V1.compute.instances.stop remediation

​

Event Information

• The v1.compute.instances.stop event in GCP for Compute refers to the action of stopping a virtual machine instance in the Google Cloud Platform.
• This event indicates that the virtual machine instance has been intentionally halted, temporarily suspending its operation and releasing any allocated resources.
• Stopping an instance can be useful for cost optimization, as it allows you to avoid paying for idle resources when the instance is not in use. Additionally, it can be used for maintenance purposes or to scale down resources during periods of low demand.

​

Examples

1. Unauthorized access: If security is impacted with v1.compute.instances.stop in GCP, it could potentially allow unauthorized users to stop instances, leading to service disruption or unauthorized access to sensitive data. This can occur if proper access controls and permissions are not in place, allowing unauthorized users to execute the stop command.
2. Denial of Service (DoS) attacks: If security is impacted with v1.compute.instances.stop in GCP, an attacker could potentially launch a DoS attack by repeatedly stopping instances. This can result in service unavailability and impact the availability of other resources running on the same infrastructure.
3. Data loss or corruption: If security is impacted with v1.compute.instances.stop in GCP, there is a risk of data loss or corruption if instances are stopped abruptly without proper shutdown procedures. This can lead to data inconsistency or potential data corruption, especially if applications or databases are not designed to handle sudden shutdowns. It is important to ensure proper backup and recovery mechanisms are in place to mitigate this risk.

​

Remediation

​

Using Console

1. Enable VPC Flow Logs:
   • Go to the GCP Console and navigate to the VPC network page.
   • Select the VPC network where you want to enable flow logs.
   • Click on “Edit” at the top of the page.
   • Scroll down to the “Flow logs” section and click on “Enable flow logs”.
   • Configure the desired flow log settings, such as the filter, destination, and sampling rate.
   • Click on “Save” to enable flow logs for the selected VPC network.
2. Enable CloudTrail for GCP:
   • Go to the GCP Console and navigate to the CloudTrail page.
   • Click on “Create a new trail” to create a new CloudTrail configuration.
   • Provide a name for the trail and select the desired GCP project.
   • Choose the services for which you want to enable CloudTrail logging.
   • Configure the storage settings, such as the bucket name and object prefix.
   • Optionally, enable log file validation and data events.
   • Click on “Create” to enable CloudTrail for the selected GCP project.
3. Enable Security Center for GCP:
   • Go to the GCP Console and navigate to the Security Command Center page.
   • Click on “Enable Security Command Center” to enable Security Center for the selected GCP project.
   • Wait for the Security Command Center to be enabled.
   • Once enabled, navigate to the Security Command Center dashboard.
   • Review the security findings and recommendations provided by Security Center.
   • Take necessary actions to remediate the identified security issues based on the recommendations.

​

Using CLI

1. Disable SSH access for the default service account:
   • Use the following command to get the email address of the default service account:
     Copy

     Ask AI

     gcloud iam service-accounts list --filter="displayName:Compute Engine default service account"
     

   • Once you have the email address, use the following command to remove the roles associated with SSH access:
     Copy

     Ask AI

     gcloud projects remove-iam-policy-binding PROJECT_ID --member=serviceAccount:EMAIL_ADDRESS --role=roles/compute.osLogin
     

2. Enable VPC Flow Logs for network monitoring:
   • Use the following command to enable VPC Flow Logs for a specific subnet:
     Copy

     Ask AI

     gcloud compute networks subnets update SUBNET_NAME --region=REGION --enable-flow-logs
     

3. Restrict public access to Cloud Storage buckets:
   • Use the following command to update the bucket ACL and remove all public access:
     Copy

     Ask AI

     gsutil iam ch allUsers:legacyObjectReader gs://BUCKET_NAME
     gsutil iam ch allAuthenticatedUsers:legacyObjectReader gs://BUCKET_NAME
     

​

Using Python

1. Enforce secure OS configurations:
   • Use the google-cloud-sdk library to retrieve the list of GCP Compute instances.
   • Iterate through each instance and check the OS configuration settings.
   • Use the googleapiclient library to update the instance settings and enforce secure configurations.
   • Example Python script:
     Copy

     Ask AI

     from google.cloud import compute_v1
     
     def enforce_secure_os_config(project_id):
         compute_client = compute_v1.InstancesClient()
         instances = compute_client.list(project=project_id)
         
         for instance in instances:
             # Check OS configuration settings
             if instance.os_config.secure_boot == False:
                 # Update instance settings to enforce secure boot
                 instance.os_config.secure_boot = True
                 compute_client.update(project=project_id, instance=instance)
     

2. Implement network security controls:
   • Use the google-cloud-sdk library to retrieve the list of GCP Compute instances.
   • Iterate through each instance and check the network security controls.
   • Use the googleapiclient library to update the instance settings and implement necessary network security controls.
   • Example Python script:
     Copy

     Ask AI

     from google.cloud import compute_v1
     
     def implement_network_security_controls(project_id):
         compute_client = compute_v1.InstancesClient()
         instances = compute_client.list(project=project_id)
         
         for instance in instances:
             # Check network security controls
             if instance.network_config.firewall_rules == []:
                 # Add necessary firewall rules
                 firewall_rule = compute_v1.FirewallRule(...)
                 compute_client.insert(project=project_id, firewall_rule=firewall_rule)
     

3. Enable logging and monitoring:
   • Use the google-cloud-sdk library to retrieve the list of GCP Compute instances.
   • Iterate through each instance and enable logging and monitoring.
   • Use the googleapiclient library to update the instance settings and enable necessary logging and monitoring.
   • Example Python script:
     Copy

     Ask AI

     from google.cloud import compute_v1
     
     def enable_logging_and_monitoring(project_id):
         compute_client = compute_v1.InstancesClient()
         instances = compute_client.list(project=project_id)
         
         for instance in instances:
             # Enable logging and monitoring
             instance.logging_config.enable = True
             instance.monitoring_config.enable = True
             compute_client.update(project=project_id, instance=instance)