What the data for this category looks like
Data for this category primarily comes from internal enterprise databases, data dictionaries, masking tools, and access approval systems. Update frequency is once per batch task or project. Daily output documents include masking plans, field mapping tables, masking validation reports, and approval records. Field mapping tables must include fields such as sensitive field names, masking rule codes, and associated business modules. Masking validation reports must label validation batches, compliance items, result status, and other content. All data is stored as structured documents or structured database tables.
Constraints on permissions and data isolation
Data sources include sensitive information from multiple systems. Cross-departmental access must be strictly restricted. Unauthorized personnel must not access raw sensitive database data. Permissions configurations must adjust dynamically with tasks, to match the per-project or per-batch update pattern. Leftover old permissions can lead to cross-project data leaks, so dynamic adjustments are required. Daily output documents such as approval records contain traces of sensitive operations. These documents must only be accessible to compliant personnel. Documents such as field mapping tables include mappings between sensitive fields and rules. Only data security engineers may edit these documents. Unauthorized modification of masking rules is prevented by this restriction.
Configuration guidelines
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
teamId | Assign a unique teamId for each masking project | Implement project-level data isolation to prevent cross-project data leaks |
tmbId | Assign tmbId permission scopes by job role. Data security engineers: full permissions. On-call operations personnel: only view masking data associated with tickets. Compliant personnel: only view validation reports and approval records | Align with job responsibilities, follow the principle of least privilege |
| Sensitive field access control | Only root accounts and data security engineers may edit sensitive field configurations | Prevent unauthorized modification of sensitive field configurations |
| Team data storage quota | 1000 MB per team | Limit resource usage per team for masked data, prevent resource contention |
| Team data retention period | 30 days | Meet compliance requirements for data retention, avoid expired data leaks |
| Single task timeout threshold | 300 seconds | Prevent masking tasks from occupying system resources for extended periods |
Three common configuration errors
- Scenario: On-call operations personnel can view unmasked user ID number fields. Cause:
tmbIdpermission scopes were not configured by job role. Full permissions for the full masked dataset were granted to non-authorized roles, creating personal information leakage risks. - Scenario: Deleted team members can still access corresponding masked data. Cause: Permission caches associated with
teamIdwere not updated synchronously. Leftover old permissions cause data isolation failures. - Scenario: Compliant personnel cannot view masking validation reports. Cause: Compliant personnel were incorrectly bound to the on-call operations role. Corresponding view permissions were not matched, leading to incorrect permission configurations.
How to confirm proper configuration
- Log in to accounts with different roles, verify that only authorized personnel can access specified masked datasets and corresponding documents.
- Check the binding relationship between
teamIdandtmbId, confirm that permission scopes for each masking project match the configured settings. - Attempt to modify sensitive field configurations, verify that only authorized roles can perform this action.
- Trigger a masking task, verify that approval records are only visible to compliant personnel.
The values given are common starting points. They should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.