Google Professional-Cloud-Security-Engineer Dumps

The key requirement is restricting access based on the client device (i.e., "corporate computers"). Context-Aware Access (CAA) is the specific Google Cloud tool designed to enforce access based on contextual factors, including the device security status or IP address.

Context Restriction: Context-Aware Access allows you to define an Access Level based on attributes like device policy compliance, operating system, or IP address range—this addresses the "corporate computers" requirement.

Isolation and Control: The Access Level is then enforced via an Organization Policy applied at the Project Level (or the folder/organization level), which fulfills the requirement to isolate access to Cloud Storage for this project and restrict the access to specific resources (Cloud Storage).

VPC Service Controls (VPC SC) (Option B) are great for isolating projects and preventing data exfiltration, but its primary access restriction mechanisms are based on IP range, not fine-grained device security posture and user identity together, making CAA the more precise tool for device-specific enforcement. Also, applying VPC SC ingress/egress based on IP addresses for end-user access can be complex and less flexible than CAA.

IAM (Option D) only controls who (identity) can access a resource, not where or how (context) they are accessing it from.

Extracts:

"Context-Aware Access (CAA) integrates with Google Workspace or Cloud Identity to enforce granular access to Google Cloud resources based on a user's context, such as their location, device security status, and IP address." (Source 7.1)

"To enforce CAA for Google Cloud resources like Cloud Storage, you create an Access Level that defines the required context (e.g., only corporate-managed devices) and apply it via an Organization Policy constraint (e.g., iam.allowedServices) at the project level." (Source 7.2)

"CAA allows you to restrict access based on the device security posture, a key requirement for enforcing 'corporate computer' access." (Source 7.3)

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.

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.

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

Setting up a Shared VPC allows you to create a centrally managed network that spans multiple projects. Here's how you can achieve this while ensuring separation of duties:

Create a Host Project:

Create a project that will act as the host project for your Shared VPC.

Configure Shared VPC:

In the host project, enable the Shared VPC feature.

Create Service Projects:

Create separate service projects for different teams, such as developers and other stakeholders.

Assign Roles:

Security Team: Grant the Compute Network Admin role. This allows the security team to manage network resources, such as firewall rules, subnets, and routes.

Developers: Share the host project’s network with the service projects. Assign roles like Compute Instance Admin to developers in the service projects, enabling them to create and manage VM instances without altering network configurations.

Firewall Management:

The security team will define and manage firewall rules within the host project, ensuring consistent and secure network policies.

Benefits:

Separation of Duties: Security teams handle networking, and developers focus on application deployment and management.

Centralized Control: Network policies are centrally managed, ensuring compliance and security.

Scalability: Easy to add new projects and teams without compromising the overall network security.

References

Google Cloud VPC Documentation

Managing Resources with Shared VPC

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To manage consumer user accounts created using the corporate domain name, you can use the transfer tool for unmanaged user accounts provided by Google Cloud Identity. Here’s how you can proceed:

Identify Unmanaged Accounts:

Use the Cloud Identity interface to identify consumer (unmanaged) accounts that exist with your corporate domain.

Initiate Transfer Process:

Use the transfer tool for unmanaged user accounts to initiate the transfer. This tool helps in converting unmanaged accounts (consumer accounts) into managed accounts.

User Notification:

Users with unmanaged accounts will receive an email notification prompting them to accept the transfer to the organization’s managed account system.

Accept Transfer:

Users need to follow the instructions in the email to accept the transfer. Once accepted, their accounts will be managed under your organization’s Cloud Identity setup.

Benefits:

Centralized Management: All user accounts under your corporate domain are managed centrally, ensuring compliance and security.

Enhanced Security: Managed accounts provide better control over security policies and access management.

References

Transfer tool for unmanaged users

Cloud Identity Documentation

The Organization Policy Service provides a specific constraint called constraints/gcp.restrictServiceUsage. This is the most direct and efficient way to "Allow" or "Deny" specific Google Cloud APIs (services) at any node in the hierarchy (Org, Folder, or Project).

According to Google Cloud Documentation (Restricting Resource Service Usage):

"The Restrict Resource Service Usage constraint allows enterprise administrators to control which Google Cloud services can be used within their Google Cloud resource hierarchy. This constraint can be enforced on an Organization, Folder, or Project. When applied at the folder level, it restricts service usage for all descendant projects within that folder."

Why Option C is the most efficient:

Targeted: By applying it directly to the folder, you don't need to manage complex "exceptions" at the Org level (as in Option B).

Simple: It is a single policy rule that defines an "Allowlist" of services.

IAM vs. Org Policy: IAM (Option A) controls who can do something, but Org Policy controls what can be done. Even if a user is an Editor, the Org Policy will block them from enabling a restricted API.

VPC-SC (Option D): VPC Service Controls is much more complex and is used for data exfiltration prevention, not for simply restricting which APIs can be enabled/used in a project.

The Google Cloud Resource Hierarchy is designed to allow inheritance with the ability to override policies at lower levels (Folders or Projects).2 This is the standard way to handle exceptions for specific business units without weakening the security posture of the entire organization.

According to Google Cloud Documentation (Understanding Hierarchy Evaluation):

"By default, organization policies are inherited by the descendants of the resource on which the policy is enforced. However, you can explicitly override a policy on a child resource (Folder or Project) by setting a new policy that either adds to or replaces the inherited values.3 This allows for granular control and exception handling."

