Evaluation guide
AI data loss prevention should control the submission, not just the tool
- 01
Identify sensitive values
- 02
Replace with stable tokens
- 03
Restore only inside your boundary
Direct answer
AI data loss prevention inspects information submitted to AI services and applies policy before the data leaves organizational control. It can allow an approved tool, redact PII from a prompt, block credentials or restricted documents, and record a safe policy outcome for review.
Tool access and data policy are different decisions
An organization may approve an AI service for general work while restricting customer records, credentials, source code, or regulated information. A simple allowlist answers which service can be used; DLP answers what data can be sent and under what conditions.
Policy may vary by user, department, account type, destination, data category, and purpose. The same prompt may be acceptable through an enterprise account with contractual controls and unacceptable through a personal account.
Redaction is useful when context can remain
When the AI task needs narrative context but not identity, redaction can remove names and identifiers while allowing the sanitized prompt. Credentials, restricted intellectual property, or highly sensitive records may require blocking instead.
Attachments and generated responses also matter. The evaluation should define whether the control covers files, images, copied tables, browser text, API calls, and data returned from the AI service.
- Identify user, account, and destination
- Inspect prompt and supported attachments
- Classify PII and other sensitive data
- Allow, redact, warn, block, or review
- Create safe policy evidence without retaining the original prompt
Verify the boundary during evaluation
Ask where inspection occurs, whether unredacted content leaves the device or controlled environment, how bypass paths are handled, and which browsers, applications, and APIs are covered. Test personal accounts, alternate domains, file uploads, and copied content explicitly.
MaskFlare is developing AI-workflow data protection as part of Vault and Shield. Exact coverage remains pilot-dependent.
Related PII guidance
Frequently asked questions
Is AI DLP the same as blocking AI websites?
No. Website blocking controls access to a destination. AI DLP evaluates the data being submitted and can apply different actions based on content, user, and destination.
Can AI DLP redact a prompt instead of blocking it?
Yes, when policy permits and the prompt remains useful after sensitive values are replaced. Other categories may still require blocking.
Does AI DLP cover API-based AI use?
It can, if the API path passes through an integration or enforcement point that inspects the request. Browser and API coverage should be evaluated separately.