Pass the Google Google Cloud Certified Professional-Cloud-Security-Engineer Questions and answers with CertsForce

In Google Cloud, the best practice for micro-segmentation and tier isolation is to use a single VPC with multiple subnets and apply firewall rules using Service Accounts or Network Tags. Using Service Accounts is generally preferred over tags because they are identity-based and more secure.

According to the Google Cloud Security Foundations Guide:

"Segment your VPC networks into subnets to provide logical isolation. Use firewall rules to control traffic between tiers. Instead of relying on IP addresses, use service accounts to define source and destination for firewall rules. This ensures that even if an IP changes, the security policy remains enforced based on the identity of the workload."

Implementation Details:

Web Tier: Use a firewall rule allowing 0.0.0.0/0 (Internet) to the Service Account associated with the web VMs on port 80/443.

App Tier: Use a firewall rule allowing traffic ONLY from the Web Tier Service Account to the App Tier Service Account.

DB Tier: Use a firewall rule allowing traffic ONLY from the App Tier Service Account to the DB Tier Service Account.

Identity-Aware Proxy (IAP) controls access to web resources based on user identity and context, not network firewalls (like Option B). The tool used to define the contextual requirements (IP range) and identity (group membership) is an Access Level within Access Context Manager.

Access Level: Defines the required context (e.g., source IP range of the internal network) and the required identity attributes (e.g., user is a member of the AppDev group).

IAP Policy: The IAP policy for the Cloud Run application is then configured to only allow access if the user meets the conditions defined in the Access Level.

Extracts:

"Identity-Aware Proxy works by verifying a user's identity and context of the request to determine if the user should be allowed to access an application." (Source 3.1)

"When you set an IAP policy, you can define an Access Level from Context-Aware Access to enforce conditions based on user location (IP address), security status, and device policy, along with user identity/group membership." (Source 3.2)

"IAP with Context-Aware Access is the recommended zero-trust approach for enforcing both identity (AppDev group) and context (internal IP address) requirements." (Source 3.3)

https://cloud.google.com/identity/solutions/automate-user-provisioning#cloud_identity_automated_provisioning

"Cloud Identity has a catalog of automated provisioning connectors, which act as a bridge between Cloud Identity and third-party cloud apps."

To delegate management of access control permissions to each business unit effectively, organizing projects into folders and assigning permissions to Google groups at the folder level allows for scalable and manageable access control. Using Google Cloud Directory Sync (GCDS) to synchronize users and groups from the on-premises directory service ensures that access controls are maintained and updated automatically as users change roles or leave the company.

Steps:

Organize Projects in Folders: Create a folder structure in the Google Cloud Resource Manager to organize projects by business unit.

Assign Permissions to Google Groups: Use IAM to assign necessary permissions to Google Groups at the folder level, ensuring each business unit can manage access controls for their own projects.

Synchronize Users and Groups: Use GCDS to sync users and group memberships from your on-premises directory service to Google Cloud Identity, ensuring that changes in the on-premises directory are reflected in Google Cloud.

The problem is the detection of secrets (sensitive data patterns) within the environment variables of deployed resources (Cloud Functions) in a timely, automated manner.

Sensitive Data Protection (SDP), formerly Cloud DLP, is the purpose-built Google Cloud service for scanning and classifying sensitive data patterns. It can be configured to scan code, configuration, or environment variables and integrate its findings directly with Security Command Center (SCC).

Extracts:

"Sensitive Data Protection provides highly configurable, automated detection of sensitive data, including API keys, passwords, and other credentials, using both pre-built and custom infoTypes." (Source 8.1)

"SDP can be integrated with Cloud Functions and other resource configurations to scan environment variables or configuration files for secrets. Violations can be automatically routed to Security Command Center as findings." (Source 8.2)

Option D (DAST) scans the application code or running application logic, but the requirement specifies the secrets are in the environment variables, which are part of the configuration/deployment metadata, making SDP the correct detection tool.

