Practice Free Professional-Cloud-Security-Engineer Google Cloud Certified - Professional Cloud Security Engineer Exam Questions Answers With Explanation

The requirements are runtime threat detection for containers that specifically detects activities like loading additional libraries or executing malicious scripts, with findings visible in Security Command Center (SCC).

Container Threat Detection (CTD) is the specific SCC service component designed to monitor container runtimes for suspicious events like reverse shells, suspicious library loading, and execution of malicious scripts. It is available only with the Security Command Center Premium tier.

Extracts:

"Container Threat Detection (CTD) is a Security Command Center Premium service that provides runtime threat detection for Google Kubernetes Engine (GKE) and Kubernetes clusters." (Source 4.1)

"CTD detects specific runtime events, such as: Execution of malicious scripts... Loading of suspicious libraries... CTD creates high-fidelity Security Command Center findings for these threats." (Source 4.2)

"Security Health Analytics (Option C) identifies misconfigurations and compliance violations, such as overly permissive IAM roles or open firewall ports, but it does not perform runtime threat detection." (Source 4.3)

While using log-based metrics (Option D) is possible, enabling CTD (Option B) is the specific, managed, and authoritative way to generate verified runtime threat findings directly within Security Command Center as required by the prompt.

Enable automatic key version rotation on a regular schedule:

Regularly rotating keys reduces the impact of a potentially compromised key by limiting the amount of data encrypted with a single key version.

Set up automatic key rotation in Cloud KMS to ensure keys are rotated without manual intervention.

Limit the number of messages encrypted with each key version:

Reducing the number of messages encrypted with each key version minimizes the potential data exposure in case of a key compromise.

Implement policies to ensure that new key versions are used periodically to limit the usage of each key version.

The problem requires automating user provisioning to a Cloud Identity security group using a service account, adhering to Google-recommended practices and the principle of least privilege.

Cloud Identity Groups and Google Workspace: Cloud Identity groups are managed as part of Google Workspace. To programmatically manage Google Workspace resources (like groups), you typically use the Admin SDK APIs.

Domain-Wide Delegation: Service accounts cannot directly authenticate to Google Workspace APIs using IAM roles. Instead, they require "domain-wide delegation" to impersonate a user with the necessary administrative privileges within Google Workspace. This allows a service account to access user data or perform administrative tasks across the domain. The correct scope for managing groups is https://www.googleapis.com/auth/admin.directory.group.Extract Reference: "To allow a service account to access user data on behalf of users in a Google Workspace domain, you must delegate domain-wide authority to your service account." (Google Cloud documentation: https://developers.google.com/identity/protocols/oauth2/service-account#delegating)

Extract Reference (Admin SDK Scopes): The https://www.googleapis.com/auth/admin.directory.group scope is explicitly listed for "View and manage all groups on the domain." (Google Workspace Admin SDK documentation: https://developers.google.com/admin-sdk/directory/v1/scopes)

Application Default Credentials (ADC) with Resource-Attached Service Account: Google-recommended practices strongly advise against using service account keys directly for authentication when running on Google Cloud infrastructure. Instead, it's recommended to use Application Default Credentials (ADC) with a service account attached to the resource (e.g., a Compute Engine VM, Cloud Run service, or Cloud Functions). This method manages credentials automatically and securely, reducing the risk associated with managing and rotating keys.Extract Reference: "For most Google Cloud services, Application Default Credentials (ADC) is the recommended way to authenticate." and "When running code in a Google Cloud environment, such as Compute Engine, Cloud Run, or Cloud Functions, use the built-in service account to authenticate automatically with ADC. This is the most secure approach, as you don't need to manually create or manage service account keys." (Google Cloud documentation: https://cloud.google.com/docs/authentication/production)

Options C and D are incorrect because granting an IAM role like "Groups Editor" in Google Cloud does not enable a service account to manage Google Workspace (Cloud Identity) group memberships; domain-wide delegation is required for that. Option A uses a service account key, which is less secure than ADC with a resource-attached service account according to Google's recommendations.

Therefore, option B is the most aligned with Google's recommended practices for securely automating group provisioning using a service account and domain-wide delegation.

This question requires implementing fine-grained data access control across multiple services based on the Principle of Least Privilege.

Project/Service Access (IAM): Granting project-level group permissions with specific Cloud IAM roles (e.g., BigQuery Data Viewer) is the primary way to control who has access to which project's resources.

Data Isolation (Service-Specific): To ensure only relevant data is accessed and to protect sensitive information within the datasets, you must use the most granular control mechanism available for each service:

BigQuery: Authorized Views allow access to specific query results (subsets of data) without granting access to the underlying table.

Cloud Storage: Uniform bucket-level access simplifies and tightens security by forcing all access to be controlled by IAM, preventing accidental object-level exposure.

Cloud SQL: Database Roles are the native, most granular way to control access within the database itself (e.g., read-only access to specific tables).

Extracts (Conceptual Basis):

"The principle of least privilege dictates that users should only have the permissions necessary to perform their jobs. Granular access is enforced using a combination of IAM roles and service-native access controls." (Source 5.1)

"For BigQuery, using authorized views is the standard way to limit data exposure to users who should only see a subset of data." (Source 5.2)

To minimize the attack surface of the container for an internet-facing application running on Google Kubernetes Engine (GKE), the best practice is to build small containers using small base images. This approach helps in the following ways:

Reduce Vulnerabilities: Smaller base images contain fewer packages and dependencies, which minimizes the potential vulnerabilities that an attacker could exploit.

Improved Security: Using minimal base images such as distroless or Alpine Linux ensures that only the necessary components are included, reducing the attack surface significantly.

Easier Maintenance: Small containers are easier to maintain and update, ensuring that security patches can be applied quickly without dealing with unnecessary components.

Steps to Implement:

Choose a Minimal Base Image:

Use base images like gcr.io/distroless/base or alpine.

FROM gcr.io/distroless/base COPY myapp /myapp CMD ["/myapp"]

Optimize Container Image:

Remove unnecessary tools and libraries.

Use multi-stage builds to keep the final image small.

Regularly Update Base Images:

Keep the base images up-to-date with the latest security patches.

Distroless Images

Best Practices for Building Containers

To ensure that payment information is encrypted between the customer’s browser and Google Cloud Platform during checkout, the company should configure an SSL certificate on an L7 (Layer 7) Load Balancer. Here’s why this is the best solution:

SSL/TLS Termination: An L7 Load Balancer can handle SSL/TLS termination, which means it can decrypt HTTPS traffic, offloading the work from the backend servers. This is essential for handling encrypted connections securely.

HTTPS Configuration: By configuring an SSL certificate, the load balancer ensures that all traffic between the customer’s browser and the application is encrypted using HTTPS.

Security Best Practices: Using an L7 Load Balancer with an SSL certificate aligns with best practices for securing web applications, particularly for e-commerce sites handling sensitive payment information.

Managed Certificates: Google Cloud offers managed SSL certificates, which simplifies the process of obtaining, deploying, and renewing SSL certificates.

Implementation Steps:

Obtain an SSL certificate.

Configure the L7 Load Balancer in the GCP Console.

Associate the SSL certificate with the load balancer.

Ensure that the backend services are configured to handle HTTPS traffic.

Google Cloud Load Balancing Documentation

Setting up HTTPS Load Balancing

An unmanaged Google account is a personal account created by an individual using a corporate email address (e.g., john@company.com), which the organization cannot control. The root cause is that the organization has not claimed the identity for that email address.

Extracts:

"To prevent unmanaged Google account creation, you have two options: Create a user for every person who has an email address in your domain... If there are unmanaged accounts already created, you can use the Transfer Tool for unmanaged users to invite them to become managed users." (Source 5.1)

"If an admin creates a managed Google Account using the same account name as an existing unmanaged user account, this results in a conflicting account." (Source 5.3)

By provisioning an account for every employee (via Google Workspace or Cloud Identity), you effectively claim that domain identity, making it a managed account under IT control and preventing the creation of a new, unmanaged consumer account with the same email address.

Option B describes the foundational, preventative step in identity management: provisioning managed identities for all users in the domain.

o ensure that users can only access the data in a BigQuery table during working hours, you can assign the BigQuery Data Viewer role with an IAM condition that specifies the allowed access times. This method leverages IAM Conditions, which allow you to define and enforce time-based access policies. Here's how to do it:

Identify the BigQuery Table: Determine which BigQuery table(s) require restricted access.

Create an IAM Policy with Conditions: Define an IAM policy that includes a condition for time-based access. You can do this using the Google Cloud Console, gcloud command-line tool, or directly editing the IAM policy JSON.

