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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11To prove an agent’s permissions, define the access its task needs, test its workflows using a non-owner identity, and inspect the credentials and resources available to its runtime. A permissions screen, visible tool list, or single successful test cannot establish that every user, connection, and execution path is appropriately limited.
Start with the task and the identity behind each action
Write down what the agent must do, then specify the minimum access required for each step. OpenAI’s platform permissions documentation advises: “Use the principle of least privilege. Start with the minimum permissions required for a task, then add permissions only as needed.” Treat that as a baseline to verify, not a guarantee that a configured role is the only access the agent can exercise.
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Record the principal—the identity whose authority is being used—for every tool or connection. It may be the end user, a service account, the agent builder’s connected account, or another credential holder. The same action can have different consequences depending on which identity performs it and what that identity can access.
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An agent’s effective access can depend on several controls. Keep them distinct in your inventory, because changing one does not necessarily change the others.
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- Platform roles: Which users can configure, administer, or use the agent and its platform features?
- Agent audience and enabled actions: Who can run a published agent, and which tools and actions can it invoke?
- App-level controls: What does the platform allow the app or tool to do within its own interface?
- Provider authorization and source-system access: What does the connected service authorize, and what can the underlying account access there?
- Tool and API credentials: Which credentials are available to the code or application that performs a function?
- Runtime resources: Which files, credentials, and network destinations can the execution environment reach?
OpenAI’s ChatGPT app-permissions guidance distinguishes app permissions from provider authorization: app controls govern how an app is used after access exists; they do not grant provider permissions or change access in the source system. Check the provider and source-system account separately rather than assuming a platform setting narrows them.
Assess each tool by its impact
For every tool, document what it reads or changes, the account permissions it needs, and whether its actions can be undone. OpenAI’s practical agent-building guide identifies read versus write access, action reversibility, and required account permissions as useful factors for comparing tool configurations.
| Check | What to record | Why it matters |
|---|---|---|
| Read or write | Whether the tool only retrieves data or can create, update, send, or delete it. | Write access can change systems or disclose information, so it calls for closer scrutiny than read-only access. |
| Reversibility | Whether an action can be reliably undone, and by whom. | Irreversible or difficult-to-reverse actions have a higher impact if invoked incorrectly. |
| Required account permissions | The permissions the tool’s identity must hold at the provider or source system. | Excessive account authority can make a narrowly described tool more powerful than intended. |
| Principal and connection owner | Whose identity or credential is used for the action. | A builder-owned connection may expose the builder’s access to people who can run the agent. |
| Runtime reach | Files, credentials, and network destinations accessible to execution. | Tool configuration alone does not show everything code in the environment might reach. |
Test effective access with a non-owner identity
Configuration is a statement of intent; an identity-based test checks what the system actually permits. OpenAI’s RBAC guidance recommends validating expected access with a non-owner account before broad rollout.
- Choose a test identity that does not own or administer the agent, its connection, or the relevant source-system account.
- Run representative workflows that exercise each enabled tool, including the read and write paths that matter to the task.
- Check both expected successes and expected denials. A test that only confirms permitted actions does not show that out-of-scope access is blocked.
- Compare observed access with the minimum-access baseline you documented. Investigate any unexpected data, action, or account authority.
- Record the identity, workflow, tool, expected result, observed result, and configuration tested. Re-run the checks after changes to roles, connections, tools, or runtime settings.
A non-owner test is evidence about the tested identity and workflows, not proof that all users or paths behave the same way. Test other materially different roles or connection arrangements when they change the authority available to the agent.
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Make workflow tests repeatable—and know what they prove
The OpenAI Agents SDK testing documentation describes deterministic utilities for testing agent workflows, including workflows involving tools. Use repeatable tests to check that a workflow invokes the right tools and handles expected outcomes consistently.
Do not treat a deterministic workflow test as an authorization audit unless it actually checks authorization. A test may confirm that a tool call occurs without verifying which principal authorized it or whether a different identity would be denied. Keep workflow behavior and effective-access checks as explicit, related but distinct test objectives.
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Review published agents and connection ownership
For published workspace agents, inspect the audience, enabled tools and actions, and the account that owns each connection. OpenAI’s workspace-agent guidance warns that publishing an agent with personal connections may expose the builder’s app access to users of that agent.
- Limit the audience to people who need to run the agent.
- Review whether each connection uses a personal account or an appropriately scoped identity.
- Enable only the tools and actions the task needs, with particular care around sensitive or high-impact connectors.
- Revisit the configuration regularly and after changes to the audience, connections, or available actions.
Inspect the runtime boundary, not just the tool list
An agent can be constrained at the tool layer yet still run in an environment with broad access. OpenAI’s sandbox security documentation explains that agent-generated code can access files, credentials, and network resources available to its environment. Review what the runtime can actually reach, including credentials and network pathways, and narrow that boundary to what the task needs.
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The OpenAI Agents SDK security policy states: “Model output, model tool calls, remote content, and serialized state do not by themselves authorize access to host resources or credentials.” In other words, content produced by a model or returned by a tool is not itself permission to access host resources. The runtime and the application that handles a function tool still need to enforce the appropriate authorization boundary. OpenAI’s sandbox guidance advises keeping credentials in the application that handles a function tool where applicable.
Keep the proof current
Permissions can change when a user’s role changes, a connection is replaced, an agent gains a tool, or the runtime environment is reconfigured. Keep a compact record of the intended access, principals and connection owners, tool risk characteristics, runtime resources, and test results. Recheck the affected paths whenever one of those inputs changes, rather than relying on an old successful run or a configuration screenshot.
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