> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wisdom.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Column-Level Security (CLS)
This tutorial demonstrates how to protect sensitive information in your datasets while still enabling high-level analysis on the unmasked columns within a row. You will learn how to configure Column-Level Security (CLS) to mask specific values based on user attributes.
## Configure CLS
Follow these steps to configure CLS:
1. Navigate to the **Data Sources** tab in your project.
2. Select the table you wish to modify (e.g., `Account`).
3. Ensure that **Show advanced options** is toggled on in the top-right corner.
4. Locate your sensitive column and click **Configure** under the **CLS Masking** column.
5. In the **Column-Level Security** modal, provide a SQL expression that determines how the data is displayed at query time.
6. Click **Save**. The status badge in the CLS Masking column will now show as Active.
If you enter an incorrect value, such as a column name that doesn't exist, the system will alert you to the error and will not let you save it.
## Verifying the Implementation
Once active, CLS functions as a global security layer. It automatically enforces your masking logic across **WisdomAI Chat**, **Dashboards**, the **SQL Playground**, and **Data Source Previews**.
For unauthorized users, protected data will appear as hashed values. It is important to remember that CLS is applied strictly at the column level.
**Avoid Data Leakage**: If you protect a column (e.g., `Customer Name`) but leave a correlative column unprotected (e.g., `Customer Email`), an unauthorized user will see the hashed name, but the clear-text email address. Ensure you apply masking to all columns that could potentially identify the sensitive entity.
## Next Steps
Manage user roles, permissions, and access to the platform.
Walk through the initial setup to connect a data source and run your first query.