Specify Working Hours: In the IAM condition, specify the time frame during which access is allowed. For example, you can set access to be allowed from 9 AM to 5 PM on weekdays.

Assign the Role with Conditions: Apply the policy to the users or groups who need access. Ensure that the condition is correctly attached to the BigQuery Data Viewer role.

Example using gcloud:

gcloud projects add-iam-policy-binding [PROJECT_ID] \

--member=user:[USER_EMAIL] \

--role=roles/bigquery.dataViewer \

--condition=expression="(request.time.getFullYear() == 2024) && (request.time.getDayOfWeek() in [1, 2, 3, 4, 5]) && (request.time.getHours() >= 9) && (request.time.getHours() < 17)",title="Working hours condition",description="Access limited to working hours"

References

Google Cloud IAM Conditions

Google Cloud BigQuery IAM Roles

To monitor and get notified in case the script causing the Compute Engine instance to crash is executed again, you should create an Alerting Policy in Stackdriver (now known as Google Cloud Monitoring). The Process Health condition can be set to monitor the number of executions of the script and ensure it remains below the desired threshold. By enabling notifications, you will be alerted if this threshold is exceeded.

Step-by-Step:

Log Script Executions: Ensure that the script execution is logged.

Create a User-Defined Metric: Go to Google Cloud Console > Logging > Logs-based Metrics, and create a new user-defined metric that counts the number of times the script executes.

Set Up Alerting Policy:

Navigate to Google Cloud Console > Monitoring > Alerting.

Click on “Create Policy”.

Add a condition and select “Logs-based Metric”.

Configure the condition to trigger when the number of script executions exceeds the threshold.

Configure Notifications: Add notification channels (email, SMS, etc.) to the alerting policy.

Save and Test: Save the policy and test to ensure notifications are received when the script is executed beyond the threshold.

Google Cloud Logging User-defined Metrics

Google Cloud Monitoring Alerting Policies

To allow a large number of users to access the GCP Console while keeping the existing Active Directory or LDAP server for identity management, use Google Cloud Directory Sync (GCDS).

Install GCDS:

Download and install Google Cloud Directory Sync from here.

Configure GCDS:

Set up the synchronization by specifying the LDAP server details and the Google domain.

Map the LDAP attributes to Google attributes to ensure user data is synchronized correctly.

Run Synchronization:

Perform an initial synchronization to populate the Google domain with existing users from the LDAP server.

Schedule regular synchronizations to keep the data up-to-date.

Benefits:

Automated Sync: Ensures that user data is consistently updated without manual intervention.

Secure Access: Users can log in to the GCP Console using their existing credentials, enhancing security and user experience.

Google Cloud Directory Sync Documentation

GCDS Administration Guide

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.

Challenge:

Prevent common misconfigurations that expose services (e.g., MYSQL) to the public internet.

Hierarchical Firewall Policies:

These policies can be applied at the organization level to enforce consistent network security rules across all projects.

Solution:

Create a hierarchical firewall policy that allows connections only from internal IP ranges.

This policy ensures that services like MySQL are not exposed to 0.0.0.0/0 (the entire internet).

Steps:

Step 1: Define the hierarchical firewall policy at the organization level.

Step 2: Set the rule to allow traffic only from internal IP ranges.

Step 3: Apply the policy to all projects under the organization.

Benefits:

Centralized management of network security.

Prevents accidental exposure of services to the public internet, enhancing security.

Google Cloud customers with additional requirements for encryption of data over WAN can choose to implement further protections for data as it moves from a user to an application, or virtual machine to virtual machine. These protections include IPSec tunnels, Gmail S/MIME, managed SSL certificates, and Istio. https://cloud.google.com/docs/security/encryption-in-transit

Objective: Quickly recover a deleted service account used for data transfers.

Solution: Use the undelete command available in the gcloud command-line tool to recover the service account.

Steps:

Step 1: Open the Cloud Shell in the Google Cloud Console.

Step 2: Run the following command to list the deleted service accounts:

gcloud iam service-accounts list --filter="deleted: true"

Step 3: Identify the name and ID of the deleted service account.

Step 4: Use the undelete command to recover the service account:

gcloud iam service-accounts undelete [SERVICE_ACCOUNT_ID]

Step 5: Verify that the service account has been restored and reassign any necessary permissions.

By using the undelete command, you can quickly restore the service account and resume application functionality without compromising security.

Use the TCP/UDP Network Load Balancer:

TCP/UDP Network Load Balancer maintains the client IP address by default when forwarding traffic to backends.

Configure a TCP/UDP Network Load Balancer with appropriate backend services and health checks.

Ensure that the load balancer is using the standard network tier to comply with the requirements.

Google's Super Administrator security best practices emphasize that these accounts should be handled differently from standard user accounts, especially when using third-party SSO (like Entra ID).

According to Google Cloud Best Practices for Admin Accounts:

"You should maintain at least two super administrator accounts that are not part of your standard SSO (Single Sign-On) flow. These should be 'Cloud-only' accounts. This ensures that if your external IdP (Entra ID) is down or misconfigured, you can still sign in to Google Cloud. Furthermore, you must enforce Google 2-step verification (2SV)—ideally using hardware security keys—directly on these accounts to provide the strongest level of protection independent of the IdP."

Key Best Practices:

Dedicated Accounts: Do not use the same account for daily work (Email/Docs) and Admin tasks.

Avoid SSO for Admins: If Entra ID has an issue, you could be locked out of your Google Org. Cloud-only accounts solve this.

Strong 2SV: Google's native 2SV is required to protect these highly privileged identities from phishing and credential theft.

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

The requirement to log access by Google personnel (e.g., Google administrators or support) is the specific function of Access Transparency.

Access Transparency logs provide records of actions taken by Google staff when they interact with your content, which is a requirement for many regulated industries. It is typically enabled at the Organization level to ensure consistent coverage, though it can be configured lower.

Extracts:

"Access Transparency logs provide records of actions taken by Google employees when accessing your data or configuration... Access Transparency allows you to monitor compliance with vendor access rules, including those for security and privacy." (Source 9.1)

"Access Transparency is enabled for all supported Google Cloud services across your organization when enabled at the organization level." (Source 9.2)

Option A and C (Data Access logs) record customer/user access to data, but do not record actions taken by Google personnel.

Activate Security Command Center (SCC) Premium: Security Command Center (SCC) Premium provides advanced security analytics and best practice recommendations for your Google Cloud environment. It includes functionalities such as asset discovery, vulnerability scanning, and security findings.

Create a Custom Rule to Mute Irrelevant Security Findings:

Navigate to the Security Command Center (SCC) in the Google Cloud Console.

Go to the "Settings" tab and find the "Mute findings" section.

Create a new mute rule by specifying the conditions that match the irrelevant controls you want to disregard. These conditions can be based on attributes such as resource type, finding type, and other metadata.

Apply this mute rule, which will ensure that the specified findings are not evaluated in your security posture assessments.

Ensure Continuous Compliance Monitoring:

The mute rules will automatically filter out the irrelevant findings, ensuring that only relevant controls from the CIS Google Cloud Computing Foundations Benchmark v1.3.0 are evaluated.

Regularly review and update the mute rules to adapt to any changes in your compliance requirements or security posture.

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.

Create a new Service Account that should be able to list the Compute Engine instances in the project. You want to follow Google-recommended practices.

https://cloud.google.com/security/compliance/iso-27017

Objective: Prevent users from creating projects while allowing only the DevOps team to create projects.

Solution: Modify IAM roles and permissions.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the IAM & Admin page.

Step 3: At the organizational level, find and remove all users from the Project Creator role.

Step 4: Create or identify a group for the DevOps team.

Step 5: Assign the Project Creator role to the DevOps team group at the organizational level.

By removing all users from the Project Creator role and granting it only to the DevOps team, you ensure that only the designated team can create projects.

To manage user accounts and ensure they comply with corporate policies, using Google Cloud Directory Sync (GCDS) allows synchronization between your local identity system and Cloud Identity. The Transfer Tool for Unmanaged Users (TTUU) helps identify and manage conflicting accounts by allowing users to transfer their personal accounts to managed accounts.

Steps:

Synchronize Identities: Use GCDS to sync users from your local identity management system to Cloud Identity, ensuring that all corporate user accounts are managed.

Identify Conflicting Accounts: Use TTUU to find users who have personal Google accounts using corporate email addresses.

Manage Conflicting Accounts: Request users to transfer their personal accounts to managed accounts using TTUU, ensuring all accounts are under corporate control.

The problem requires gaining "detailed visibility into changes to IAM policies, user activity, service account behavior, and access to sensitive projects" due to security inconsistencies.

