# How to wear Model Armor 3: How you protect sensitive data from LLM. Do you need to?

> Source: <https://leoy.blog/posts/how-to-wear-model-armor-3/>
> Published: 2026-08-26 22:03:09+00:00

When building Generative AI applications for the enterprise, you are likely hyper-aware of the risks surrounding sensitive data. The knee-jerk reaction for many engineering teams is to aggressively block all sensitive data ‒ ranging from PII to financial records and internal credentials ‒ from absolutely everywhere in the stack.

But a blind, one-size-fits-all approach introduces its own massive headaches. It compromises internal reasoning, ruins user experiences and breaks downstream autonomous systems. As I promised in the first “[How to wear Model Armor](https://leoy.blog/posts/how-to-wear-model-armor-1/)” post, we are going to dive into exactly when to keep sensitive data out of your language models, the reasons you must often avoid de-identifying an agent’s output, and how to orchestrate this balance using Google Cloud’s Sensitive Data Protection (SDP) and Model Armor.