Test DLP against AI websites: Separate uploads, pasted text, and screenshots

Quick answer

Test each AI transfer path and environment independently. Blocking an upload does not establish control over pasted text or images. Record expected results, actual outcomes and limitations.

A blocked upload does not demonstrate protection of all AI input methods. File transfer and pasted text follow different mechanisms. This is a defensive evaluation method using synthetic data, not guidance for circumventing policy.

Define paths and expected outcomes

List the service, browser, operating system, data category, and submission method. Specify whether the expected outcome is block, alert, or allow, with a business justification. Endpoint DLP Plus upload documentation describes file-content and destination controls; assess other paths separately.

Test legitimate work as well

Use a consistent synthetic dataset and ordinary documents that should remain transferable. Verify the agent and policy version each time. Record the user, device, timestamp, visible outcome, and console event. Use only approved external test accounts.

Describe gaps honestly

If a path is unsupported, label it accordingly and plan compensating controls, such as approved-tool restrictions or training. Do not describe complete AI data protection without evidence for each required path.

Implementation checklist

• Avoid real customer information in test fixtures.
• Separate upload, paste, image, and extension cases.
• Compare console evidence with user-visible behavior.
• Distinguish pass, fail, unsupported, and untested outcomes.

A useful proof of concept produces a coverage matrix with evidence, not a single impressive blocking screenshot. Share required websites and data paths with KTNBS to design a focused test.

A scenario to take into your evaluation

Send the same synthetic data by upload, paste and screenshot in the browsers your organization uses.

This is a proposed test, not a measured result or customer endorsement. Record the actual platform and edition, owner, expected result and observed outcome before expanding scope.