Why this is the correct approach:

Isolation: By moving the workload to a specific folder, you isolate the exception.

Least Privilege: Only the resources within that folder gain the exception; the rest of the organization remains protected by the constraints/compute.vmExternalIpAccess constraint.

No "Bypass" Role: There is no standard IAM role that allows a user to "bypass" an Org Policy (Option A). Policies are enforced at the API level regardless of user roles.

Auditability: Having a specific folder with an override makes it easy for auditors to see exactly where and why an exception exists.

When configuring SAML-based Single Sign-On (SSO) in an organization that's using Active Directory, the general steps would involve setting up a SAML profile, specifying the necessary URLs for sign-in and sign-out processes, uploading an X.509 certificate for secure communication, and setting up the Entity ID and Assertion Consumer Service (ACS) URL in the Identity Provider (which in this case would be Active Directory).

Access Google Cloud Console:

Log in to the Google Cloud Console with administrative privileges.

Navigate to the "IAM & Admin" section.

Set Session Length Timeout:

Go to the "Settings" page within IAM & Admin.

Locate the "Session control" settings.

Configure the session length timeout to a shorter duration, such as 15 or 30 minutes. This ensures that user sessions expire automatically after the specified time of inactivity.

Apply and Enforce the Policy:

Save the changes and ensure the new session timeout policy is applied across all users and services.

Communicate the new policy to employees, highlighting the importance of session security and the rationale behind the change.

Additional Security Measures:

Consider implementing additional measures such as automatic screen locks and secure session management practices.

Educate employees on the importance of logging out of their sessions and securing their devices when not in use.

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.

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).

The problem requires a cost-effective, scalable, and secure strategy to anonymize 3 TB of PII in BigQuery and Cloud SQL.

Cloud Sensitive Data Protection (Cloud DLP): Cloud DLP is Google Cloud's fully managed service designed for discovering, classifying, and de-identifying sensitive data, including PII, across various Google Cloud services and on-premises environments. It is specifically built for scale and security.

Extract Reference: "Sensitive Data Protection helps you discover, classify, and de-identify sensitive data." and "Sensitive Data Protection includes advanced de-identification techniques, such as tokenization, masking, and format-preserving encryption, to help you protect your sensitive data while preserving its utility for analysis." (Google Cloud Documentation: "Sensitive Data Protection overview" -

Data Profiling: Cloud DLP's data profiling feature automatically scans your data (e.g., BigQuery tables, Cloud SQL databases) to identify where sensitive data resides and to understand its characteristics. This is crucial for developing an effective de-identification strategy.

Extract Reference: "Data profiles provide metrics and insights about your sensitive and high-risk data, helping you make informed decisions about data protection, access, and storage." and "When you configure Sensitive Data Protection to profile data in BigQuery, Cloud Storage, and Datastore, it automatically scans your data for sensitive information." (Google Cloud Documentation: "About data profiles" -

De-identification Templates and Custom Configurations: After profiling identifies the PII, Cloud DLP offers various de-identification methods, which can be applied using pre-built templates or custom configurations. This allows for flexible and targeted anonymization. For BigQuery specifically, DLP can integrate with remote functions for de-identification at query time, minimizing data movement.

Extract Reference: "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." and "You can use this tutorial to replace that pipeline with a SQL query for only re-identification or both de-identification and re-identification." (Google Cloud Documentation: "De-identify BigQuery data at query time | Sensitive Data Protection Documentation" -

Let's evaluate the other options:

B. Copy small subset... create a custom anonymization script... apply the script to the entire 3 TB dataset: Relying on a "custom anonymization script" for 3 TB of data is generally not scalable, cost-effective, or secure compared to a managed service like Cloud DLP. Custom scripts require significant development, testing, maintenance, and robust error handling for large datasets, and might introduce security vulnerabilities.

C. Export all 3TB of data... to Cloud Storage... anonymize... Re-import: While feasible, exporting and re-importing 3 TB of data is a very time-consuming and potentially costly process due to data transfer and storage operations. Cloud DLP can often process data in-place or integrate more efficiently, especially with BigQuery. This option might not be the most cost-effective or efficient.

D. Inspect a representative sample... develop a custom script: Similar to option B, this relies on a custom script, which is less ideal for scalability, cost-effectiveness, and security than a managed service like Cloud DLP for 3 TB of sensitive data. Sample inspection is a good initial step, but the subsequent custom script for anonymization is the weak point.

Therefore, using Cloud DLP's data profiling to inform a de-identification strategy with its managed templates and configurations is the most appropriate, scalable, secure, and cost-effective approach for anonymizing PII in BigQuery and Cloud SQL.

Define Trusted Image Projects:

Identify the project or projects where your trusted operating system images are stored.

Ensure these images meet your organization’s security requirements and are regularly updated to mitigate vulnerabilities.

Create an Organization Policy:

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

Create a policy constraint that restricts the creation of boot disks to only those images stored in your trusted image project(s).

The policy constraint to use is constraints/compute.trustedImageProjects.

Apply the Policy:

Apply this organization policy at the appropriate level (organization, folder, or project) to enforce that all new VM instances use images from the trusted repository.