To maintain proper security policies across numerous Google Cloud environments, especially with a large developer base and a small security team, it's crucial to implement automated and scalable security measures.​

Option A: While applying AI-recommended security posture templates can be beneficial, as of now, there isn't a specific predefined template for Gemini in Vertex AI within the Security Command Center.​

Option B: Publishing internal policies and guidelines is essential for promoting secure development practices but may not be sufficient alone to enforce or detect security policies.​

Option C: Implementing the principle of least privilege through Identity and Access Management (IAM) roles minimizes the risk of misconfigurations and unauthorized access by ensuring users have only the permissions necessary for their tasks.​

Option D: Applying organization policy constraints enforces specific configurations and restrictions across projects. Utilizing Security Health Analytics helps in detecting and monitoring deviations from these policies, providing automated insights into potential security issues.​

Option E: Using Cloud Logging to detect misconfigurations and triggering Cloud Run functions for remediation introduces complexity and may require significant maintenance, making it less practical for a small security team.​

Therefore, Options C and D are the most effective strategies. They provide automated enforcement and monitoring of security policies, aligning with the need for scalable solutions given the organization's size and resources.​

To securely access Google Cloud APIs from CI/CD pipelines running on Google Kubernetes Engine (GKE), follow these steps:

Create Service Accounts:

Create individual service accounts for each CI/CD pipeline. This ensures isolation and minimal permissions per pipeline.

Use a naming convention that includes an identifier for each pipeline, such as pipeline-a-sa, pipeline-b-sa, etc.

Configure Kubernetes Service Accounts:

Create Kubernetes service accounts for each CI/CD pipeline pod.

Map Kubernetes Service Accounts to Google Service Accounts:

Use Workload Identity to associate Kubernetes service accounts with the corresponding Google service accounts. This allows the pods to authenticate to Google Cloud APIs securely.

Example command to bind the Kubernetes service account to the Google service account:

gcloud iam service-accounts add-iam-policy-binding \ --role roles/iam.workloadIdentityUser \ --member "serviceAccount:.svc.id.goog[/]" \ @.iam.gserviceaccount.com

Deploy CI/CD Pipelines:

Ensure each pipeline runs in dedicated pods that use the specific Kubernetes service accounts configured earlier.

This setup ensures that each pipeline has the necessary permissions to interact with Google Cloud APIs securely, adhering to the principle of least privilege.

References

Using Workload Identity

Managing Service Accounts

https://gsuite.google.com/learn-more/security/security-whitepaper/page-1.html

Shared responsibility “Security of the Cloud” - GCP is responsible for protecting the infrastructure that runs all of the services offered in the GCP Cloud. This infrastructure is composed of the hardware, software, networking, and facilities that run GCP Cloud services.

To restrict access to the MySQL instance to only the frontend application while other VMs are present in the subnets, creating an ingress firewall rule is the most appropriate approach. This rule will specifically allow traffic from subnet A (where the frontend application resides) to the MySQL instance in subnet B on port 3306, using network tags to target the specific MySQL VM.

Steps:

Create Network Tags: Apply a network tag (e.g., "data-tag") to the MySQL VM in subnet B.

Create Ingress Firewall Rule: Configure an ingress firewall rule with the following settings:

Source IP Range: Subnet A's IP range.

Target Tag: "data-tag".

Allowed Protocol/Ports: TCP:3306 (for MySQL).

This setup ensures that only instances in subnet A can communicate with the MySQL instance on port 3306.

To comply with the regulation to keep instance logging data within Europe, specifically in the Netherlands (region europe-west4), you need to configure Cloud Logging to ensure that all logs are stored in a specified region. Here are the steps to achieve this:

Create a Cloud Storage Bucket:

Go to the Google Cloud Console.

Navigate to Cloud Storage and create a new bucket.

Set the location type to "Region" and select "europe-west4" as the region.

Configure Log Sink:

Go to the Logging section in the Google Cloud Console.

Create a new log sink and configure it to export logs to the Cloud Storage bucket you just created.

Ensure the sink includes all logs you want to keep within europe-west4.

Verify Configuration:

Ensure that the logs are being exported to the Cloud Storage bucket by checking the contents of the bucket.

This setup ensures that all your logging data remains within the specified region, adhering to compliance requirements.

References

Creating and Managing Log Sinks

Cloud Storage Locations