An AI tool approval is effective only when the action executed matches the action the authorized person reviewed. An assessment checks the connection between the preview, approval record, tool arguments, and final business result.
This matters when an assistant can send messages, share files, change customer records, or initiate payments. A generic approval button does not explain which recipient, data, or operation the user has authorized.
What should an approval preview show?
Show the details that determine the consequence: action, target account, recipient, affected record, relevant content, and destination. OWASP’s AI agent guidance calls for explicit approval and previews for high-impact actions. The tests here examine whether that approval remains meaningful through execution.
Consider an illustrative assistant preparing to send a synthetic proposal to a designated test customer. The reviewer should see the actual recipient and attachment, not only a summary saying that the assistant will follow up with the customer.
What if the tool arguments change after approval?
Use a controlled mail sink or simulated tool that cannot contact real customers. Prepare the proposal, approve the displayed recipient and attachment, then change one of those details through an authorized test hook before execution.
The executor should reject the changed action or require renewed approval under the product’s policy. Capture the approved action representation and the actual arguments received by the tool. A log entry saying approved is insufficient if it does not identify what was approved.
Repeat the unchanged case to establish that normal work still completes. The test should distinguish a functioning approval boundary from a tool that simply never executes.
Can a queued action outlive the user’s permission?
Pause the synthetic proposal task after approval. Remove the reviewer’s access to the test customer or remove the assistant’s ability to use the tool, then resume the task.
Define beforehand whether the application must recheck current permission at execution. If the business intentionally honors a prior approval, document the allowed scope and lifetime explicitly. The assessment should establish the product’s actual behavior and whether it meets that requirement.
Also change the destination record while the task waits. If a customer entry now points to a different email address, decide whether the approval covers the old reviewed address or a dynamic lookup. The reviewer needs a clear contract for that choice.
How do retries avoid repeating an approved action?
In the simulated environment, let the tool complete once but withhold the normal completion response. Observe how the application recovers. It should resolve the previous outcome before creating another external effect.
Record the approval identifier, tool operation identifier, and resulting message count. A retry may be legitimate, but a single approval should not silently become permission to send unlimited copies or act on additional recipients.
Test expiry and cancellation too. A task canceled in the interface should have an observable effect on pending execution according to the stated policy, including work already handed to another service.
What should a business ask Ceron to verify?
Scope the approval interface, action storage, queue, authorization service, and tool executor. Use synthetic records and a test destination so the assessment can observe the complete result safely.
The deliverable should connect reviewed details to execution, show what happens after material changes, and document handling of revoked permission, cancellation, and uncertain retries. Include the legitimate successful path in the retest.
AI agent permission design covers the actions an agent may request. Validating AI output before business actions covers the transition from generated content to application input. The proposal workflow above is an illustrative acceptance test.
