Professional-Cloud-Security-Engineer Exam Dumps - Google Cloud Certified - Professional Cloud Security Engineer

Objective: Optimize the usage of Cloud Data Loss Prevention (DLP) API to reduce costs.

Solution:

rowsLimit and bytesLimitPerFile: These parameters help in sampling data instead of scanning the entire dataset, thereby reducing the amount of data processed.

CloudStorageRegexFileSet: This feature allows you to specify a subset of files to be scanned using regular expressions, limiting the scope and volume of data scanned.

Steps:

Step 1: Set appropriate rowsLimit values for BigQuery data scans to sample rows instead of scanning entire tables.

Step 2: Set bytesLimitPerFile values for Cloud Storage buckets to limit the number of bytes scanned per file.

Step 3: Use CloudStorageRegexFileSet to specify the subset of files to be scanned based on patterns that match the filenames.

By combining these strategies, you effectively reduce the scope and volume of data processed by the DLP API, leading to cost savings.

References:

DLP API Best Practices

Configuring Finding Limits

Objective: Implement an encryption at-rest strategy that balances key management complexity and control for sensitive and non-sensitive data, ensuring FIPS 140-2 L1 compliance.

Solution: Use Google default encryption for non-sensitive data and Cloud Key Management Service (KMS) for sensitive data.

Steps:

Step 1: Store non-sensitive data using Google Cloud’s default encryption, which automatically encrypts data at rest without additional configuration.

Step 2: For sensitive data, use Cloud KMS to create and manage encryption keys.

Step 3: Configure key rotation policies for the keys managed by Cloud KMS to meet compliance requirements.

Step 4: Ensure that all data encryption keys used by Cloud KMS comply with FIPS 140-2 Level 1 standards.

By using Google default encryption for non-sensitive data and Cloud KMS for sensitive data, you can manage encryption efficiently while maintaining control over key residency and rotation for sensitive data.

References:

Google Cloud Default Encryption

Cloud Key Management Service

FIPS 140-2 Compliance

To ensure that only trusted container images are deployed on Cloud Run, you can implement Binary Authorization, which is a deploy-time security control that ensures only trusted images are used.

Set Up Binary Authorization:

Navigate to the Google Cloud Console.

Go to Security > Binary Authorization.

Configure the policy to include attestors that verify your trusted images.

Enable Binary Authorization on Cloud Run:

Go to the Cloud Run service.

Enable Binary Authorization on your existing Cloud Run services by selecting the appropriate Binary Authorization policy.

Set Organization Policy:

Go to the Organization Policies page in the Google Cloud Console.

Add a constraint for constraints/run.allowedBinaryAuthorizationPolicies.

Specify the list of allowed Binary Authorization policy names to enforce across your organization.

These steps ensure that any container image deployed on Cloud Run is validated against the specified Binary Authorization policies, preventing untrusted images from being deployed.

References:

Binary Authorization Documentation

Enabling Binary Authorization on Cloud Run

"However, even though it is possible to uses tags for target filtering in this manner, we recommend that you use service accounts where possible. Target tags are not access-controlled and can be changed by someone with the instanceAdmin role while VMs are in service. Service accounts are access-controlled, meaning that a specific user must be explicitly authorized to use a service account. There can only be one service account per instance, whereas there can be multiple tags. Also, service accounts assigned to a VM can only be changed when the VM is stopped"