1. Open the GCP console and navigate to the BigQuery service.
2. Click on the “Navigation Menu” icon on the top-left corner of the console.
3. From the menu, select “BigQuery”.
4. In the BigQuery console, click on the “Settings” icon on the left-hand side panel.
5. Click on the “Audit logs” tab.
6. Under the “Audit logs” tab, click on the “Configure” button.
7. In the “Configure audit logs” window, select the checkbox next to “Data access”.
8. Select the checkbox next to “Cloud audit logs”.
9. Click on the “Save” button.
10. Once the configuration is saved, the user activity logging for BigQuery is enabled.

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1. Open the GCP Console and navigate to the BigQuery service.
2. Click on the “Logs” tab in the left-hand menu.
3. Click on the “Audit Logs” tab.
4. Click on the “Create Sink” button.
5. Select the “BigQuery” destination.
6. Choose the project and dataset where you want to store the audit logs.
7. Click on the “Create Sink” button.
8. Open the Cloud Shell or terminal on your local machine and install the Google Cloud SDK.
9. Authenticate using your GCP account credentials by running the command gcloud auth login.
10. Set the project ID by running the command gcloud config set project PROJECT_ID.
11. Create a new Python file and import the necessary libraries:

from google.cloud import logging_v2
from google.cloud.logging_v2 import enums

12. Initialize the Logging client:

logging_client = logging_v2.LoggingServiceV2Client()

13. Define the BigQuery dataset ID and table ID where you want to store the audit logs:

dataset_id = 'DATASET_ID'
table_id = 'TABLE_ID'

14. Define the Sink ID for the BigQuery sink:

sink_name = f"projects/{project_id}/sinks/{sink_id}"

15. Create a new Sink object for the BigQuery sink:

sink = logging_v2.LogSink(
    name=sink_name,
    destination=destination,
    filter_=filter_,
    output_version_format=enums.LogSink.VersionFormat.V2,
    bigquery_options=bigquery_options
)

16. Update the Sink configuration:

update_mask = logging_v2.field_mask.FieldMask(
    paths=["destination", "filter", "bigquery_options"]
)

response = logging_client.update_sink(
    request={
        "sink_name": sink_name,
        "sink": sink,
        "update_mask": update_mask,
    }
)

17. Verify that the Sink configuration was updated successfully by checking the response:

print(f"Sink updated: {response}")

18. Run the Python script to remediate the misconfiguration.