious?
A: Organisations should isolate the agent, review the full action sequence, and verify whether the behaviour shows a change in destination, volume, or task scope. If the agent is moving beyond its normal pattern, treat it as a live identity risk and contain it before the session completes or data leaves the environment.
👉 Read our full editorial: AI agent identity security in 2025 needs runtime trust controls