Cloud Audit Logs: Cloud Audit Logs records administrative activities, data access, and system events across Google Cloud. These logs are the primary source of truth for tracking "who did what, where, and when" in your Google Cloud environment.

Extract Reference: "Cloud Audit Logs maintains the following audit logs for each project, folder, and organization: Admin Activity audit logs, Data Access audit logs, System Event audit logs, Policy Denied audit logs."

Extract Reference: "Admin Activity audit logs contain log entries for API calls or other actions that modify the configuration or metadata of resources. Data Access audit logs record API calls that read the configuration or metadata of resources, as well as user-provided data." (Google Cloud Documentation: "Cloud Audit Logs overview" - https://cloud.google.com/logging/docs/audit)

These logs directly capture:Changes to IAM policies: Recorded in Admin Activity logs.

User activity: Recorded in Admin Activity and Data Access logs.

Service account behavior: Actions performed by service accounts are logged in the same way as user actions.

Access to sensitive projects: Data Access logs, especially for sensitive data services, record access events.

Log Export Sinks: To gain "detailed visibility" and enable "correlation with other event sources," these audit logs should be exported to a centralized Security Information and Event Management (SIEM) solution. Log sinks allow you to route logs from Cloud Logging to various destinations, including BigQuery, Cloud Storage, or Pub/Sub (which can then feed into a SIEM).

Extract Reference: "You can use sinks to route some or all of your logs to supported destinations." and "Many security information and event management (SIEM) systems can ingest logs through Cloud Pub/Sub." (Google Cloud Documentation: "Routing and storage overview | Cloud Logging" - https://cloud.google.com/logging/docs/routing-overview)

Let's evaluate the other options:

A. OS Config Management agent: This service manages operating system configurations, patching, and inventory on VMs. It is not designed to monitor or log IAM policy changes, user activity, or service account behavior within Google Cloud's IAM system.

B. Metrics Explorer in Cloud Monitoring: While Cloud Monitoring can provide some metrics related to service account authentication, it focuses on time-series data and operational health metrics. It does not provide the detailed, event-level audit records necessary for forensic analysis of IAM policy changes, specific user actions, or granular access events to sensitive data that Cloud Audit Logs offer.

D. Cloud Functions triggered by IAM policy changes + Policy Simulator: This describes a reactive automation pattern for some IAM changes. While useful for immediate alerting on risky modifications, it's a custom solution for a subset of the requirements. It doesn't inherently provide "detailed visibility" into all user activity or comprehensive service account behavior across all projects, nor does it replace the robust logging and correlation capabilities of a SIEM solution ingesting raw audit logs. Cloud Audit Logs are the fundamental data source this approach would rely on.

Therefore, leveraging Cloud Audit Logs and exporting them to a SIEM is the most comprehensive and recommended approach for gaining detailed visibility into IAM-related changes and activities across your Google Cloud organization.

The core requirement is to ensure only scanned and verified containers can run in the environment, which is a deployment-time enforcement action.

Binary Authorization is the service designed for this purpose. It is a deployment-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or other supported container platforms. The core mechanism it uses to verify that an image has completed required steps (like a vulnerability scan) is an attestation.

Extracts:

"GCP Binary Authorization is a security feature designed to prevent the deployment of unverified, unauthorized, or potentially malicious container images to Kubernetes clusters." (Source 1.1)

"Binary Authorization ensures that only images that are signed by trusted entities (such as a trusted attestation authority) are allowed to be deployed." (Source 1.1)

"Binary Authorization aims to reduce the risk of deploying defective, vulnerable, or unauthorized software in this type of environment. Using this service, you can prevent images from being deployed unless it satisfies a policy you define." (Source 1.2)

"The most common Binary Authorization use cases involve attestations. An attestation certifies that a specific image has completed a previous stage... Attestations signify that the associated image was built by successfully executing a specific, required process. For example, the attestation might indicate that the image has passed all required end-to-end functional testing in a staging environment." (Source 1.2, 1.4)

"After a container image is built, an attestation can be created to affirm that a required activity was performed on the image such as a regression test, vulnerability scan, or other test." (Source 1.5)

Option A correctly identifies the two necessary components for this deployment-time enforcement: Binary Authorization for policy enforcement and attestations to certify that the vulnerability scan (or other required check) has been completed and verified.

Objective: Ensure that a Cloud Storage bucket in Project A can only be readable from Project B and prevent data access or copying to Cloud Storage buckets outside the network, even with correct credentials.

Solution: Use VPC Service Controls to create a security perimeter.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the VPC Service Controls page.

Step 3: Create a new service perimeter.

Step 4: Add Project A and Project B to the service perimeter.

Step 5: Include Cloud Storage service in the perimeter configuration.

Step 6: Define access levels to ensure that only resources within the perimeter can access the Cloud Storage bucket.

By setting up a VPC Service Controls perimeter, you can enforce security boundaries that restrict data access and movement to within defined projects, providing an extra layer of protection beyond IAM permissions.

External HTTP(S) Load Balancer: Deploy an external HTTP(S) load balancer to manage traffic to your VMs. This load balancer will handle incoming traffic from the internet while the VMs themselves do not have public IP addresses.

Host (VPC) Project Deployment: Deploy the load balancer in the host (VPC) project. This allows for centralized management of network resources and maintains the integrity of your shared VPC configuration.

Backend Configuration: Configure the MIG as the backend for the load balancer. This setup ensures that the VMs can still serve external users while reducing their direct exposure to the internet. This solution provides the required access to external users through the load balancer, enhancing security by not exposing individual VM IP addresses. References:

Google Cloud - External HTTP(S) Load Balancer Overview

Google Cloud - Shared VPC Overview

To ensure servers do not have any direct communication with the public internet, they must be configured without a public IP address.

VPC and Private Subnet: A Virtual Private Cloud (VPC) network provides the isolated, internal network structure. A subnet is the logical partition within the VPC.

Private IP Address: Assigning only a private IP address to the database servers ensures they can only communicate internally within the VPC (or connected on-premises networks) and cannot directly connect to or be connected from the public internet.

Extracts:

"Resources in a VPC network can be assigned two types of IP addresses: internal (private) and external (public). If a VM is not assigned an external IP address, it can only communicate internally with other resources in the VPC network..." (Source 6.1)

Option A and C involve assigning a public IP address, which violates the "no direct communication with the public internet" rule. Option D uses NAT to provide outbound internet connectivity, which also violates the requirement.

The core security and privacy requirement is to prevent personal data from being used in the training process, which necessitates de-identification. Cloud Data Loss Prevention (DLP), also referred to as Sensitive Data Protection (SDP), is the specific Google Cloud tool for this purpose. The secondary requirement, restricting access, is handled by IAM.

Extracts:

"Sensitive Data Protection (SDP)... De-identification enables you to transform your data to reduce data risk while retaining data utility." (Source 1.4)

"De-identification techniques like encryption, obfuscate raw sensitive identifiers in your data. These techniques let you preserve the utility of your data for joining or analytics, while reducing the risk of handling the data." (Source 1.1)

"DLP provides tools to classify and de-identify sensitive elements or unwanted content within your data... Find and remove sensitive elements from your data before model training." (Source 1.4)

IAM policies are the standard mechanism to satisfy the requirement to "restrict access to the dataset to an authorized subset of people only." Option B combines the precise technical solution for privacy (DLP De-identification) with the necessary access control (IAM).

App Engine ingress firewall rules are available, but egress rules are not currently available. Per requirements 1.2.1 and 1.3.4, you must ensure that all outbound traffic is authorized. SAQ A-EP and SAQ D–type merchants must provide compensating controls or use a different Google Cloud product. Compute Engine and GKE are the preferred alternatives. https://cloud.google.com/solutions/pci-dss-compliance-in-gcp

To enforce access control policies for applications and resources in Google Cloud, the recommended service is Identity-Aware Proxy (IAP).

Identity-Aware Proxy (IAP):

IAP allows you to control access to your applications and resources based on the identity of the user and the context of the request. It integrates with IAM to provide fine-grained access control, ensuring that only authorized users can access specific resources.

IAP helps enforce security policies at the application layer, providing an additional layer of protection beyond traditional network-based security measures.

References

Identity-Aware Proxy documentation

https://cloud.google.com/sql/docs/mysql/cmek

"You might have situations where you want to permanently destroy data encrypted with CMEK. To do this, you destroy the customer-managed encryption key version. You can't destroy the keyring or key, but you can destroy key versions of the key."

Admin activity logs are always created to log entries for API calls or other actions that modify the configuration or metadata of resources. For example, these logs record when users create VM instances or change Identity and Access Management permissions.

Using Identity-Aware Proxy (IAP) for managing SSH access to private VMs ensures secure access control and avoids the need for public IPs. IAP allows you to enforce identity-based access control policies.

