An AI agent’s initial authorization does not automatically cover every later action. Before it uses a new tool, reaches a different resource, or takes a consequential step, the system should check who the agent is acting for, whether the action fits the granted scope, and whether current policy allows it. A person might authorize an agent to read project files, for example, without authorizing it to send a message about them.
What does it mean for an AI agent to be authorized?
An AI agent is software that can use tools and connected systems to gather information and take actions. Its authority has two essential parts: the identity or organization on whose behalf it acts, and the scope of operations and resources it may access.
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Those parts should not be collapsed into a general instruction such as “help this user.” The system needs to distinguish the agent as a software actor while retaining a traceable link to the person or organization whose authority it is using. NIST’s National Cybersecurity Center of Excellence (NCCoE), in its February 2026 concept paper, identifies agent identity, authentication, authorization, delegation, and accountability as design concerns. It discusses mechanisms such as OAuth 2.0 and policy-based access control as areas to explore, not as a finalized required architecture.
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Why can an initial grant stop being enough?
The requested action and its context can change after permission is granted. An agent that starts with read access might later be asked to send a message, modify a record, or use a newly connected tool. Combining data from multiple sources can also change how sensitive that information is. A grant that made sense for the original task may not cover the new operation or context.
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NIST’s concept paper raises these as open design questions: how authorization should respond when agents gain tools or resources, when data aggregation changes sensitivity, and when actions are difficult to predict in advance. It does not establish a universal rule that every agent must use one specific runtime authorization design.
How should authorization work throughout an agent’s task?
A practical control sequence is to establish the agent’s identity and scope, then check authorization at the point of action rather than relying only on the permission granted at the start. This approach combines NIST’s design questions with OWASP’s recommendation for complete mediation of requests.
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Identify the principal and the agent
Record the agent as a distinct software actor and maintain its link to the person or organization it represents. NIST identifies that human-agent relationship as important for delegation and accountability.
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Grant only the scope the task needs
Limit both the tools exposed to the agent and the permissions those tools carry in downstream systems. OWASP’s LLM06:2025 guidance gives concrete examples: a task that only needs database reads should not also receive insert, update, and delete permissions; an agent summarizing a mailbox does not necessarily need the power to send or delete messages.
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Re-check each material action
Before an operation, evaluate the current identity, requested action, target resource, applicable policy, and any relevant delegation or changed context. A prompt telling the model what it may do is not a substitute for this check: OWASP recommends that downstream systems enforce authorization for each request.
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Require approval for consequential steps
For high-impact actions—such as deleting data, sending messages, or changing settings—OWASP recommends user approval. Approval should apply to the action that is actually about to happen, rather than functioning as indefinite permission for unrelated later actions.
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Record the decision and outcome
Keep enough information to reconstruct which identity acted, what resource and operation were involved, which policy applied, whether approval was required and obtained, and what executed. NIST’s concept paper asks how action and intent might be logged in a tamper-proof, verifiable way and tied back to human authorization.
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What should happen when authority is delegated?
If an agent hands work to another agent or service, the receiving system should be able to determine whose authority is being used and what scope travels with it. Otherwise, a downstream service may see only a generic service identity and lose the user-specific limits attached to the original request.
NIST identifies binding human and agent identities, delegated authority, and accountability as issues for the proposed project. Its summary of public comments reports that commenters called for authorization context to persist across service boundaries and delegation chains. Those comments are stakeholder input, not an adopted NIST requirement.
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Why are prompt injection and repeated testing relevant?
Agents may read emails, files, or web pages that contain malicious instructions disguised as ordinary content. If an agent follows those instructions and can act through connected tools, a hostile input can become an authorization problem as well as a model-behavior problem. The safety boundary must therefore be enforced by the systems receiving actions, not by trusting the agent to recognize every forbidden request.
NIST’s Center for AI Standards and Innovation (CAISI) reported results from simulated AgentDojo Workspace tasks against the upgraded Claude 3.5 Sonnet configuration described in its January 2025 technical blog. The strongest baseline attack succeeded in 11% of tasks; the strongest new attack developed through red teaming succeeded in 81% on a held-out set of user tasks. In five selected injection tasks, average measured attack success rose from 57% after one attempt to 80% after 25 attempts. These are results from that test setup, not observed rates for deployed agents generally.
The CAISI team also added scenarios involving remote code execution, database exfiltration, and automated phishing, and said it was frequently able to induce the agent to follow malicious instructions in those areas. The findings make task-specific and repeated-attempt evaluation relevant; a single score should not be treated as a universal estimate of real-world risk.
Which authorization design choices matter most?
| Choice | Weaker control | Stronger control |
|---|---|---|
| Scope | Agent-wide standing access to tools and resources | Task-scoped access limited to needed operations and data |
| User context | Generic service identity without the user’s authorization context | Downstream checks that preserve the relevant user identity and scope |
| Enforcement | Permission described only in model instructions | Policy checked and enforced by the system receiving each action |
| High-impact actions | Autonomous execution without action-specific approval | Human approval before consequential operations |
| Evaluation | Single-shot testing alone | Repeated, task-specific testing that distinguishes impact levels |
These are practical decision axes, not a claim that one configuration fits every deployment. OWASP’s LLM06:2025 guidance supports least privilege, user-context execution, downstream authorization checks, human approval for high-impact actions, and logging and monitoring. NIST’s concept paper frames identity and authorization architecture as work under consideration.
What do the NIST and OWASP documents establish?
NIST NCCoE’s February 2026 concept paper proposed a project to apply identity standards and best practices to software and AI agents; its comment period closed April 2, 2026. The concept paper is not a final standard or binding rule. OWASP LLM06:2025 is guidance for reducing excessive agency, not a complete identity architecture. Together, they support treating authorization as a continuing control problem while leaving implementation choices dependent on the system and its risks.
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