This ensures consistency in the security posture across all projects within the organization.

Monitor Compliance:

Regularly monitor the compliance with this policy using audit logs and other monitoring tools.

Update the trusted images as necessary to ensure they remain secure and compliant with your security standards.

In the Google Cloud resource hierarchy, Organization Policy is a powerful tool for governance, but its effectiveness depends on strict control over who can modify it. If a policy set at the folder level was "overwritten," it means a principal with the Organization Policy Administrator role (roles/orgpolicy.policyAdmin) at the project level (or folder level) changed the inheritance or defined a more permissive policy.1

According to Google Cloud Documentation (Organization Policy Service - IAM Roles):

"To manage organization policies, a principal must have the Organization Policy Administrator role. This role should be granted only at the Organization level to a limited set of trusted security or compliance administrators to prevent project owners from overriding security guardrails."

Why Option A is the best fix:

By removing the role from everyone except the central security team at the Organization level, you ensure that no one else has the technical permission to "Manage Policy" or click "Override" at any child node (folder or project).

B is insufficient because if a user has the role at the organization level, they can still apply overrides at the folder or project level.

C and D (Security Postures) are detective controls. While the secure_ai_extended template helps monitor drift, it does not prevent the occurrence. The question asks for a solution that "prevents a repeat occurrence," which requires a preventative IAM change.

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.

To meet data residency requirements on Google Cloud, the recommended option is to use Organization Policy Service constraints. This service allows you to define and enforce specific constraints across your organization, including constraints related to the geographical location where data is stored.

Organization Policy Service constraints allow administrators to enforce policies that restrict resources to specific locations. For instance, you can set policies to ensure that all storage buckets, databases, and other data resources reside within specific geographic boundaries. This helps in complying with data residency requirements.

References

Organization Policy Service documentation

Google Cloud Data Residency

If the environment variable GOOGLE_APPLICATION_CREDENTIALS is set, ADC uses the service account key or configuration file that the variable points to. If the environment variable GOOGLE_APPLICATION_CREDENTIALS isn't set, ADC uses the service account that is attached to the resource that is running your code.

To minimize the usage of service account keys and implement Workload Identity Federation (WIF) with your on-premises identity provider, you can use a workload identity pool integrated with your corporate Active Directory Federation Service (ADFS). This setup allows your on-premises Windows-based applications to authenticate to Google Cloud APIs without using long-lived service account keys.

Set Up a Workload Identity Pool:

In the Google Cloud Console, go to IAM & Admin > Workload Identity Federation.

Create a new workload identity pool.

Configure the pool to trust your corporate ADFS by specifying the federation provider details.

Create a Workload Identity Provider:

Within the created pool, set up a new provider for ADFS.

Configure the provider with the necessary details such as the issuer URL and credentials.

Configure Impersonation Rules:

Set up rules to allow principals in the workload identity pool to impersonate specific Google Cloud service accounts.

This is done by specifying the identity provider and the conditions under which the service accounts can be impersonated.

Update Applications:

Modify your on-premises applications to use the configured ADFS authentication to obtain tokens.

These tokens can then be exchanged for Google Cloud access tokens to interact with Google Cloud APIs securely.

By setting up the workload identity pool and configuring impersonation rules, you achieve secure authentication without needing to distribute and manage service account keys.

Workload Identity Federation Documentation

Federating On-Premises Identities to Workload Identity Federation

To investigate and remediate the issue of public access to Cloud Storage buckets, you can follow these steps:

Change Bucket Permissions:

Navigate to the Cloud Storage section in the Google Cloud Console.

For each affected bucket, remove any public access permissions (e.g., removing allUsers or allAuthenticatedUsers from the IAM policy).

Ensure that only authorized users have the necessary permissions to access the buckets.

Query Data Access Audit Logs:

Go to the Logging section in the Google Cloud Console.

Query the audit logs for the affected buckets to identify any unauthorized access. You can use filters to search for access by unauthorized users.

Correct the Misconfiguration:

After correcting the permissions, mute the relevant findings in the Security Command Center to indicate that the issue has been resolved.

This helps in maintaining a clear view of ongoing security issues and ensures the findings are not flagged again unless there's a new occurrence.

By following these steps, you ensure that the buckets are no longer publicly accessible, investigate any potential unauthorized access, and update the Security Command Center status to reflect the resolution of the issue.

Cloud Storage IAM Permissions

Viewing Audit Logs

Security Command Center Documentation

Cloud NAT (Network Address Translation) enables instances in a private network to connect to external services while not exposing their internal IP addresses to the public internet. This solution helps in situations where VMs need to initiate outbound connections without having a public IP address:

Cloud NAT Setup: Configure Cloud NAT for the subnet where your VMs are located. This allows these VMs to use the NAT gateway to communicate with external services securely.

Network Security: By using Cloud NAT, the internal IP addresses of VMs remain private, reducing the attack surface and enhancing security.

Operational Continuity: VMs can continue to communicate with external sites as needed for operations without requiring public IP addresses, meeting both security and functional requirements.

References

Cloud NAT Documentation

Understand Organization Policies:

Organization policies allow you to enforce restrictions on Google Cloud resources to adhere to your organization’s security and compliance requirements.