Enable IAP: Ensure that IAP is enabled for your project. This can be done via the Google Cloud Console under "Security" -> "Identity-Aware Proxy".

Set Up Firewall Rule: Create a firewall rule to allow SSH traffic from the IAP IP ranges.

Navigate to "VPC network" -> "Firewall".

Create a new rule allowing ingress traffic on port 22 (SSH) from the IAP IP ranges.

Assign IAP-Secured Tunnel User Role: Grant the roles/iap.tunnelResourceAccessor role to the administrators who need SSH access.

Go to "IAM & Admin" -> "IAM".

Assign the IAP-Secured Tunnel User role to the relevant users or groups.

SSH Using IAP: Administrators can now use IAP to SSH into the instances. This can be done using the gcloud command:

gcloud compute ssh [INSTANCE_NAME] --tunnel-through-iap

Objective: Synchronize security groups with email addresses from an LDAP directory to Cloud IAM.

Solution: Use Google Cloud Directory Sync (GCDS) to perform one-way synchronization based on LDAP search rules.

Steps:

Step 1: Download and install Google Cloud Directory Sync (GCDS) on a secure server.

Step 2: Configure GCDS with the LDAP server details and authentication.

Step 3: Define LDAP search rules to filter security groups based on the “user email address” attribute.

Step 4: Map LDAP security groups to Google Cloud IAM roles.

Step 5: Set up a synchronization schedule to keep the groups in sync.

Step 6: Perform a test sync to ensure that the configuration is correct.

Step 7: Activate the synchronization to keep the LDAP directory and Cloud IAM in sync.

Using GCDS for one-way synchronization ensures that the security groups in Cloud IAM are consistently updated based on the LDAP directory, maintaining alignment with the organization’s security policies.

To grant an IAM user access to HTTPS resources protected by Identity-Aware Proxy (IAP), you should assign the IAP-Secured Web App User role.

IAP-Secured Web App User (C):

This role grants the necessary permissions for a user to access web applications secured by IAP. It includes permissions to access the IAP-secured resources, ensuring that users can authenticate and gain the appropriate access based on the policies defined in IAP.

Assigning this role ensures that users have the right level of access to protected web resources, aligned with the security controls enforced by IAP.

References

Identity-Aware Proxy Documentation

IAP Roles and Permissions

Objective: You want to limit the images that can be used as the source for boot disks to a set of images stored in a dedicated project.

Solution: Use the Organization Policy Service.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Organization Policies page.

Step 3: Create a new policy by clicking on "Create Policy".

Step 4: Select the constraint compute.trustedimageProjects.

Step 5: Set the policy to ALLOW and specify the project ID where the trusted images are stored in the whitelist.

Step 6: Save and apply the policy.

By creating a compute.trustedimageProjects constraint at the organization level and specifying the trusted project in the allow list, you ensure that only images from this project can be used for boot disks across the organization.

Use the org policy constraint "Google Cloud Platform - Resource Location Restriction" on your Google Cloud organization node: This organizational policy constraint allows you to restrict the locations where your resources can be created. By setting this constraint to allow only Europe regions, you can ensure compliance with GDPR and other regional regulations.

Implementation: To implement this, you need to configure the organization policy with the constraint constraints/gcp.resourceLocations. You can specify allowed regions such as europe-west1 and europe-west4 to ensure resources are only created in these locations.

References

Resource Location Restriction documentation

GDPR compliance on Google Cloud

The key requirements are maintaining a specific set of controls, including data residency and personnel data access controls, specifically to meet a highly regulated industry's compliance program.

Assured Workloads is the specific Google Cloud service designed to help customers meet these stringent regulatory and compliance requirements (e.g., FINRA, FedRAMP, HIPAA, etc.) by enforcing a specific control bundle.

Extracts:

"Assured Workloads helps organizations run their sensitive workloads securely and in a compliant manner... by providing continuous compliance monitoring for specific compliance programs." (Source 4.1)

"When you create an Assured Workloads folder, the platform automatically enforces compliance controls... including: Data residency and location controls... Personnel access controls... Organizational policies..." (Source 4.2)

This service creates a dedicated, compliant environment in a folder, ensuring the necessary configurations and personnel controls are applied automatically and continuously maintained, which is a more complete solution than the posture management in option B (which focuses only on configuration monitoring) or the singular organizational policy in option C.

To grant read access to a third-party disk image stored in an external Google Cloud organization so it can be deployed into a VPC Service Controls perimeter, you need to update the service perimeter to allow egress traffic from your projects to the external project.

Update the Service Perimeter:

Go to the Google Cloud Console, navigate to Security > VPC Service Controls.

Select the appropriate service perimeter that includes your image repository project.

Configure Egress Policy:

Within the perimeter settings, configure the egressTo field to allow traffic to the external project.

Set the identityType to ANY_IDENTITY to permit any principal to access the external project for this specific egress rule.

Specify External Project and Service:

In the egressFrom field, include the external Google Cloud project number as an allowed resource.

Set the serviceName to compute.googleapis.com to specifically allow access to the Compute Engine service in the external project.

This configuration permits your internal projects to read the disk image from the external project while maintaining the security boundaries established by the service perimeter.

VPC Service Controls Documentation

Configuring Service Perimeters

To centrally govern and restrict which AI models (from the Model Garden) can be used within an organization, Google Cloud provides a specific Organization Policy Constraint.9

According to Google Cloud Documentation (Vertex AI Organization Policy Constraints):

"The constraints/vertexai.allowedModels constraint allows you to define a list of allowed models that can be deployed or used within your organization. This includes Google first-party models, open-source models, and third-party models available in the Model Garden.10 By using this policy, you can prevent users from using unvetted or non-compliant models even if they have IAM permissions to use Vertex AI."

How it works:

You define an "Allowlist" of model IDs.

When a user attempts to deploy a model or call an API for a model not on the list, the request is blocked.

This is the most scalable and compliant way to manage AI governance.

Why other options are incorrect:

A is incorrect: Model Garden is a catalog; you cannot apply granular IAM permissions to individual entries within the public catalog itself in the same way you can restrict API usage via Org Policy.

B is incorrect: Auditing is reactive. The requirement is to ensure users can only access approved models (prevention).

Cloud Asset Inventory: Using Cloud Asset Inventory allows you to quickly identify all the external assets and resources in your Google Cloud environment. This includes information about your projects, instances, storage buckets, and more. This step is crucial for understanding the scope of your audit. Network Security Scanner: Once you have identified the external assets, you can run a network security scanner to assess the security of these assets. Network security scanners can help identify vulnerabilities and potential security risks quickly.

Objective: Ensure that a Cloud Storage bucket in Project A can only be readable from Project B and prevent data access or copying to Cloud Storage buckets outside the network, even with correct credentials.

Solution: Use VPC Service Controls to create a security perimeter.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the VPC Service Controls page.

Step 3: Create a new service perimeter.

Step 4: Add Project A and Project B to the service perimeter.

Step 5: Include Cloud Storage service in the perimeter configuration.

Step 6: Define access levels to ensure that only resources within the perimeter can access the Cloud Storage bucket.

By setting up a VPC Service Controls perimeter, you can enforce security boundaries that restrict data access and movement to within defined projects, providing an extra layer of protection beyond IAM permissions.

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)

The problem has two key requirements:

All applications must send data to a centralized security service.

Developers need high autonomy over firewall rules within their projects.

Prevent accidental blockage of access to the central security service.

This scenario requires a mechanism to enforce critical network policies at a higher level of the resource hierarchy while still allowing project-level flexibility.

Hierarchical Firewall Policies: Google Cloud's Hierarchical Firewall Policies (HFP) are designed precisely for this purpose. They allow administrators to define firewall rules at the organization or folder level, and these rules are inherited by all projects and VPC networks within that hierarchy. Crucially, HFP rules can be prioritized. Rules with higher priority (lower numerical value) are evaluated first. This means you can create high-priority "allow" rules for critical services that cannot be overridden or blocked by project-level firewall rules.Extract Reference: "Hierarchical firewall policies allow you to define and enforce consistent network security policies across your organization. Policies can be applied at the organization or folder level, and they are inherited by all projects and VPC networks within that hierarchy." and "Rules in a hierarchical firewall policy can take precedence over VPC network firewall rules based on priority. A rule with a lower priority value takes precedence over a rule with a higher priority value." (Google Cloud documentation: https://cloud.google.com/vpc/docs/firewall-policies-overview)

Preventing Accidental Blockage while Allowing Autonomy: By setting a high-priority "allow" rule for the central security service in a hierarchical firewall policy, you guarantee that this traffic will always be permitted, regardless of what project-level firewall rules developers might configure. This ensures the critical connectivity while still allowing developers to manage other, less critical firewall rules within their projects with high autonomy.

