> For the complete documentation index, see [llms.txt](https://help.nightfall.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.nightfall.ai/detection_platform/custom_detectors/dictionary_detector.md).
# Creating Dictionary Detector
Learn how to create a Dictionary detector in Nightfall.
A dictionary detector can detect a specific piece of sensitive data (referred to as a token). The token can be any type of sensitive data like a password, API key, IP address, PII, and so on. You must add the token to a file and then upload the file while creating the dictionary. Nightfall scans your data to check if the token present in the uploaded file exists in your data. If a match is found, it fis flagged as sensitive data exposure.
To create a Dictionary Detector:
1. Navigate to the Detectors section from the left pane.
2. Click **+ Custom Detector** and select **Dictionary**.
3. Enter a name for your custom Detector in the **Name** field.
4. (Optional) Enter a description for the Detector in the **Description** field.
5. Upload or drag and drop the text file which contains a token.
6. (Optional) Select the **Match substrings** check box to match the sub-strings of the text file.
7. Click **Add**.
---
# 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 by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://help.nightfall.ai/detection_platform/custom_detectors/dictionary_detector.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
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.