Policies can be set at the organization, folder, or project level, with project-level policies able to override higher-level policies unless explicitly prevented.

Identify the Policy Constraint:

The specific constraint in question is likely constraints/compute.vmExternalIpAccess, which controls whether VMs can have external IP addresses.

Check Policy Overwrites:

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

Check the policy settings at the project level under the affected folder to see if there is an override in place with an 'allow' value.

This override would permit the creation of VMs with external IP addresses despite the higher-level restriction.

Resolve the Policy Conflict:

If an override is found, remove or modify the project-level policy to align with the organizational policy denying external IP addresses.

Communicate with project administrators to ensure they understand and comply with the overarching security policies.

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.

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.

"In order to be able to keep using the existing identity management system, identities need to be synchronized between AD and GCP IAM. To do so google provides a tool called Cloud Directory Sync. This tool will read all identities in AD and replicate those within GCP. Once the identities have been replicated then it's possible to apply IAM permissions on the groups. After that you will configure SAML so google can act as a service provider and either you ADFS or other third party tools like Ping or Okta will act as the identity provider. This way you effectively delegate the authentication from Google to something that is under your control."

The problem is that the on-premises developers cannot resolve the Artifact Registry hostname, and they have no route to the internet. This is a classic DNS resolution problem in a hybrid network using private API access.

Artifact Registry is a Google-managed service, and its hostname (e.g., us-west1-docker.pkg.dev) resolves to a Google API domain. To access Google services privately from an on-premises network without an internet route, the traffic must be directed to Private Google Access IP ranges.

Issue: The on-premises DNS cannot resolve the Google service domain to the required private IP range.

Solution: The on-premises DNS needs a record (or a forwarding rule) to resolve the Google service domain to the dedicated IP ranges used for Private Google Access, specifically restricted.googleapis.com or private.googleapis.com (which provide the IP addresses for private access).

Extracts (Conceptual Basis):

"To direct traffic privately, you must ensure that your on-premises network's DNS is configured to resolve Google API and service domain names to the IP address range for Private Google Access." (Source 1.1)

"The IP addresses for private.googleapis.com are used for Private Google Access. To enable on-premises hosts to access Google APIs and services using this method, you must configure on-premises DNS to resolve requests for Google API domain names to the IP address range for private.googleapis.com." (Source 1.2)

Option B is incorrect because Private Google Access (PGA) is enabled on the VPC subnet, allowing VMs within the VPC to access Google APIs. However, the problem is with the on-premises developers; the on-premises DNS must be configured to resolve the hostname correctly.

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

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.

To meet the requirements of encrypted communication over private IP addresses between Compute Engine instances in different Google Cloud organizations, a Cloud VPN connection is appropriate:

Cloud VPN: Cloud VPN creates a secure, encrypted tunnel between your organization's VPC network and the third party's VPC network. This ensures that data transmitted over the network is encrypted and secure.

Private IP Communication: Cloud VPN allows communication over private IP addresses, which helps maintain security by keeping traffic within the Google Cloud network and not exposing it to the public internet.

Firewall Rules: VPC firewall rules can be configured to control the traffic that flows through the VPN, ensuring that only authorized traffic is allowed, further enhancing security.

By setting up a Cloud VPN connection, you can achieve secure, encrypted communication over private IP addresses between different Google Cloud organizations.

References

Cloud VPN Overview

To validate that all data written to BigQuery was done using the App Engine Default Service Account, you can use StackDriver Logging (now known as Cloud Logging) to filter and inspect the logs for BigQuery insert jobs. By hiding the entries matching the App Engine Default Service Account, you can ensure that no other service account has written to BigQuery if the resulting list is empty.

Steps:

Open Cloud Logging: Navigate to Cloud Logging in the Google Cloud Console.

Filter Logs: Apply a filter to display logs for BigQuery insert jobs.

Inspect Entries: Click on the email address that corresponds to the App Engine Default Service Account in the authentication field.

Hide Matching Entries: Select the option to hide matching entries.

Validate: Check if the resulting list is empty, confirming that no other service account has performed write operations to BigQuery.

Scenarios for exporting Cloud Logging data: Splunk This scenario shows how to export selected logs from Cloud Logging to Pub/Sub for ingestion into Splunk. Splunk is a security information and event management (SIEM) solution that supports several ways of ingesting data, such as receiving streaming data out of Google Cloud through Splunk HTTP Event Collector (HEC) or by fetching data from Google Cloud APIs through Splunk Add-on for Google Cloud. Using the Pub/Sub to Splunk Dataflow template, you can natively forward logs and events from a Pub/Sub topic into Splunk HEC. If Splunk HEC is not available in your Splunk deployment, you can use the Add-on to collect the logs and events from the Pub/Sub topic.

The core requirements are: centralized, tamper-proof, long-term (seven years) immutable audit trails for administrative and data access activity.