Let's evaluate the other options:

A. Deploy a central Secure Web Proxy and connect it to all VPC networks. Create a Secure Web Proxy policy to allow traffic to the central security service. A Secure Web Proxy is for HTTP/S outbound traffic to external web services. The central security service might not be an external web service, and this solution is focused on application-layer proxies, not general network connectivity like sending data to an internal service. Also, it doesn't directly address the challenge of developers blocking access with project-level firewall rules.

C. Create a central project to manage Shared VPC networks which will be accessible to all other projects. Administer all firewall rules centrally within this project. While Shared VPC centralizes network management, it means all firewall rules are administered centrally. This directly contradicts the requirement for developers to have "high autonomy to configure firewall rules within their projects." Shared VPC would centralize too much control for this specific scenario.

D. Use Terraform to automate the creation of the required firewall rule in all projects. Restrict rule change permissions solely to the Terraform service account. This approach automates the creation but doesn't prevent developers from creating conflicting or overriding rules in their projects (unless Terraform is used to manage all rules, again removing autonomy). It also relies on restricting IAM permissions for all firewall rules, which is against the "high autonomy" requirement for developers. Hierarchical firewall policies offer a more robust and native solution for overriding and enforcing specific rules.

Therefore, implementing a hierarchical firewall policy is the most effective solution, as it allows for the enforcement of critical security service connectivity at a higher level, while still granting developers the desired autonomy over their project-specific firewall rules.

If a user loses their second factor for 2-Step Verification (2SV), you can help them regain access with minimal risk by generating a backup code.

Generate a Backup Code (A):

In the Google Admin console, navigate to the user's account settings.

Generate a backup code for the user. This code allows them to sign in despite not having access to their usual second factor.

Instruct the user to log in using the backup code and then update their second factor in their account settings.

This method ensures that only the affected user’s access is temporarily adjusted, minimizing risk while maintaining overall security policies.

References

Google Admin console 2-Step Verification documentation

This approach allows you to leverage your existing on-premises PKI infrastructure while minimizing its impact and manual processes. By creating a subordinate CA in Google’s Certificate Authority Service, you can automate the process of issuing certificates for your HTTP load balancer frontends. This solution scales well as the number of load balancers increases.

To ensure that a Compute Engine instance does not have access to the internet or to any Google APIs or services, you need to disable the following settings:

Public IP: Disabling the public IP address ensures that the instance does not have a direct connection to the internet. Without a public IP address, the instance cannot be accessed from or communicate with the internet directly.

Private Google Access: Disabling Private Google Access ensures that the instance does not have access to Google APIs and services through the internal Google network. Private Google Access allows instances without a public IP to reach Google APIs and services using private IP addresses, but disabling it will block this path.

Disabling these settings will effectively isolate the instance from both the public internet and Google's internal API services.

References

Google Cloud VPC Documentation - Overview

Configuring Private Google Access

Compute Engine Network Overview

Google Cloud Armor provides protection against DDoS attacks and allows you to define security policies to control access to your application. It enables you to block traffic from specific IP addresses or ranges, making it suitable for denying traffic from a list of malicious IP addresses while protecting your application from being directly exposed to the internet.

Steps:

Set Up Cloud Armor: Enable Cloud Armor in your Google Cloud Console.

Create Security Policies: Define security policies that specify the rules for allowing or denying traffic based on IP addresses.

Attach Policies to Backend Services: Apply these security policies to the backend services of your web application.

https://cloud.google.com/bigquery/docs/scan-with-dlp

Cloud Data Loss Prevention API allows to detect and redact or remove sensitive data before the comments or reviews are published. Cloud DLP will read information from BigQuery, Cloud Storage or Datastore and scan it for sensitive data.

There is mention about simulating in Web Security Scanner. "Web Security Scanner cross-site scripting (XSS) injection testing *simulates* an injection attack by inserting a benign test string into user-editable fields and then performing various user actions." https://cloud.google.com/security-command-center/docs/how-to-remediate-web-security-scanner-findings#xss

Titan Security Keys are a physical form of two-step verification (2SV) that provide the highest level of account security by using cryptographic signatures to verify the user and the URL of the login page.

Cryptographic Security: Titan Security Keys use a hardware-based cryptographic method to authenticate users, which is resistant to phishing attacks. This ensures that the authentication process is secure and not susceptible to being intercepted or spoofed.

URL Verification: Titan Security Keys verify the URL of the login page during the authentication process, providing an additional layer of security against phishing attempts that may try to redirect users to malicious websites.

Ease of Use: These keys are easy to use and integrate with Google's 2SV process, providing a seamless and highly secure authentication method for users.

References

Titan Security Keys

To ensure least-privilege access and provide necessary permissions to the DevOps team only during a deployment issue, follow these steps:

Create a Service Account:

In your Google Cloud project, create a new service account specifically for the DevOps team.

Assign Limited Permissions:

Grant the service account permissions with only the necessary list/view roles. For instance, you can create a custom IAM role with compute.instances.list and compute.instances.get permissions.

Grant Service Account User Role:

Assign the Service Account User role to the DevOps team members for the created service account. This allows them to act as the service account and use its permissions.

Access Control During Incidents:

During a deployment issue, the DevOps team can temporarily use the service account to access the resources. This ensures they have the least-privilege access required to investigate and resolve the issue.

Automation and Monitoring:

Implement automation to enable and disable the service account access as needed and monitor the usage to ensure compliance with the least-privilege principle.

Benefits:

Security: Limits access to only what is necessary, reducing the risk of unauthorized changes.

Flexibility: Provides necessary access during incidents without granting permanent elevated permissions.

References

Creating and Managing Service Accounts

Service Account User Role

When implementing new security perimeters or access levels, Google Cloud recommends using Dry Run Mode in VPC Service Controls.12 This allows you to see what would have been blocked without actually disrupting traffic.

According to Google Cloud Documentation (Dry Run Mode for Service Perimeters):

"Dry run mode allows you to test the impact of a service perimeter before enforcing it. You can associate an Access Level (which contains Context-Aware attributes like device status and location) with the dry run configuration. Any request that violates the perimeter or the access level will be logged in Cloud Audit Logs as a 'dry run violation,' but the request will still be allowed to proceed."13

Evaluation Process:

Define the Access Level in Access Context Manager (Managed Device + Location).

Configure the VPC-SC Perimeter to include the project.

Apply the Access Level to the Dry Run section of the perimeter.

Monitor the VPC Service Controls Violation Dashboard or Audit Logs for dry run errors to identify legitimate users who would be blocked under the new policy.

Physical Token for MFA: Implement multi-factor authentication (MFA) using physical tokens (such as security keys) for super admin accounts. This adds an extra layer of security to the highest privilege accounts.

Non-Privileged Identities: Provide super admins with separate non-privileged accounts for daily activities. This practice minimizes the risk associated with using highly privileged accounts for routine tasks.

Account Management: Ensure that super admin accounts are only used for tasks requiring elevated privileges, reducing exposure to potential security threats. These measures enhance the security of super admin accounts, protecting your Google Cloud organization from unauthorized access. References:

Google Cloud - Best Practices for Securing Cloud Identity

Google Cloud - Using Security Keys

Understanding Unmanaged Users:

Unmanaged users are those who have created Google Cloud accounts using their company email addresses outside of the organization's management (e.g., through GCDS).

Challenge:

The goal is to bring these unmanaged accounts under your company's control without disrupting their existing accounts and access.

Using the Transfer Tool:

Google provides a transfer tool specifically designed to migrate unmanaged users to a managed state.

This tool allows administrators to invite unmanaged users to join the organization's Google Cloud Identity or Google Workspace account.

Steps to Use the Transfer Tool:

Step 1: Access the transfer tool from the Google Admin console.

Step 2: Identify the unmanaged users using their email addresses.

Step 3: Send invitations to these users to transfer their accounts.

Step 4: Users accept the invitations, allowing their accounts to be managed under the organization's domain.

Benefits:

This method ensures a smooth transition for users without losing access to their existing data and services.

It aligns with best practices for managing user accounts in a corporate environment.

To organize GCP projects based on different business units and manage IAM permissions, you should create an organization node and assign folders for each business unit. This approach allows you to logically separate projects under folders and apply IAM policies at the folder level.

Step-by-Step:

Create Organization Node: Ensure that your GCP account is linked to an organization.

Create Folders for Business Units:

Navigate to the GCP Console > IAM & Admin > Resource Manager.

Create a folder for each business unit under the organization node.

Move Projects to Folders:

Move existing projects into the respective folders according to the business unit.

