> For the complete documentation index, see [llms.txt](https://help.protecto.ai/getting-started/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.protecto.ai/getting-started/protecto-overview/introduction/protecto-vault/tokenization-apis/masking/identify-and-mask-auto-detect.md).

# Identify and mask (Auto-detect)

This method automatically identifies and masks personal/sensitive data within specific sentences.

***Note:*** To send a request with the authentication token, include the following in headers: 

Headers: {"Authorization": "Bearer \<AUTH\_TOKEN>"}

<figure><img src="/files/aR8sclYTnjgRkOYvuGOD" alt=""><figcaption></figcaption></figure>

**`Endpoint:`**

```
https://protecto.ai/api/vault/mask
```

**`Request Method: PUT`**

**`Request Payload: eg :`**&#x20;

```
{"mask": [{ "value": “George Williams lives in Washington”}]}
```

**`Parameters:`**

·       value (string): Sensitive data value that needs to be masked.

**`Response:`**

```
{"data": [{"value": " George Williams lives in Washington“, "token_value”: “243 3466 lives in eweww”}]}

```

**`Response Parameters:`**

·       token\_value (string): Generated token replacing the sensitive data.

**`Advantage:`**

This approach is particularly useful when users may not be aware of all the sensitive data present in a given text or when dealing with large volumes of data where manual identification is impractical. Auto-detect masking offers the following advantages:

1. **`Effortless Sensitive Data Identification:`** Users do not need to manually identify and specify sensitive data elements within the text. The system automatically detects patterns and formats indicative of sensitive information, such as names, phone numbers, credit card numbers, and more.
2. **`Comprehensive Data Protection:`** Auto-detect masking ensures that all instances of sensitive data within a dataset are masked, providing a comprehensive approach to data security. This is especially valuable for scenarios where users may not be aware of all the potential data types that need protection
3. **`Reduced Human Error`:** Automated detection reduces the risk of human errors that can occur during manual identification and specification of sensitive data. It enhances accuracy and consistency in data protection processes.
4. **`Time and Resource Savings:`** Auto-detect masking saves time and effort, particularly when dealing with large amounts of data. Users do not need to spend time identifying each instance of sensitive data, allowing them to focus on other tasks.


---

# 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://help.protecto.ai/getting-started/protecto-overview/introduction/protecto-vault/tokenization-apis/masking/identify-and-mask-auto-detect.md?ask=<question>&goal=<endgoal>
```

`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.