Centralization: The current logging is fragmented. To centralize, you need to collect logs from across the organization. Cloud Logging sinks configured at the organization level are designed for this purpose. They allow you to route logs from all projects within an organization to a single destination.Extract Reference: "Aggregated exports allow you to export logs from multiple Google Cloud projects, folders, or your entire organization. An aggregated export can include all logs from all included resources, or you can use queries to include only specific logs." (Google Cloud documentation:

Long-Term Storage (Seven Years): Cloud Logging buckets have default retention periods (e.g., 30 days for Data Access logs, 400 days for Admin Activity logs) which are not sufficient for a seven-year requirement. Cloud Storage is ideal for long-term archival.Extract Reference: "Cloud Storage is a highly scalable and durable object storage service suitable for archiving large volumes of data for extended periods." (Google Cloud documentation, general overview of Cloud Storage features)

Tamper-Proof / Immutability: This is a critical requirement for audit trails in financial services under strict regulatory frameworks. Cloud Storage's "object retention lock" feature provides immutability. Once an object retention lock is set on a bucket, objects within that bucket cannot be deleted or overwritten for a specified duration, ensuring data integrity for compliance purposes.Extract Reference: "Object Retention Lock helps you meet compliance requirements by preventing data from being deleted or modified for a fixed amount of time or indefinitely. This feature satisfies SEC Rule 17a-4(f), FINRA Rule 4511(c), and CFTC Regulation 1.31(c)-(d) requirements." (Google Cloud documentation:

Let's evaluate the other options:

A. Implement Pub/Sub to stream all audit logs from each project in real-time to an external SIEM: While Pub/Sub can centralize real-time streaming to a SIEM, the solution described does not inherently guarantee tamper-proof storage or 7-year immutability within Google Cloud. The SIEM itself would need to provide those capabilities, which is outside the scope of Google Cloud's direct offering for this specific requirement.

C. Enable Security Command Center across the organization: Security Command Center (SCC) provides centralized visibility into security posture, threats, and compliance. However, SCC is a security management and monitoring platform; it does not serve as the primary long-term, immutable storage for raw audit logs. It consumes information from logs but doesn't store them in a way that meets the 7-year immutable archival requirement.

D. Individually configure Cloud Audit Logs for all Google Cloud services in each project. Store the logs in regional Cloud Logging buckets with 30-day retention policies: This fails on multiple counts: it's not centralized (requires individual configuration), and the 30-day retention in Cloud Logging buckets is far short of the seven-year requirement. It also doesn't explicitly guarantee tamper-proof storage beyond the default logging immutability.

Therefore, option B directly addresses all aspects of the requirement: centralization via organization-level sinks, long-term storage with Cloud Storage, and immutability/tamper-proofing with object retention lock.

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

Understanding Organization Policies:

Organization policies are rules that can be set at different levels of the resource hierarchy in GCP to enforce governance and compliance.

These policies can be set at the organization node, folders, and projects, and they are inherited down the hierarchy unless explicitly overridden.

Hierarchy and Policy Inheritance:

The provided resource hierarchy has an organization node (Example.com), folders (Folder 1 and Folder 2), and a project (Project 2) under Folder 2 with a specific VPC (VPC A).

Each node in the hierarchy can have its own policies, and these policies are inherited by child nodes unless overridden.

Analyzing the Policies in the Hierarchy:

Organization Node Policy:

json

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "allValues": "DENY" } }

This policy at the organization node denies all load balancer types.

Folder 2 Policy:

json

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "deniedValues": ["INTERNAL_TCP_UDP", "INTERNAL_HTTP_HTTPS"] } }

This policy at Folder 2 denies the creation of INTERNAL_TCP_UDP and INTERNAL_HTTP_HTTPS load balancers.

Project 2 Policy:

json

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "deniedValues": ["EXTERNAL_TCP_PROXY", "EXTERNAL_SSL_PROXY"] } }

This policy at Project 2 denies the creation of EXTERNAL_TCP_PROXY and EXTERNAL_SSL_PROXY load balancers.

Policy Application to VPC A:

Since policies are inherited, VPC A (which is within Project 2 under Folder 2) will be affected by the policies of both Folder 2 and Project 2.

Combining the denied values from both Folder 2 and Project 2:

From Folder 2: INTERNAL_TCP_UDP, INTERNAL_HTTP_HTTPS

From Project 2: EXTERNAL_TCP_PROXY, EXTERNAL_SSL_PROXY

Conclusion:

VPC A will have the following load balancer types denied: INTERNAL_TCP_UDP, INTERNAL_HTTP_HTTPS, EXTERNAL_TCP_PROXY, EXTERNAL_SSL_PROXY.

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

VPC Peering is between organizations not between Projects in an organization. That is Shared VPC. In this case, both projects are in same organization so having VPC Service Controls around both projects with necessary rules should be fine.

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.

The requirement to ensure the master encryption key material never leaves the on-premises hardware (HSM) and retaining the unilateral ability to revoke access are the defining features of Cloud External Key Manager (Cloud EKM).

Key Residency: Cloud EKM allows you to use encryption keys stored and managed in a supported external key management system, such as an on-premises HSM, for encrypting data in Google Cloud services like BigQuery and Cloud Storage. This ensures the key material remains in your accredited hardware.

Unilateral Control: Since Google Cloud must request the key from the external system for every encryption/decryption operation, revoking access (by disabling the key or revoking Google's access) in the external system immediately renders the data in Google Cloud inaccessible, granting the customer unilateral control.

