How can I secure and manage access to my data when using the native LLM experiences?
Snowflake Cortex's native LLM experiences are built on the Snowflake platform, which is known for its security and compliance features. However, it is important to take additional steps to secure and manage access to your data when using these experiences.
Here are some tips:
Use access control lists (ACLs) to control who can access your data. You can grant permissions to specific users, groups, or roles.
Use resource monitors to track usage of your data. This can help you to identify any suspicious activity.
Use encryption to protect your data at rest and in transit. Snowflake Cortex provides a variety of encryption options, including Transparent Data Encryption (TDE) and Customer Managed Encryption (CME).
Use auditing to track all activity on your data. This can help you to investigate any security incidents.
In addition to these general security tips, you should also take the following steps to manage access to your data when using the native LLM experiences in Snowflake Cortex:
Use Snowflake's built-in data governance features. Snowflake Cortex provides a number of features to help you manage access to your data, such as row-level security and column-level security.
Use Snowflake's managed services, such as Snowflake Copilot and Snowflake Universal Search. These services can help you to further secure and manage access to your data.
Work with a Snowflake partner to get help with securing and managing access to your data. Snowflake has a number of partners who can provide you with assistance with security and data governance.
By following these tips, you can help to ensure that your data is secure when using the native LLM experiences in Snowflake Cortex.
Here are some additional tips for managing access to your data when using the native LLM experiences in Snowflake Cortex:
Use data tagging to classify your data. This will help you to identify and manage sensitive data.
Use data masking to protect sensitive data. Data masking can be used to hide sensitive data from unauthorized users.
Use data lineage to track the movement of your data. This will help you to identify where your data is stored and who has access to it.
Use data loss prevention (DLP) to prevent sensitive data from being leaked. DLP solutions can be used to monitor and block the transmission of sensitive data.
By following these tips, you can help to ensure that your data is managed securely when using the native LLM experiences in Snowflake Cortex.
In addition to the above, here are some specific security considerations for each of the native LLM experiences in Snowflake Cortex:
Document AI
Make sure to only upload documents to Document AI that you are authorized to access and share.
Use Document AI's access control features to control who can access your documents and the results of your document extraction tasks.
Monitor Document AI's audit logs to identify any suspicious activity.
Snowflake Copilot
Make sure to only use Snowflake Copilot to generate code from data that you are authorized to access.
Use Snowflake Copilot's access control features to control who can use Snowflake Copilot and what types of code they can generate.
Monitor Snowflake Copilot's audit logs to identify any suspicious activity.
Universal Search
Make sure to only use Universal Search to search for data that you are authorized to access.
Use Universal Search's access control features to control who can use Universal Search and what data they can search.
Monitor Universal Search's audit logs to identify any suspicious activity.
By following these security considerations, you can help to ensure that your data is secure when using the native LLM experiences in Snowflake Cortex.