A Sensitive Data Protection action is something that occurs after an operation completes successfully or, in the case of emails, on error. For example, you can save findings to a BigQuery table, publish a notification to a Pub/Sub topic, or send an email when an operation either finishes successfully or stops on error.
When you run a Sensitive Data Protection job, a summary of its findings are saved by
default within Sensitive Data Protection. You can see this summary using
Sensitive Data Protection in the Google Cloud console. For
jobs, you can also retrieve summary information in the DLP API
Sensitive Data Protection supports different types of actions depending on the type of operation being run. The following are the supported actions.
Save findings to BigQuery
Save the Sensitive Data Protection job results to a BigQuery table. Before viewing or analyzing the results, first ensure that the job has completed.
Each time a scan runs, Sensitive Data Protection saves scan findings to the BigQuery table you specify. The exported findings contain details about each finding's location and match likelihood. If you want each finding to include the string that matched the infoType detector, enable the Include quote option.
If you don't specify a table ID, BigQuery assigns a default name to a new table the first time the scan runs. If you specify an existing table, Sensitive Data Protection appends scan findings to it.
When data is written to a BigQuery table, the billing and quota usage are applied to the project that contains the destination table.
If you don't save findings to BigQuery, the scan results only contain statistics about the number and infoTypes of the findings.
Publish to Pub/Sub
Publish a notification that contains the name of the Sensitive Data Protection job as an attribute to a Pub/Sub channel. You can specify one or more topics to send the notification message to. Make sure that the Sensitive Data Protection service account running the scan job has publishing access on the topic.
If there are configuration or permission issues with the Pub/Sub topic, Sensitive Data Protection retries sending the Pub/Sub notification for up to two weeks. After two weeks, the notification is discarded.
Publish to Security Command Center
Publish a summary of the job results to Security Command Center. For more information, see Send Sensitive Data Protection scan results to Security Command Center.
Publish to Dataplex
Send job results to Dataplex, Google Cloud's metadata management service.
Notify by email
Send an email when the job completes. The email goes to IAM project owners and technical Essential Contacts.
Publish to Cloud Monitoring
Send inspection results to Cloud Monitoring in Google Cloud's operations suite.
Make a de-identified copy
De-identify any findings in the inspected data, and write the de-identified content to a new file. You can then use the de-identified copy in your business processes, in place of data that contains sensitive information. For more information, see Create a de-identified copy of Cloud Storage data using Sensitive Data Protection in the Google Cloud console.
The following table shows the Sensitive Data Protection operations and where each action is available.
|Action||BigQuery inspection||Cloud Storage inspection||Datastore inspection||Hybrid inspection||Risk analysis||Data profiling|
|Save findings to BigQuery||✓||✓||✓||✓||✓||✓|
|Publish to Pub/Sub||✓||✓||✓||✓||✓||✓|
|Publish to Security Command Center||✓||✓||✓|
|Publish to Data Catalog||✓|
|Notify by email||✓||✓||✓||✓||✓|
|Publish to Cloud Monitoring||✓||✓||✓||✓|
You can specify one or more actions when you configure a Sensitive Data Protection:
- When you create a new inspection or risk analysis job using Sensitive Data Protection in the Google Cloud console, specify actions in the Add actions section of the job creation workflow.
- When you configure a new job request to send to the DLP API,
specify actions in the
For more information and sample code in several languages, see:
- Creating and scheduling inspection jobs
- Computing k-anonymity for a dataset
- Computing l-diversity for a dataset
Example action scenario
You can use Sensitive Data Protection actions to automate processes based on
Sensitive Data Protection scan results. Suppose you have a BigQuery
table shared with an external partner. You want to ensure both that this table
does not contain any sensitive identifiers like US Social Security numbers
and that, if you find any, access is revoked from the partner. Here is a rough
outline of a workflow that would use actions:
- Create a Sensitive Data Protection job trigger to run an inspection scan of the BigQuery table every 24 hours.
- Set the action of these jobs to publish a Pub/Sub notification to the topic "projects/foo/scan_notifications."
- Create a Cloud Function that listens for incoming messages on "projects/foo/scan_notifications." This Cloud Function will receive the name of the Sensitive Data Protection job every 24 hours, call Sensitive Data Protection to get summary results from this job, and, if it finds any Social Security numbers, it can change settings in BigQuery or Identity and Access Management (IAM) to restrict access to the table.
- Learn about the actions available with inspection jobs.
- Learn about the actions available with risk analysis jobs.