Extracts:

"Cloud External Key Manager (Cloud EKM) is a cloud service that lets you encrypt data in Google Cloud with keys you manage outside of Google Cloud." (Source 6.1)

"The key material is stored on an external system, such as a Cloud EKM partner or an on-premises HSM, and never leaves that system." (Source 6.1)

"The customer can unilaterally revoke access to the key at the EKM system, making the encrypted data in Google Cloud inaccessible, which is a key requirement for highly regulated industries." (Source 6.2)

The problem describes an application with two Cloud Run services (Service A - frontend, Service B - backend) and requires setting up IAM with the principle of least privilege. Service A calls Service B.

Principle of Least Privilege: This principle dictates that each entity (in this case, a Cloud Run service) should only have the minimum permissions necessary to perform its function.

Separate Service Accounts for Separate Services: To adhere to the principle of least privilege, it's best practice to assign a unique service account to each distinct service or component. This ensures that a compromise of one service account does not grant excessive permissions across other services. Service A needs permissions to run itself and to invoke Service B. Service B only needs permissions to run itself.Extract Reference: "Assign a service account to a Cloud Run service. The service account acts as the identity for your service and determines what permissions your revisions have when executing requests. It is a best practice to grant each service account only the permissions that are required to run the specific service (principle of least privilege)." (Google Cloud documentation:

Authentication for Cloud Run Services: When one Cloud Run service (caller) needs to invoke another Cloud Run service (callee), the caller must be authorized to do so. This is typically achieved by assigning the roles/run.invoker role on the callee service to the caller's service account.Extract Reference: "To allow a service to invoke another service, grant the roles/run.invoker role on the called service to the caller's service account." (Google Cloud documentation:

Let's evaluate the options:

A. Create a new service account with the permissions to run service A and service B. Require authentication for service B. Permit only the new service account to call the backend. This violates the principle of least privilege by giving a single service account permissions for both services. If that service account were compromised, both services would be affected.

B. Create two separate service accounts. Grant one service account the permissions to execute service A, and grant the other service account the permissions to execute service B. Require authentication for service B. Permit only the service account for service A to call the back-end. This aligns perfectly with least privilege. Service A gets its own identity, Service B gets its own identity. Service A's service account is then granted run.invoker permissions on Service B, allowing it to call the backend while Service B requires authentication. This is the recommended approach.

C. Use the Compute Engine default service account to run service A and service B. Require authentication for service B. Permit only the default service account to call the backend. The Compute Engine default service account often has broad permissions (e.g., editor role in its project). Using it violates the principle of least privilege and is generally discouraged for production applications due to the potential for excessive permissions.

D. Create three separate service accounts. Grant one service account the permissions to execute service A. Grant the second service account the permissions to run service B. Grant the third service account the permissions to communicate between both services A and B. Require authentication for service B. Call the back-end by authenticating with a service account key for the third service account. This introduces unnecessary complexity with a third service account just for communication. More critically, using a service account key for authentication is generally discouraged in Cloud Run environments where ADC (Application Default Credentials) can be used, as managing keys securely becomes an operational overhead and security risk. Cloud Run services automatically use their attached service accounts for authentication when making calls to other Google Cloud services, including other Cloud Run services.

Therefore, option B is the best solution, adhering to the principle of least privilege and Google Cloud best practices for Cloud Run service-to-service authentication.

The action fails because a constraints/iam.allowedPolicyMemberDomains organization policy is in place and only members from the flowlogistic.com organization are allowed. The inheritFromParent: false property on the “Apps” folder means that it does not inherit the organization policy from the organization node. Therefore, only the policy set at the folder level applies, which allows only members from the flowlogistic.com organization. As a result, the attempt to grant access to the user testuser@terramearth.com fails because this user is not a member of the flowlogistic.com organization.

To migrate the current data backup and disaster recovery solutions to GCP while keeping the production environment on-premises, the most scalable and cost-efficient solution is using Google Cloud Storage with scheduled tasks and the gsutil command.

Setup Cloud Storage: Create a Cloud Storage bucket to store the backups.

Go to the Cloud Console and navigate to Cloud Storage.

Click "Create bucket" and follow the prompts to configure the storage bucket.

Install gsutil: Ensure gsutil is installed on the on-premises servers.

gsutil is a command-line tool for interacting with Cloud Storage.

Follow the installation guide here.

Create Backup Script: Write a script to upload data to Cloud Storage using gsutil.

#!/bin/bash gsutil -m cp -r /path/to/local/backup gs://your-bucket-name

Schedule Backup Task: Use a scheduling tool like cron on Linux to run the backup script at regular intervals.

Edit the crontab file with crontab -e and add an entry like:

Cloud Storage Documentation

gsutil Documentation

- constraints/compute.trustedImageProjects

This list constraint defines the set of projects that can be used for image storage and disk instantiation for Compute Engine. If this constraint is active, only images from trusted projects will be allowed as the source for boot disks for new instances.

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

A. Create a Cloud Build pipeline that will monitor changes to your container templates in a Cloud Source Repositories repository. Add a step to analyze Container Analysis results before allowing the build to continue:

Use Cloud Build to automate your CI/CD pipeline.

Integrate Container Analysis to scan container images for vulnerabilities during the build process.

If vulnerabilities are found, configure the build to fail, preventing deployment of insecure containers.

E. In your CI/CD pipeline, add an attestation on your container image when no vulnerabilities have been found. Use a Binary Authorization policy to block deployments of containers with no attestation in your cluster:

Use Binary Authorization to enforce deploy-time security policies.