Set IAM Policies:

Assign IAM roles and permissions at the folder level to manage access for each business unit independently.

Monitor and Manage: Use Cloud Audit Logs and other GCP tools to monitor the activities and ensure compliance with the organization’s policies.

Creating and Managing Folders

Managing IAM Policies

Google Cloud Logging supports Field-level access control, which allows you to hide specific sensitive fields within a log entry from certain users while still allowing them to see the rest of the log entry.5 This is achieved using Log Views and IAM.

According to Google Cloud Documentation (Configuring field-level access):

"Field-level access control allows you to restrict access to specific fields of LogEntry objects. You can define which fields are sensitive (such as principalEmail) and then grant the logging.fieldAccessor role to specific users or groups.6 Users without this role will see the log entry, but the sensitive fields will be redacted or omitted from their view."

Key Implementation Steps:

Identify Fields: Determine which paths in the JSON payload are sensitive.

Define Access: Use a Log View to define the scope of logs and apply field-level restrictions.7

Grant Permissions: Grant the standard logging.viewer role for general access and the logging.fieldAccessor role ONLY to the security team for the specific sensitive fields.

Why other options are incorrect:

B is incorrect: IAM conditions cannot natively parse and redact specific JSON fields within a log entry at the platform level; they are typically used for resource-level access.

C is incorrect: While excluding fields via a sink works, it is "all or nothing." If you exclude it at the sink, no one (including the security team) will see that data in the destination.

D is incorrect: This is a workaround that only works if the team uses BigQuery for logs. It doesn't solve the problem within the Cloud Logging Logs Explorer itself.

To ensure that the developers can view audit logs for the development environment and the security team can review all logs, you should grant IAM roles at the appropriate resource levels:

Grant logging.admin Role to the Security Team:

Assign the logging.admin role to the security team at the organization resource level.

This grants the security team full access to all logging data across the organization, including both production and development environments.

Grant logging.viewer Role to the Developer Team:

Assign the logging.viewer role to the developer team at the folder resource level that contains all the development projects.

This restricts the developers' access to only view logs in the development environment, ensuring they do not have access to production logs.

By using these roles and assigning them at the appropriate levels, you ensure that each team has the access they need while adhering to the principle of least privilege.

IAM Roles for Cloud Logging

Resource Hierarchy in Google Cloud

The requirements necessitate a private, cross-project service-to-service connection with explicit authorization—a capability perfectly addressed by Private Service Connect (PSC).

Internal Load Balancer: Ensures the service is isolated from the internet (Layer 7 Load Balancer for HTTP/S ML endpoint).

Private Service Connect (PSC): Allows a service (the model endpoint, exposed via the internal load balancer) in one VPC/project (producer) to be securely consumed by other VPCs/projects (consumers) using an internal IP address.

Defined List of Projects: PSC enables Explicit authorization, allowing the producer to define the allowed list of consumers that can establish a connection, directly meeting the granular restriction requirement.

Extracts:

"Private Service Connect provides... Explicit authorization. Private Service Connect provides an authorization model that gives consumers and producers granular control." (Source 2.4)

"Private Service Connect backends let Google Cloud load balancers send traffic through Private Service Connect to reach published services... Placing a load balancer in front of a managed service provides the consumer with more visibility and control..." (Source 2.4)

"Publish services by using Private Service Connect... Select the internal load balancer that hosts the service that you want to publish." (Source 2.3)

https://cloud.google.com/logging/docs/export/troubleshoot#errors_exporting_to_cloud_storage

https://cloud.google.com/logging/docs/export/troubleshoot

Unable to grant correct permissions to the destination: Even if the sink was successfully created with the correct service account permissions, this error message displays if the access control model for the Cloud Storage bucket was set to uniform access when the bucket was created. For existing Cloud Storage buckets, you can change the access control model for the first 90 days after bucket creation by using the Permissions tab. For new buckets, select the Fine-grained access control model during bucket creation. For details, see Creating Cloud Storage buckets.

Google Cloud Armor helps to protect applications from DDoS attacks and web application firewall (WAF) threats like XSS and SQLi. To use Google Cloud Armor security policies, certain requirements must be met:

External Load Balancers: Google Cloud Armor is specifically designed to work with external HTTP(S) load balancers, which handle traffic at the edge of the Google Cloud network. This type of load balancer provides a global frontend that can distribute traffic to various backends.

Load Balancing Scheme: The backend service associated with the Google Cloud Armor policy must have an EXTERNAL load balancing scheme. This scheme allows the service to accept traffic from outside the Google Cloud network, which is necessary for applying security policies effectively at the network edge.

These requirements ensure that Google Cloud Armor can inspect and filter incoming traffic before it reaches your web application's backend services, providing an additional layer of security against common web vulnerabilities.

References

Google Cloud Armor Documentation

External HTTP(S) Load Balancing Overview

Storing secrets securely is crucial for maintaining the integrity and confidentiality of your applications. Here is how you can achieve this using Google Cloud Platform:

Encrypt the Secrets: Use Customer-Managed Encryption Keys (CMEK) to encrypt your secrets. CMEK allows you to have greater control over the encryption keys used to protect your data. This ensures that even if the storage medium is compromised, the secrets remain protected by strong encryption.

Store in Cloud Storage: Store the encrypted secrets in Google Cloud Storage. Cloud Storage is a secure and scalable object storage service. By using encrypted storage, you can ensure that the secrets are securely stored and can only be accessed by authorized entities.

This method provides a secure and managed way to store secrets, ensuring that they are not exposed in plain text within your source code management system.

References

Customer-Managed Encryption Keys (CMEK)

Google Cloud Storage Security

To evaluate Google Cloud Platform (GCP) for PCI compliance and identify Google's inherent controls, you should review the "Google Cloud Platform: Customer Responsibility Matrix". This document provides detailed information about the shared responsibility model, outlining the security controls managed by Google and those that are the responsibility of the customer.

Steps to access and use the document:

Access the Document:

Go to the Google Cloud compliance resource center.

Locate the "Customer Responsibility Matrix" for PCI DSS compliance.

Review Inherent Controls:

The document lists various controls and specifies whether they are managed by Google, the customer, or both.

It covers different aspects such as infrastructure security, data protection, and compliance requirements.

Analyze PCI Compliance:

Use the matrix to understand which PCI DSS requirements are inherently addressed by Google Cloud.

Identify the controls you need to implement and manage as a customer to ensure full compliance.

By reviewing this document, you can gain a comprehensive understanding of the inherent controls provided by Google Cloud and the responsibilities you must fulfill to achieve PCI compliance.

Google Cloud Compliance Documentation

PCI DSS Compliance on Google Cloud

When a vulnerability patch is released for a running container in Google Kubernetes Engine (GKE), the recommended approach is to update the application code or apply the patch directly to the codebase. Then, a new container image should be built incorporating these changes. After building the new image, it should be deployed to replace the running containers. This method ensures that the containers run the updated, secure code.

Steps:

Update Application Code: Modify the application code or dependencies to incorporate the vulnerability patch.

Build New Image: Use a tool like Docker to build a new container image with the updated code.

Push New Image: Push the new container image to the Container Registry.

Update Deployments: Update the Kubernetes deployment to use the new image. This can be done by modifying the image tag in the deployment YAML file.

Redeploy Containers: Apply the updated deployment configuration using kubectl apply -f .yaml, which will redeploy the containers with the new image.

Use Google Shielded VM including secure boot Virtual Trusted Platform Module (vTPM) and integrity monitoring: Shielded VMs provide verifiable integrity of the VM by ensuring that it was not tampered with or compromised at the boot level. They use features like Secure Boot, vTPM, and integrity monitoring to detect and prevent malicious changes to the VM's operating system and firmware.

Activate Confidential Computing: Confidential Computing provides a secure environment for processing sensitive data. It uses hardware-based enclaves to protect data in use by ensuring it cannot be accessed by the underlying host or any other unauthorized entity. By leveraging Intel SGX or AMD SEV, it ensures that data remains encrypted even when it is being processed.

Enforce these actions by using organization policies: Organization policies can enforce the use of Shielded VMs and Confidential Computing across your organization. This ensures that all VMs comply with these security measures without requiring manual configuration for each VM.

References

Shielded VMs documentation

Confidential Computing documentation

Organization Policies documentation

The problem focuses on securing "super administrator accounts for the organization" when Cloud Identity is synced with Microsoft Entra ID and uses Entra ID for SSO. The key requirements are the principle of least privilege and strong authentication.

Principle of Least Privilege & Dedicated Accounts: Google's best practices strongly recommend creating dedicated, non-federated accounts for super administrators that are distinct from regular user accounts. These accounts should only be used for super administrator tasks and not for daily activities. This segregation ensures that the highest privilege accounts are isolated and adhere to the principle of least privilege by not having combined responsibilities.

