> For the complete documentation index, see [llms.txt](https://gl-docs.gitbook.io/zkpass/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gl-docs.gitbook.io/zkpass/core-components/trust-models/data-privacy-trust-model.md). # Data Privacy Trust Model Imagine your personal data is like a precious gemstone, and you want to keep it safe while also showing it off under certain conditions. Welcome to the world of zkPass, a service designed to protect your "gemstone" like a high-security vault while still letting you make use of it. At the heart of zkPass is something called a Trusted Execution Environment, or TEE for short. Think of TEE as an ultra-secure vault room where special processes can take place without anyone else peeking in. It's like a VIP lounge for data, where only the most trusted operations are allowed to enter. In this VIP lounge, zkPass performs two main tasks on your data. First, it verifies that the data is genuinely yours, kind of like a bouncer checking your ID at the door. This is done through digital signature verification. Second, it performs some fancy math—called Zero-Knowledge Proof calculations—to make sure that your data can be used without revealing any sensitive information. You might wonder, "Why not just keep the data encrypted all the time?" Well, some operations need to look at the data in its raw form, just like a jeweler needs to take the gemstone out of the safe to inspect it or reshape it. Also, techniques like Homomorphic Encryption, which can do some calculations on encrypted data, just aren't powerful enough for what zkPass needs to do. So, what it comes down to is trust. You have to trust that zkPass's VIP lounge is as secure as it claims to be, and that it's been set up correctly to protect your precious gemstone—your data. In other words, the zkPass service is built on a Trusted Model. You're trusting that everything behind the scenes is working to keep your data both useful and secure. And there you have it! That's how zkPass works to keep your data safe yet functional, all wrapped up in a layer of trust. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://gl-docs.gitbook.io/zkpass/core-components/trust-models/data-privacy-trust-model.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.