Prevent AI data leakage
AI data leakage often happens through normal work rather than an attack: copy-paste, uploads, summaries, file analysis and tests of new tools. DLPShield adds guardrails before those transfers.
- Prompt check text before sending
- Upload control files before transfer
- Shadow AI audit before blind spots
Answer first: how do you prevent AI data leakage?
Prevent AI data leakage with approved tools, clear data classes, training, audit and technical controls directly in the browser. The key is checking prompts and uploads before they are sent.
Common causes
- Customer tickets copied into AI tools for faster replies.
- Confidential PDFs uploaded for summaries or analysis.
- Employees testing new AI tools without approval.
- Source code, API keys, tokens or credentials pasted into web interfaces.
Control model
| Mode | When useful | Example |
|---|---|---|
| Audit | When usage needs to become visible first. | Which AI domains are used and which data classes appear? |
| Warn | When employees should make a conscious decision. | Warning on customer data in ChatGPT or Claude. |
| Mask | When work may continue but data must be reduced. | Remove IBAN, email or customer ID before sending. |
| Block | When data must not be transferred. | Patient data, client data, secrets or unreleased source code. |
Why local-first matters
If the goal is protecting sensitive data, inspection should not create unnecessary new data flows. DLPShield is positioned local-first: detection in the browser before raw content leaves.
How do you prevent data leakage in AI tools?
Combine approved tools, data classification, employee training and browser controls that check prompts and uploads before sending.
What is a ChatGPT data leak?
A ChatGPT data leak happens when confidential, personal or regulated data is entered into or uploaded to an AI service without proper approval, contract, legal basis and safeguards.