Configure your CI/CD pipeline to generate attestations for container images that pass vulnerability scans.

Binary Authorization will then block deployments of any containers without valid attestations, ensuring only secure images are deployed.

The best way to describe security responsibilities when using a Google Cloud service, especially a managed one like a managed AI service, is to invoke the Shared Responsibility Model.

This model clarifies that Google secures the underlying infrastructure (the hardware, data centers, and the service platform itself), while the customer (your organization) retains responsibility for security in the cloud, specifically: data, access controls (IAM), and operational monitoring.

Extracts:

"This division of duties is defined by the Shared Responsibility Model, a framework that clarifies the security responsibilities of both the cloud provider and the customer." (Source 3.2)

"While cloud providers secure the infrastructure, customers must take active steps to protect their applications, data, and access controls." (Source 3.2)

"The following areas are customer responsibilities as a user of any public cloud: Configuring Identity and Access Management (IAM) to ensure that the contents of your organization are accessed and modifiable by the appropriate personnel... Ensuring you have read all documentation to understand and follow best practices." (Source 3.5)

For Google Cloud, the customer is responsible for: "Managing user permissions and access controls using Cloud IAM... Encrypting sensitive data... Monitoring logs and security events using Cloud Audit Logs and Security Command Center." (Source 3.2)

Option C is incorrect because using PaaS/Managed Services does NOT transfer all security concerns to Google. The customer is still responsible for key areas.

Option B is the most comprehensive and correct answer as it immediately introduces the foundational concept (Shared Responsibility Model) and focuses on the most critical customer responsibilities: IAM (access controls), data procedures (upload/download), and monitoring logs (detective controls), all of which fall squarely under the customer's purview for a managed service.

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.​

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.

To handle significant traffic spikes and potentially malicious IPs, you can use Google Cloud Armor to configure rate-based bans. This approach allows you to automatically ban clients that exceed a predefined request rate, protecting your application from potential denial-of-service attacks.

Access Google Cloud Console: Log in to your Google Cloud Console.

Navigate to Google Cloud Armor: Go to the "Security" section and select "Google Cloud Armor".

Create Security Policy: Create a new security policy or edit an existing one. Add a new rule to the policy.

Configure Rate-Based Ban: Set the action to rate_based_ban. Define the rate limit (e.g., requests per second) and set the ban_duration_sec parameter to the desired time interval.

Apply the Policy: Apply the security policy to your backend service or load balancer.

Monitor and Adjust: Monitor the traffic patterns and adjust the rate limits and ban durations as necessary to balance security and availability.

Objective: Provide evidence of access reviews for an upcoming audit.

Solution: Use Policy Analyzer to review and report on IAM policies.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Policy Analyzer tool.

Step 3: Select the project for which you need to review access policies.

Step 4: Use the tool to generate reports on IAM roles and permissions.

Step 5: Export the reports as evidence for the audit.

Policy Analyzer provides detailed insights into IAM policies, helping you to review access configurations and generate necessary reports for compliance and auditing purposes.

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.

Dedicated Interconnect provides a high-bandwidth (up to 80 Gbps per connection) and secure connection between your on-premises network and Google Cloud. It ensures reliable and high-speed data transfer, meeting the requirement of at least 50 Gbps bandwidth.

Steps:

Set Up Dedicated Interconnect: Order a Dedicated Interconnect connection through the Google Cloud Console.

Configure VLAN Attachments: Set up VLAN attachments to segment traffic between your on-premises network and Google Cloud.

Establish BGP Sessions: Configure BGP sessions for dynamic routing and failover.

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

To identify all principals who can change firewall rules, you need to determine which users or service accounts have permissions that allow them to modify firewall rules in your Google Cloud project. The correct permissions to check for this are compute.firewalls.create and compute.firewalls.delete. These permissions enable a user to create and delete firewall rules, respectively.

The Policy Analyzer tool in Google Cloud allows you to query and analyze IAM policies to identify which principals have specific permissions. By using Policy Analyzer, you can effectively identify all principals with the compute.firewalls.create and compute.firewalls.delete permissions.

Open Policy Analyzer: Go to the Google Cloud Console, navigate to IAM & Admin, and select Policy Analyzer.

Set Up Query: Create a new query specifying the permissions compute.firewalls.create and compute.firewalls.delete.

Run Query: Execute the query to retrieve a list of principals who have these permissions.

Review Results: Analyze the results to identify all users and service accounts with the capability to modify firewall rules.

This method ensures you have a comprehensive list of all principals who can change firewall rules, enhancing your audit and security posture.

Google Cloud Policy Analyzer Documentation

Google Cloud IAM Documentation

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.

The greatest risk to regulatory compliance stems from violations of the Principle of Least Privilege and the lack of enforced configuration/hardening standards. Regulatory compliance typically mandates strict control over infrastructure and sensitive systems.

Option A (Greatest Risk): Broad IAM roles violate the principle of least privilege, which is a fundamental compliance requirement (e.g., ISO 27001, PCI DSS). Allowing users to create and manage critical resources (VMs) without a pre-defined hardening process means new resources can be deployed in a non-compliant, vulnerable state (e.g., unpatched, open ports, default configurations). This lack of control and excessive access poses an immediate and high risk to the security posture and compliance.

