The Tool Desk
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Start by mapping the workflow, not choosing a token
An agent’s request to call a tool is a proposed action, not proof that the action is authorized. Before selecting a grant, map the route from user request to API call: an agent may combine a model with tools, data, memory, and planning. Australian government cyber guidance describes that composition as a security concern because authority and sensitive information can pass through multiple parts of the system.
For each task, record the following:
- Resource and owner: Which API, dataset, mailbox, workspace, or tenant is involved, and who is responsible for it?
- Operation: Does the agent need to read, create, update, delete, export, or administer?
- Authority: Should the decision follow a particular user’s permissions, or permissions assigned to the agent itself?
- Execution context: Is a user present to authenticate or approve the work, or will it run unattended?
- Impact: What could happen if the agent targets the wrong resource or makes an incorrect call?
Use those answers to define the intended boundary before granting access. A workflow that reads a named knowledge collection has a different boundary from one that exports customer records or changes permissions, even if both use the same API.
Give the agent its own accountable identity
Create a stable principal for each agent or distinct workload, with a named human or team owner and a documented purpose. Keep that principal separate from the identity of the user who may have initiated a task. This makes it possible to distinguish what the agent was configured to do from whose request or authority was involved.
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Do not give an agent a person’s password or an unrestricted human session. For delegated work, preserve user context through the identity platform’s supported mechanism. Log the agent identity and, where applicable, the initiating or delegated user so an action can be attributed to both. AWS guidance recommends distinct service identities and signed user-context claims through the call chain; Microsoft documents agent identities and token acquisition for downstream APIs.
That separation is central to answering a practical security question raised by the AWS Well-Architected Agentic AI Lens: how to manage agent identities and permissions while preventing privilege escalation. An identity identifies the caller; it does not, by itself, authorize every action the agent might propose.
Choose an authorization pattern for each resource and workflow
Decide whose permissions should govern access by considering who owns the data, whether a user is present, when the task runs, and which identity the target service must evaluate. AWS documents three common patterns. They can coexist in one application; choose per workflow rather than forcing one pattern across the entire agent.
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| Pattern | Good fit | Authority to preserve | Design check |
|---|---|---|---|
| OAuth 2.0 authorization code with user delegation | Interactive tasks that access a particular user’s data or act for that user | The user’s consent and delegated scopes | Request only the scopes needed for the task; handle user and administrator consent intentionally. |
| OAuth 2.0 client credentials | Background automation or access to organization-owned resources when a user is not present | The agent’s own preconfigured permissions | Keep the agent’s permissions narrow because no user approves each run. |
| On-behalf-of token exchange | A signed-in user invokes an agent that must call downstream services enforcing per-user policy | The authenticated user and the agent or workload identity | Obtain a token for the downstream audience and have the target service apply its policy. |
For example, one customer-service agent could use delegated access for a user’s records, client credentials for a shared knowledge base, and token exchange for a downstream service that applies per-user access rules. The pattern changes with the resource and its policy, not merely with the fact that an AI model is involved.
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Turn the task into narrow, enforceable grants
Define permissions around a discrete task and resource, such as “read this knowledge collection” or “create a draft ticket.” Avoid broad roles chosen for convenience. Where practical, separate read access from write access, and distinguish routine work from operations with higher impact, such as deletion, export, administration, or permission changes.
- Limit the operation: Grant only the actions the workflow needs; do not infer write or administrative authority from a read requirement.
- Limit the resource: Bind access to the intended dataset, tenant, workspace, or other supported boundary.
- Account for sensitivity: Treat access to sensitive data or consequential actions more restrictively than low-impact reads.
- Constrain elevation: For higher privilege, use a stronger approval control or time-bounded elevation where the platform supports it.
Microsoft’s least-privilege guidance for AI agents treats identity, scope, tool access, and auditability as design requirements. AWS recommends controls such as permission boundaries, IAM conditions, short-lived credentials, and just-in-time elevation for higher privilege. These are platform-specific mechanisms; apply the equivalent controls offered by the identity and API platforms in use.
A scope is not the whole authorization policy. A target API should validate the caller and evaluate the identity, delegation context, requested action, and resource. Recheck access at each downstream service. If a call is denied, investigate whether the requested operation belongs in the approved task before changing a grant; denial alone is not a reason to broaden access.
Make consent and provisioning part of the workflow
Consent, provisioning, and token acquisition are related but distinct steps. Use the identity platform’s supported process, verify the requested permissions and token audience, and account for whether a user or administrator must approve access.
For Microsoft 365 delegated access, Microsoft documents OAuth flows in which users or administrators consent to API permissions. Requested delegated scopes—such as User.Read or Mail.Read—are recorded for the agent client, and approved scopes can appear in the token’s scp claim. Some permissions require administrator consent. These details describe Microsoft’s platform, not a universal OAuth rule.
Microsoft also documents application permissions and access packages that can standardize agent access and support expiration or revocation. In its interactive agent flow, the consent request records permission but does not itself return a token; token acquisition is a separate step. Do not treat a successful consent screen as proof that a later API call has the right token, audience, or resource-level authority.
Constrain callable tools and protect credentials
Expose only the approved operations the agent needs. A tool allowlist can reduce the actions available to the model, but it does not replace authorization at the API. Validate sensitive parameters—especially the target resource, operation, and destination—before executing a call.
- Keep secrets out of prompts, model context, and logs the agent can access.
- Use the platform’s credential handling and short-lived credentials where supported instead of embedding reusable secrets in agent code.
- Authenticate and authorize every hop between agents, tools, gateways, and services; chained or multi-agent workflows do not inherit trust automatically.
- Do not assume a curated tool list or a gateway makes a downstream service’s authorization check unnecessary.
AWS warns that poor credential management can expose user credentials or let agents act beyond intended authorization. Its guidance also calls for authentication and authorization at each step in multi-agent architectures.
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Log, review, expire, and revoke access
Keep enough provenance to explain what happened and investigate why. For each consequential call, record the agent, initiating or delegated user when relevant, tool and API, target resource, authorization decision, and outcome. Preserve appropriate information about the data and inputs that informed an action, subject to the organization’s data-handling requirements.
Assign owners who can review grants and provide a practical route for administrators to revoke access. Compare granted permissions with observed use to identify drift or unused access, and revisit the review process when tools, prompts, or orchestration change. Review frequency should reflect how quickly the deployment changes and the impact of its actions; a review only after an incident may miss important changes in a fast-moving system.
Use credential expiration, short-lived tokens, and time-bounded elevation where supported. NIST NCCoE’s February 2026 concept paper identifies delegation, logging and transparency, and data-flow provenance as relevant capabilities; it is a concept paper, not a finalized standard. AWS guidance likewise emphasizes continuous validation and review.
Quick Recap
Common design failures and their fixes
- Shared human credentials: Actions become difficult to attribute, and the agent may inherit access far beyond its task. Give the workload its own identity and carry delegated user context where required.
- One broad service account: An autonomous workflow may chain tools or reach resources outside its purpose. Split grants by task and resource boundary.
- Consent treated as blanket, permanent approval: Consent does not eliminate the need for scoped ownership, review, and platform-supported expiration or revocation.
- Authorization only at the orchestrator: The downstream API still needs to validate the caller and enforce its own policy using relevant identity and user context.
- Permission creep after a denial: Check whether the denied access is genuinely part of the approved task before changing permissions.
- Unrestricted tools or unchecked agent chains: Curate actions and authenticate and authorize every service or agent hop.
- Weak lifecycle oversight: Set up grant review and revocation that keep pace with changes to tools and orchestration, rather than relying only on an annual or post-incident review.
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