Extract Reference: "Designate Organization Administrators... We recommend keeping your super admin account separate from your Organization Administrator group." and "Give super admins a separate account that requires a separate login. For example, user alice@example.com could have a super admin account alice-admin@example.com." and "Use the super admin account only when needed. Delegate administrator tasks to user accounts with limited admin roles. Use the least privilege approach..." (Google Cloud Documentation: "Super administrator account best practices | Resource Manager Documentation" - https://cloud.google.com/resource-manager/docs/super-admin-best-practices)

Strong Authentication (Google 2-Step Verification): Even when using a third-party identity provider like Microsoft Entra ID for most users, Google recommends enforcing Google's own 2-Step Verification for the critical super administrator accounts. This provides a "break-glass" mechanism that is independent of the external IdP. If the Entra ID integration were to fail or become compromised, the Google-managed super administrator accounts, protected by Google's own 2SV, would still be accessible for emergency recovery.

Extract Reference: "Even when using the legacy SSO profile, super admins can't sign in with SSO in these cases: Admin console. When super administrators try to sign in to an SSO-enabled domain via admin.google.com, they must enter their full Google administrator account email address and associated Google password (not their SSO username and password), and click Sign in to directly access the Admin console. Google doesn't redirect them to the SSO sign-in page." (Google Cloud Identity Help: "Super administrator SSO" - https://support.google.com/cloudidentity/answer/6341409) - This highlights that super admin accounts can bypass SSO for direct Admin console access, making Google 's 2SV crucial.

Extract Reference: "It's especially important for super admins to use 2SV because their accounts control access to all business and employee data in the organization. Protect your business with 2-Step Verification. Use security keys for 2-Step Verification." (Cloud Identity Help: "Security best practices for administrator accounts" - https://support.google.com/cloudidentity/answer/9011373)

Options C and D are incorrect because combining "organization administrator" (IAM role for GCP resources) and "super administrator" (Google Workspace/Cloud Identity domain-level control) privileges violates the principle of least privilege. Option A is less secure than B because relying solely on Entra ID's 2SV for super administrators means a compromise of Entra ID or an outage would leave the Google Cloud organization vulnerable without an independent break-glass mechanism.

To prevent developers from creating user-managed service account keys and reduce the risk of key mismanagement, you should enable an organization policy that specifically prohibits the creation of these keys.

Enable an organization policy to prevent service account keys from being created (C):

Google Cloud provides the capability to enforce organizational policies that restrict various actions, including the creation of service account keys. By enabling this policy, you ensure that developers cannot create new user-managed service account keys, thus minimizing the risk of key mismanagement and potential security breaches.

References

Service Accounts documentation

Organization Policy Service documentation

Setting up separate service perimeters for dev, staging, and prod environments allows for more granular control and monitoring. Automating the addition of new projects to the respective perimeters ensures that all projects are consistently secured without manual intervention.

Steps:

Set Up Service Perimeters: Use Access Context Manager to define and configure three separate service perimeters for dev, staging, and prod.

Deploy Monitoring Function: Create a Cloud Function that monitors the "implementation" folder for new projects using Stackdriver (Cloud Monitoring) and Cloud Pub/Sub.

Automate Perimeter Updates: Configure the Cloud Function to execute Terraform scripts that automatically add new projects to the appropriate service perimeter.

https://cloud.google.com/blog/products/g-suite/7-ways-admins-can-help-secure-accounts-against-phishing-g-suite

https://www.duocircle.com/content/email-security-services/email-security-in-cryptography#:~:text=Customer%20Login-,Email%20Security%20In%20Cryptography%20Is%20One%20Of%20The%20Most,Measures%20To%20Prevent%20Phishing%20Attempts &text=Cybercriminals%20love%20emails%20the%20most,networks%20all%20over%20the%20world.

To comply with GDPR requirements and manage encryption keys for workloads across multiple Google Cloud services, customer-managed encryption keys (CMEK) offer a suitable solution.

Customer-managed encryption keys (B):

CMEK allows you to create and manage encryption keys using Google Cloud Key Management Service (KMS). You maintain full control over the key lifecycle, including key rotation and destruction.

CMEK can be used with various Google Cloud services, such as Compute Engine, Google Kubernetes Engine, Cloud Storage, BigQuery, and Pub/Sub, ensuring consistent and compliant encryption across your environment.

Using CMEK, you can implement data protection by design, aligning with GDPR requirements by ensuring that encryption keys are appropriately managed and secured.

References

Customer-Managed Encryption Keys Documentation

Encryption at Rest in Google Cloud

To protect your web application from threats like malware by implementing TLS interception for incoming traffic, configuring a Secure Web Proxy with TLS offloading at the load balancer is an effective approach.?

Option A: By configuring a Secure Web Proxy, you can offload TLS traffic at the load balancer, inspect the decrypted traffic for threats such as malware, and then forward the inspected traffic to your web application. This approach ensures that encrypted traffic is securely analyzed without compromising the security of the data in transit.?

Option B: An internal proxy load balancer is designed for distributing traffic within a private network and may not support TLS interception capabilities required for inspecting incoming traffic from external sources.?

Option C: Hierarchical firewall policies in Google Cloud are used to enforce security rules across your organization but do not provide TLS interception capabilities.?

Option D: VPC firewall rules control traffic to and from VM instances based on specified rules but do not have the capability to perform TLS interception or traffic inspection.?

Therefore, Option A is the most suitable solution, as it allows for TLS interception through a Secure Web Proxy, enabling the inspection of incoming encrypted traffic to detect and mitigate threats like malware before the traffic reaches your web application.?

To implement a Zero Trust architecture that evaluates device posture (OS version, encryption, etc.) for access to data in Cloud Storage, you must use Context-Aware Access (CAA). CAA relies on Access Context Manager to define "Access Levels" and VPC Service Controls (VPC-SC) to enforce those levels for managed services like Cloud Storage.

According to Google Cloud Documentation (Context-Aware Access with VPC Service Controls):

"VPC Service Controls can use Access Context Manager access levels to restrict access based on a variety of attributes, including user identity, device security status (device policy), and IP address.2 By applying an access level to a service perimeter, you can ensure that only requests meeting those specific contextual requirements can access the resources within that perimeter."

Implementation Steps:

Access Context Manager: Create an access level that checks for device management status, minimum OS version, and other posture requirements (verified by the Chrome Enterprise/Endpoint Verification agent).

VPC Service Controls: Create a service perimeter around the project containing the Cloud Storage buckets.

Policy Binding: Associate the Access Level with the VPC-SC perimeter. Any request that doesn't meet the device policy (e.g., outdated OS) will be blocked at the API layer, even if the user has the correct IAM roles.

To manage IAM permissions efficiently for a large engineering team with different levels of access in development and production environments, follow these steps:

Create Separate Folders:

Create a folder for the development environment.

Create a folder for the production environment.

This allows you to organize projects and apply different policies and permissions to each environment.

Navigate to IAM & Admin in the GCP Console.

Select "Folders" from the left-hand menu.

Create a new folder named "Development".

Create a new folder named "Production".

Create Google Groups:

Create Google Groups for different teams within the engineering department (e.g., Development Team, Production Team).

This helps in managing permissions centrally.

Use the Google Admin Console to create groups.

Add relevant engineers to each group.

Assign Permissions at the Folder Level:

Assign appropriate IAM roles to the Google Groups at the folder level.

For example, grant Viewer role to the Development Team group for the development folder.

Grant Editor or more restrictive roles as required for the Production Team group for the production folder.

Select the development folder.

Go to the "Permissions" tab.

Click on "Add" and enter the email address of the Development Team Google Group.

Assign the "Viewer" role.

Repeat for the production folder, assigning appropriate roles to the Production Team Google Group.

By following these steps, you create a clear separation between development and production environments and manage permissions efficiently using Google Groups and folders.

Google Cloud IAM Documentation

Google Cloud Resource Manager Documentation

In Google Cloud's Logging service, log entries are automatically routed to the _Default log bucket unless configured otherwise. When you create a new log bucket and intend to redirect all log entries from the _Default bucket to this new bucket, the most efficient approach is to modify the existing _Default sink to point to the new log bucket.?

Option A: Creating a new user-defined sink with filters replicated from the _Default sink is redundant and may lead to configuration complexities.?

Option B: Implementing exclusion filters on the _Default sink and then creating a new sink introduces unnecessary steps and potential for misconfiguration.?

Option C: Disabling the _Default sink would stop all log routing to it, but creating a new sink to replicate its functionality is inefficient.?

