22/04/2026
Your classic DLP is blind to the biggest data security threat in your office right now. It is not a file attachment or a USB drive; it is a simple copy-paste into an AI prompt.
Traditional Data Loss Prevention was built to stop files from leaving the building. But in the age of Generative AI, data exfiltration has become invisible. A single paragraph pasted into a chat can carry customer data, source code, or internal strategy, and it does not look like a document anymore.
Here is why classic models fail: they inspect content at rest or in transit, like emails and SharePoint files. AI prompts are short-lived text entered into a browser. To stay secure, we need a new intermediate control set that addresses how we actually work today.
First, start at the endpoint. If a user can copy sensitive data, they can paste it. Use endpoint controls to reduce risky copy-paste behavior and unsanctioned AI access, especially on unmanaged devices.
Second, label the data, not the app. Sensitivity labels make content self-describing. This allows security policies to travel with the information regardless of where it is being used or what window it is pasted into.
Third, add conditional access. Only allow AI usage from compliant devices, approved identities, and trusted locations. This ensures that the riskiest prompts never leave your controlled environment in the first place.
Finally, build prompt redaction patterns. You can detect and mask account numbers, project code names, and customer identifiers automatically before the prompt is ever sent to the model.
The ultimate goal is not to ban AI and stifle innovation. It is to make the safe path the easiest path for your team to follow by default.
I have a simple policy blueprint that helps implement these controls. Would you like me to share it with you? Let me know in the comments.
Watch the full video: https://lttr.ai/AqX15
How to Secure AI Prompts: A Modern DLP Guide
