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Event Information

  • The google.logging.v2.MetricsServiceV2.CreateLogMetric event in GCP for Logging refers to the creation of a log metric in the Google Cloud Logging service.
  • This event indicates that a user or automated process has created a new log metric, which is used to define custom metrics based on log entries in the Google Cloud Logging system.
  • The event provides information about the metric’s configuration, such as the metric name, filter expression, and the associated project and resource.

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Examples

  • Unauthorized access: If proper access controls are not implemented, unauthorized users may be able to create or modify log metrics using the google.logging.v2.MetricsServiceV2.CreateLogMetric API. This can lead to the creation of malicious or incorrect log metrics, impacting the security of the logging system.

  • Data leakage: If the google.logging.v2.MetricsServiceV2.CreateLogMetric API is misused, it can result in the creation of log metrics that capture sensitive or confidential information. This can lead to data leakage if the logs containing such information are not properly secured or restricted.

  • Denial of service: An attacker may attempt to overload the logging system by creating a large number of log metrics using the google.logging.v2.MetricsServiceV2.CreateLogMetric API. This can result in resource exhaustion and impact the availability and performance of the logging service, potentially leading to a denial of service situation.

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Remediation

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Using Console

  1. Enable GCP Logging:
  • Open the GCP Console and navigate to the Logging page.
  • Click on “Logs Explorer” in the left-hand menu.
  • Click on “Create Sink” to create a new log sink.
  • Select the desired log type, such as “Admin Activity” or “Data Access”.
  • Choose the log severity level and filter criteria as per your requirements.
  • Select the destination for the logs, such as BigQuery, Pub/Sub, or Cloud Storage.
  • Click on “Create Sink” to create the log sink.
  1. Configure Log Exports:
  • Open the GCP Console and navigate to the Logging page.
  • Click on “Exports” in the left-hand menu.
  • Click on “Create Export” to create a new log export.
  • Select the desired log type, such as “Admin Activity” or “Data Access”.
  • Choose the log severity level and filter criteria as per your requirements.
  • Select the destination for the logs, such as BigQuery, Pub/Sub, or Cloud Storage.
  • Configure any additional settings, such as format and delivery frequency.
  • Click on “Create Export” to create the log export.
  1. Set Up Log-Based Metrics:
  • Open the GCP Console and navigate to the Logging page.
  • Click on “Metrics” in the left-hand menu.
  • Click on “Create Metric” to create a new log-based metric.
  • Provide a name and description for the metric.
  • Select the desired log type, such as “Admin Activity” or “Data Access”.
  • Choose the log severity level and filter criteria as per your requirements.
  • Configure the aggregation and threshold settings for the metric.
  • Click on “Create Metric” to create the log-based metric.

Note: The above steps are general guidelines and may vary based on the specific requirements and configurations of your GCP environment. It is recommended to refer to the official GCP documentation for detailed instructions and best practices.

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Using CLI

  1. Enable GCP Logging for a specific project:

    • Use the command gcloud logging project-logs enable [PROJECT_ID] to enable GCP Logging for a specific project.
    • Replace [PROJECT_ID] with the ID of the project you want to enable logging for.

  2. Create a GCP Logging sink to export logs to Cloud Storage:

    • Use the command gcloud logging sinks create [SINK_NAME] storage.googleapis.com/[BUCKET_NAME] --log-filter="[LOG_FILTER]" to create a logging sink.
    • Replace [SINK_NAME] with the desired name for the sink.
    • Replace [BUCKET_NAME] with the name of the Cloud Storage bucket where you want to export the logs.
    • Replace [LOG_FILTER] with the filter expression to specify the logs you want to export.

  3. Configure GCP Logging to send logs to Cloud Pub/Sub:

    • Use the command gcloud logging sinks create [SINK_NAME] pubsub.googleapis.com/projects/[PROJECT_ID]/topics/[TOPIC_NAME] --log-filter="[LOG_FILTER]" to create a logging sink.
    • Replace [SINK_NAME] with the desired name for the sink.
    • Replace [PROJECT_ID] with the ID of the project.
    • Replace [TOPIC_NAME] with the name of the Cloud Pub/Sub topic where you want to send the logs.
    • Replace [LOG_FILTER] with the filter expression to specify the logs you want to send.

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Using Python

To remediate GCP Logging issues using Python, you can use the following approaches:

  1. Enable GCP Logging API:

    • Use the google-cloud-logging library to enable the GCP Logging API.
    • Install the library using pip install google-cloud-logging.
    • Use the following Python script to enable the GCP Logging API:
    from google.cloud import logging_v2

def enable_logging_api(project_id):
    client = logging_v2.LoggingServiceV2Client()
    project_name = f"projects/{project_id}"
    client.update_project(project_name, {"logging_service": "logging.googleapis.com"})

enable_logging_api("your-project-id")

  2. Create a Log Sink:

    • Use the google-cloud-logging library to create a log sink.
    • Install the library using pip install google-cloud-logging.
    • Use the following Python script to create a log sink:
    from google.cloud import logging_v2

def create_log_sink(project_id, sink_name, destination_bucket):
    client = logging_v2.ConfigServiceV2Client()
    project_name = f"projects/{project_id}"
    sink = {
        "name": sink_name,
        "destination": f"storage.googleapis.com/{destination_bucket}",
        "filter": "severity >= ERROR",
    }
    client.create_sink(project_name, sink)

create_log_sink("your-project-id", "your-sink-name", "your-destination-bucket")

  3. Export Logs to BigQuery:

    • Use the google-cloud-logging library to export logs to BigQuery.
    • Install the library using pip install google-cloud-logging.
    • Use the following Python script to export logs to BigQuery:
    from google.cloud import logging_v2

def export_logs_to_bigquery(project_id, dataset_id, table_id):
    client = logging_v2.ConfigServiceV2Client()
    project_name = f"projects/{project_id}"
    destination = f"bigquery.googleapis.com/projects/{project_id}/datasets/{dataset_id}/tables/{table_id}"
    sink = {
        "name": "export-logs-to-bigquery",
        "destination": destination,
        "filter": "severity >= ERROR",
    }
    client.create_sink(project_name, sink)

export_logs_to_bigquery("your-project-id", "your-dataset-id", "your-table-id")

Please note that you need to replace the placeholders (your-project-id, your-sink-name, your-destination-bucket, your-dataset-id, your-table-id) with the actual values specific to your GCP environment.