Option D: Editing the _Default sink to change its destination to the new log bucket ensures a seamless transition of log routing without additional configurations.?

Therefore, Option D is the most efficient and straightforward method to achieve the desired log routing.?

To ensure end-user access is only allowed if the traffic originates from a specific known good CIDR and to utilize GCP's native SYN flood protection, you can use the following product:

VPC Firewall Rules: By configuring VPC firewall rules, you can control traffic to and from your instances based on IP address, protocol, and port. You can set rules to only allow traffic from a specific CIDR block, ensuring that only authorized traffic can reach your application.

Additionally, Google Cloud Platform provides built-in protections against SYN flood attacks, which are a type of DDoS attack. These protections are part of the underlying infrastructure and do not require additional configuration.

Using VPC firewall rules will help you comply with the internal requirement of allowing access only from a specific CIDR and provide the necessary SYN flood DDoS protection.

References

Google Cloud VPC Firewall Rules

Google Cloud DDoS Protection

The most efficient and recommended way to achieve real-time/near real-time ingestion of logs (including Google Workspace Audit Logs, which feed into Cloud Logging) to a third-party system is by using a Cloud Logging sink to a Pub/Sub topic.

Cloud Logging Sink: Creates a stream of logs filtered by type (e.g., authentication events).

Pub/Sub Topic: A messaging service that acts as a reliable, real-time message queue.

SIEM Subscription: The SIEM system can subscribe directly to the Pub/Sub topic, receiving log events as soon as they are published, meeting the real-time requirement.

Extracts:

"Cloud Logging sinks let you route logs to destinations like Cloud Storage, BigQuery, or Pub/Sub... Routing logs to Pub/Sub enables real-time streaming of log data for consumption by external services or applications, such as a third-party SIEM." (Source 7.1)

Option B (polling) and Option D (Cloud Storage bucket) are batch-oriented methods, which do not meet the real-time/near real-time requirement.

Use Cryptographic Verification If there is a risk of IAP being turned off or bypassed, your app can check to make sure the identity information it receives is valid. This uses a third web request header added by IAP, called X-Goog-IAP-JWT-Assertion. The value of the header is a cryptographically signed object that also contains the user identity data. Your application can verify the digital signature and use the data provided in this object to be certain that it was provided by IAP without alteration.

https://cloud.google.com/logging/docs/access-control#considerations roles/logging.privateLogViewer (Private Logs Viewer) includes all the permissions contained by roles/logging.viewer, plus the ability to read Data Access audit logs in the _Default bucket.

To provide on-premises hosts with access to Google APIs without using public IP addresses or the public internet, Google Cloud provides Private Google Access for on-premises hosts. This feature allows traffic to stay within the Google network via Cloud Interconnect or Cloud VPN.

According to the official Google Cloud Documentation (Configuring Private Google Access for on-premises hosts):

"Private Google Access for on-premises hosts provides a way for on-premises systems to connect to Google APIs and services by routing traffic through a Cloud VPN tunnel or Cloud Interconnect attachment (VLAN). On-premises hosts don't need public IP addresses; instead, they use internal IP addresses."

Key Implementation Steps:

Network Connectivity: Ensure your on-premises network is connected to your VPC via Cloud Interconnect or VPN.

DNS Configuration: You must configure your on-premises DNS to map API requests (like storage.googleapis.com) to special IP ranges. There are two primary options:

private.googleapis.com: Resolves to 199.36.153.8/30. This range supports most Google APIs but only those that are VPC-Service Control compatible.

restricted.googleapis.com: Resolves to 199.36.153.4/30. This is required specifically when using VPC Service Controls (VPC-SC) to ensure data cannot be exfiltrated to services outside the perimeter.

Routing: You must configure custom static routes in your VPC or use BGP to advertise the 199.36.153.8/30 (or 199.36.153.4/30) range back to your on-premises router.

Why other options are incorrect:

A is incorrect: Shared VPC is used to share a network across multiple Google Cloud projects, not to extend a VPC directly to on-premises hardware.

C is incorrect: While the IP range 199.36.153.8/30 is correct for private.googleapis.com, Cloud NAT is used for outbound internet access from VPC instances without external IPs; it does not facilitate private on-premises-to-API connectivity.

D is incorrect: VPC Peering connects two VPCs within Google Cloud. You cannot "peer" an on-premises data center directly via VPC Peering; you must use Interconnect or VPN.

The problem requires restricting the types of Google Cloud services that can be deployed within specific folders to enforce compliance, without affecting other parts of the resource hierarchy, using the most efficient and simple method.

Organization Policies: Organization policies allow you to define centralized, programmatic controls over your Google Cloud resources. They apply hierarchically, meaning a policy set on a folder applies to all projects and resources within that folder and its descendants.

Restrict Resource Service Usage Constraint: This specific organization policy constraint is designed precisely for controlling which Google Cloud services can be used (and thus deployed/created resources for) within a given part of the resource hierarchy. It supports both allowlists and denylists of service API identifiers.

Extract Reference: "The Restrict Resource Service Usage constraint controls the runtime access to all in-scope resources." and "This constraint can be used in two mutually exclusive ways: Denylist - resources of any service that isn't denied are allowed. Allowlist - resources of any service that isn't allowed are denied." (Google Cloud Documentation: "Restricting resource usage | Resource Manager Documentation" - https://cloud.google.com/resource-manager/docs/organization-policy/restricting-resources)

Folder-Level Application: Applying this organization policy at the folder level directly meets the requirement of applying restrictions "only to the designated folders without affecting other parts of the resource hierarchy." This is more efficient and simpler than applying a global policy with numerous exceptions.

Let's evaluate the other options:

B. Implement IAM conditions on service account creation within each folder: IAM conditions control permissions for who can do what. While they can be used for very fine-grained access control, they are not designed to restrict the types of services that can be deployed directly. Controlling service account creation doesn't prevent a user with appropriate permissions from deploying other resources.

C. Create a global organization policy... and apply exceptions: While technically possible, this is less efficient and simple if the goal is to only restrict specific folders. Managing exceptions for the entire rest of the organization would be more complex than simply applying the policy directly where it's needed.

D. Configure VPC Service Controls perimeters around each folder: VPC Service Controls primarily prevent data exfiltration and restrict API access at a network perimeter level. They are not designed to restrict which types of Google Cloud services can be deployed within a project or folder; rather, they control how allowed services interact with each other and with external endpoints.

Therefore, creating an organization policy with the "Restrict Resource Service Usage" constraint at the folder level is the most efficient, simple, and direct method to achieve the stated goal.

https://cloud.google.com/architecture/framework/security/data-residency-sovereignty#manage_your_operational_sovereignty

To ensure compliance with GDPR and implement data residency and operational sovereignty in the EU, the following steps can be taken:

Limit Physical Location of Resources: Use the Organization Policy Service to enforce the resource locations constraint. This ensures that all new resources are created within the specified regions (EU in this case).

Configure Organization Policy: Set up an organization policy that restricts the locations where new resources can be created. This is done through the Google Cloud Console or via the gcloud command-line tool.

Example:

gcloud resource-manager org-policies allow constraints/gcp.resourceLocations [europe-west1,europe-west2] --organization=YOUR_ORG_ID

Key Access Justifications (KAJ): Use Key Access Justifications to limit Google personnel's access to encryption keys based on attributes like their geographic location or citizenship.

Set Up KAJ: Implement KAJ policies to ensure that only authorized personnel within the EU can access encryption keys.

References

Organization Policy Service

Key Access Justifications

To ensure that each team's service account has the necessary permissions to manage resources within their assigned folders while adhering to the principle of least privilege, the following considerations apply:?

Folder Administrator Role: Granting each service account the Folder Administrator role on its respective folder provides comprehensive permissions to manage resources within that folder, including creating, updating, and deleting projects and resources. This approach ensures that teams have the necessary control over their environments without extending permissions beyond their assigned scope.?

Principle of Least Privilege: By assigning permissions at the folder level, you limit the service account's access to only the resources within its designated folder, aligning with the principle of least privilege and reducing the risk of unauthorized access to other parts of the organization.?

Therefore, Option A is the most effective approach, as it provides the necessary permissions for teams to manage their resources within their assigned folders while adhering to security best practices.?

https://cloud.google.com/resource-manager/docs/organization-policy/restricting-domains#setting_the_organization_policy

The domain restriction constraint is a type of list constraint. Google Workspace customer IDs can be added and removed from the allowed_values list of a domain restriction constraint. The domain restriction constraint does not support denying values, and an organization policy can't be saved with IDs in the denied_values list. All domains associated with a Google Workspace account listed in the allowed_values will be allowed by the organization policy. All other domains will be denied by the organization policy.