Multi-level data security protection system
In enterprise data query scenarios, SQLBot realizes security control through its original workspace resource isolation architecture. Each workspace forms an independent logical unit, containing exclusive data source configuration, model instance and query history. Administrators can create different spaces for sales, finance, etc. according to the organizational structure, and set up fine-grained permissions based on the RBAC model: including data source access permissions, table-level read/write control, and even field-level desensitization rules for sensitive data.
The security mechanism in the actual application is as follows: when a member of the marketing department queries "customer contact information", the system will verify whether his/her workspace is authorized to access the CRM database, and automatically filter the sensitive fields outside the permissions. Audit logs record the query time, user and generated SQL statements to meet GDPR and other compliance requirements.
Compared to traditional BI tools, this design retains the convenience of natural language querying and effectively prevents the risk of unauthorized access and data leakage through the triple protection of permission labeling, data desensitization, and query auditing.
This answer comes from the articleSQLBot: The Intelligent Bot That Converts Natural Language to SQL QueriesThe
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