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Table-based SQL audit logging gives you detailed information about queries being executed against your system. This feature is especially useful when you want to log all queries that are run against a table containing personally identifiable information (PII). It consists of using the command to enable the logging channel per table. This page provides an example of SQL audit logging in CockroachDB, including:
  • How to turn audit logging on and off.
  • Where the audit log files live.
  • What the audit log files look like.
Note that enabling SQL audit logs can negatively impact performance. As a result, we recommend using SQL audit logs for security purposes only. For more details, see Performance considerations.
For the best visibility into security-related events on your cluster, we recommend configuring SENSITIVE_ACCESS together with the USER_ADMIN, PRIVILEGES, and SESSIONS logging channels. To learn more, see .

File format

Audit log messages, like all , consist of two sections:
  • A payload that contains notable events structured in JSON. These can include information such as the application name, full text of the query (which may contain PII), user account that triggered the event, number of rows produced (e.g., for SELECT) or processed (e.g., for INSERT or UPDATE), status of the query, and more. For more information on the possible event types logged to the SENSITIVE_ACCESS channel, see .
  • An envelope that contains event metadata (e.g., severity, date, timestamp, channel). Depending on the log format you specify when , the envelope can be formatted either as JSON or as a flat prefix to the message.

File storage location

By , audit logs are prefixed cockroach-sql-audit and are stored in the as the other logs generated by CockroachDB. To store the audit log files in a specific directory, with a custom dir path.
If your deployment requires particular lifecycle and access policies for audit log files, point SENSITIVE_ACCESS to a directory that has permissions set so that only CockroachDB can create/delete files.

Performance considerations

To ensure non-repudiation in audit logs, we recommend for the SENSITIVE_ACCESS channel. CockroachDB will then synchronously log all of the activity of every user on a cluster in a way that is durable to system failures. Note that every query that causes a logging event must access the disk of the node on which audit logging is enabled. As a result, enabling auditable on a logging channel negatively impacts performance, and we recommend using this setting for security purposes only. For debugging and troubleshooting on production clusters, the most performant way to log all queries is to enable the SQL_EXEC logging channel. For details, see .

Example

Step 1. Create sample tables

Use the statements below to create:
  • A customers table which contains PII such as name, address, etc.
  • An orders table with a foreign key into customers, which does not expose any PII
Later, we’ll show how to turn on auditing for the customers table.

Step 2. Turn on auditing for the customers table

We turn on auditing for a table using the subcommand of .
This directs for the customers table into the logging channel.
To turn on auditing for more than one table, issue a separate ALTER statement for each table.

Step 3. Populate the customers table

Now that we have auditing turned on, let’s add some customer data:
Now let’s verify that our customers were added successfully:

Step 4. Check the audit log

By , events in the SENSITIVE_ACCESS channel are output to a log file that is prefixed cockroach-sql-audit and stored in the as the other logs generated by CockroachDB. To store the audit log files in a specific directory, with a custom dir path. Like the other log files, it’s rotated according to the . When we look at the audit log for this example, we see the following lines showing every command we’ve run so far, as expected.
The above example shows the default log format. This can be changed to another format (e.g., JSON). For details, see .
For descriptions of all SQL audit event types and their fields, see .

Step 5. Populate the orders table

Unlike the customers table, orders doesn’t have any PII, just a Product ID and a delivery status. Let’s populate the orders table with some placeholder data using :
Evaluate the below a few times to generate data; note that this would error if returned multiple results, but it doesn’t in this case.
Let’s verify that our orders were added successfully:

Step 6. Check the audit log again

Because we used a SELECT against the customers table to generate the placeholder data for orders, those queries will also show up in the audit log. Note that two log entries are created for each query: one entry for the SELECT subquery, and one entry for the foreign key check on customer_id. Since the customers table is read twice with each query, the TableName and TxnCounter values will be duplicated across entries:
The above example shows the default log format. This can be changed to another format (e.g., JSON). For details, see . For descriptions of all SQL audit event types and their fields, see .

See also