Google.firestore.admin.v1.firestoreadmin.deleteindex

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Event Information

• The google.firestore.admin.v1.FirestoreAdmin.DeleteIndex event in GCP for Firestore indicates that an index has been deleted in the Firestore database.
• This event is triggered when a user or an automated process initiates the deletion of an index in Firestore.
• Deleting an index can impact the performance of queries that rely on that index, so it is important to carefully consider the implications before deleting an index.

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Examples

1. Unauthorized deletion of indexes: If security is impacted with google.firestore.admin.v1.FirestoreAdmin.DeleteIndex in GCP for Firestore, it could potentially allow unauthorized individuals to delete indexes. This could lead to data loss, disruption of services, and potential security breaches.
2. Data exposure: If security is impacted with google.firestore.admin.v1.FirestoreAdmin.DeleteIndex in GCP for Firestore, it could result in the exposure of sensitive data. If an index is deleted without proper authorization or validation, it may inadvertently expose sensitive information to unauthorized users.
3. Service disruption: If security is impacted with google.firestore.admin.v1.FirestoreAdmin.DeleteIndex in GCP for Firestore, it could cause service disruption. Deleting indexes without proper authorization or validation could lead to performance issues, slow queries, and overall degradation of the Firestore service, impacting the availability and reliability of applications relying on Firestore.

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Remediation

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Using Console

1. Enable VPC Service Controls:
   • Go to the GCP Console and navigate to the VPC Service Controls page.
   • Click on “Create Perimeter” and provide a name for the perimeter.
   • Select the project where your Firestore instance is located.
   • Choose the appropriate VPC network and subnet for the perimeter.
   • Add the necessary access levels and permissions for the perimeter.
   • Review the configuration and click on “Create” to enable VPC Service Controls.
2. Implement IAM Roles and Permissions:
   • Go to the IAM & Admin section in the GCP Console.
   • Select the project where your Firestore instance is located.
   • Click on “IAM” and then “Add”.
   • Enter the email address of the user or service account that needs access to Firestore.
   • Choose the appropriate IAM role(s) based on the required level of access.
   • Click on “Save” to grant the roles and permissions to the user or service account.
3. Enable Audit Logging:
   • Go to the GCP Console and navigate to the Firestore page.
   • Select the project and Firestore instance you want to enable audit logging for.
   • Click on “Edit” and scroll down to the “Audit Logging” section.
   • Enable the desired audit logs, such as Admin Read, Data Read, and Data Write.
   • Choose the destination for the logs, such as Cloud Storage or BigQuery.
   • Configure any additional settings, such as log retention period.
   • Click on “Save” to enable audit logging for Firestore.

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Using CLI

1. Enable audit logging:
   • Use the following command to enable audit logging for Firestore:
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     Ask AI

     gcloud firestore databases patch [DATABASE_ID] --log-exclusion-names=cloudaudit.googleapis.com%2Factivity
     

2. Implement VPC Service Controls:
   • Create a VPC Service Control perimeter using the following command:
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     Ask AI

     gcloud access-context-manager perimeters create [PERIMETER_ID] --resources=projects/[PROJECT_ID]/locations/[LOCATION]/buckets/[BUCKET_NAME] --restricted-services=firestore.googleapis.com
     

   • Associate the VPC Service Control perimeter with the project using the following command:
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     Ask AI

     gcloud access-context-manager access-policies update [ACCESS_POLICY_ID] --add-perimeter=[PERIMETER_ID]
     

3. Enable data encryption at rest:
   • Use the following command to enable data encryption at rest for Firestore:
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     Ask AI

     gcloud firestore databases patch [DATABASE_ID] --location=[LOCATION] --enable-encryption
     

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Using Python

1. Enable Firestore Audit Logs:
   • Use the Google Cloud Python SDK to enable Firestore Audit Logs for your project.
   • You can use the google-cloud-logging library to create a sink that exports Firestore Audit Logs to Cloud Logging.
   • Here’s an example Python script to enable Firestore Audit Logs:
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   Ask AI

   from google.cloud import logging_v2
   
   def enable_firestore_audit_logs(project_id, firestore_dataset):
       client = logging_v2.LoggingServiceV2Client()
       parent = f"projects/{project_id}"
       sink_name = f"{parent}/sinks/firestore-audit-logs"
       filter_expr = f'resource.type="cloud_firestore_database" AND log_name="projects/{project_id}/logs/cloudaudit.googleapis.com%2Factivity"'
       destination = f"bigquery.googleapis.com/projects/{project_id}/datasets/{firestore_dataset}"
   
       sink = {
           "name": sink_name,
           "filter": filter_expr,
           "destination": destination,
           "output_version_format": "V2",
       }
   
       response = client.create_sink(parent, sink)
       print(f"Enabled Firestore Audit Logs with sink name: {response.name}")
   
   enable_firestore_audit_logs("your-project-id", "your-firestore-dataset")
   

2. Implement Access Controls:
   • Use the Google Cloud Python SDK to implement access controls for Firestore.
   • You can use the google-cloud-iam library to manage IAM policies for Firestore.
   • Here’s an example Python script to grant a user the roles/datastore.owner role for a Firestore database:
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   Ask AI

   from google.cloud import firestore
   from google.cloud.iam_v1 import Policy
   
   def grant_firestore_access(project_id, firestore_database, user_email):
       client = firestore.Client(project=project_id)
       database_path = f"projects/{project_id}/databases/{firestore_database}"
       policy = client.get_iam_policy(request={"resource": database_path})
   
       policy.bindings.add(
           role="roles/datastore.owner",
           members=[f"user:{user_email}"],
       )
   
       updated_policy = client.set_iam_policy(request={"resource": database_path, "policy": policy})
       print(f"Granted user {user_email} the roles/datastore.owner role for Firestore")
   
   grant_firestore_access("your-project-id", "your-firestore-database", "[email protected]")
   

3. Implement Data Encryption:
   • Use the Google Cloud Python SDK to implement data encryption for Firestore.
   • You can use the google-cloud-kms library to encrypt and decrypt Firestore data using Cloud KMS.
   • Here’s an example Python script to encrypt and decrypt a Firestore document:
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   Ask AI

   from google.cloud import firestore
   from google.cloud import kms_v1
   
   def encrypt_firestore_document(project_id, firestore_database, document_path, plaintext):
       client = firestore.Client(project=project_id)
       document_ref = client.document(firestore_database, document_path)
       encrypted_data = client._firestore_v1beta1._datastore_api.encrypt_document(
           request={"name": document_ref._document_path, "plaintext": plaintext}
       )
       document_ref.set(encrypted_data.ciphertext)
   
   def decrypt_firestore_document(project_id, firestore_database, document_path):
       client = firestore.Client(project=project_id)
       document_ref = client.document(firestore_database, document_path)
       encrypted_data = document_ref.get().to_dict()
       decrypted_data = client._firestore_v1beta1._datastore_api.decrypt_document(
           request={"name": document_ref._document_path, "ciphertext": encrypted_data}
       )
       print(f"Decrypted document: {decrypted_data.plaintext}")
   
   encrypt_firestore_document("your-project-id", "your-firestore-database", "your-document-path", "your-plaintext")
   decrypt_firestore_document("your-project-id", "your-firestore-database", "your-document-path")