Option B (Risk Reduction): Uniform bucket-level access reduces risk by enforcing a consistent policy for all objects in a bucket, preventing individual object-level IAM policies that can lead to misconfigurations and unauthorized access.

Option C (Risk Reduction): Mandating CMEK is a security-enhancing control that reduces risk by giving the customer exclusive control over the encryption keys for sensitive data, which is a common requirement in regulated environments.

Option D (Necessary Control): Providing the audit team access to Cloud Audit Logs is a compliance requirement for monitoring, accountability, and forensic investigation, not a risk.

Extracts:

"The principle of least privilege states that a user should only be granted the minimum permissions necessary to perform their work. Overly permissive roles introduce a significant risk." (Source 5.1)

"Non-compliant configurations, such as unhardened virtual machines or resources with insufficient security controls, are a major source of security breaches and regulatory findings." (Source 5.2)

Multiple network interfaces. The simplest way to connect multiple VPC networks through a virtual appliance is by using multiple network interfaces, with each interface connecting to one of the VPC networks. Internet and on-premises connectivity is provided over one or two separate network interfaces. With many NGFW products, internet connectivity is connected through an interface marked as untrusted in the NGFW software.

This architecture has multiple VPC networks that are bridged by an L7 next-generation firewall (NGFW) appliance, which functions as a multi-NIC bridge between VPC networks. An untrusted, outside VPC network is introduced to terminate hybrid interconnects and internet-based connections that terminate on the outside leg of the L7 NGFW for inspection. There are many variations on this design, but the key principle is to filter traffic through the firewall before the traffic reaches trusted VPC networks.

Here are the permissions available to organizationRoleAdmin

iam.roles.create

iam.roles.delete

iam.roles.undelete

iam.roles.get

iam.roles.list

iam.roles.update

resourcemanager.projects.get

resourcemanager.projects.getIamPolicy

resourcemanager.projects.list

resourcemanager.organizations.get

resourcemanager.organizations.getIamPolicy

There are sufficient as per least privilege policy. You can do user management as well as auditing.

The problem states that the organization is using Model Garden and needs to ensure users can only access approved models. This implies a need for a central, enforceable control mechanism.

Organization Policies and Constraints: Google Cloud Organization Policy Service allows administrators to centrally control resources across an organization. Constraints are specific types of restrictions that can be applied. For AI Platform (which includes Vertex AI and Model Garden), there are specific constraints designed to control model usage.

vertexai.allowedModels Constraint: This specific organization policy constraint is designed precisely to restrict which models can be used within a given organization, folder, or project. It provides a centralized way to define a list of approved models that users are allowed to access.Extract Reference: "The vertexai.allowedModels constraint allows you to specify a list of model URIs that are allowed to be used within the resource hierarchy." and "This constraint helps organizations enforce compliance and control which models are consumed by their users." (Google Cloud documentation, typically found under Organization Policy Service constraints for Vertex AI or AI Platform)

Let's evaluate the other options:

A. Configure IAM permissions on individual Model Garden to restrict access to specific models: IAM (Identity and Access Management) typically grants permissions at a broader resource level (e.g., project, dataset, model resource). While you can control who can manage models, directly restricting access to specific models within Model Garden for consumption via IAM roles on individual models is not the primary mechanism for enforcing a list of approved models across an organization in a preventative way. Organization policies are designed for this kind of broad, preventative control.

B. Regularly audit user activity logs in Vertex AI to identify and revoke access to unapproved models: Auditing logs is a reactive measure. While important for monitoring and detecting violations, it does not prevent users from accessing unapproved models in the first place. The requirement is to ensure they can only access approved models, implying a proactive control.

C. Train custom models within your Vertex AI project and restrict user access to these models: This is about managing access to custom-trained models, not about controlling access to the collection of models in Model Garden, which often includes pre-trained or publicly available models that need to be whitelisted. It doesn't address the requirement of ensuring users only access approved models from the broader Model Garden collection.

Therefore, implementing an organization policy with the vertexai.allowedModels constraint is the most effective and Google-recommended way to centrally ensure that users can only access approved models within an organization using Model Garden.

For "automatic discovery, redaction, or pseudonymization" of sensitive data, the specific product is Sensitive Data Protection (formerly known as Cloud Data Loss Prevention - DLP).10

According to Google Cloud Documentation (Sensitive Data Protection Overview):

"Sensitive Data Protection provides visibility into where PII exists in your organization. It allows you to automatically discover and classify data using over 150 predefined infoTypes (like SSN, Credit Card, etc.). Beyond discovery, it can redact (remove), mask (cover), or pseudonymize (replace with a token) the data so that it can be used for analysis without exposing the raw PII."

Why other options are incorrect:

A is incorrect: Cloud Armor is a WAF; it doesn't scan data contents inside a database for PII.

C is incorrect: Encryption (KMS) protects the data from unauthorized disk access, but once an authorized user opens the database, the PII is still visible. It doesn't perform "redaction" or "pseudonymization."

D is incorrect: While the DLP API is mentioned, this option focuses on Cloud Storage and alerts rather than the "redaction/pseudonymization" for analysis requested in the prompt. Option B is the comprehensive managed service approach.

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)

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.

Organization Policy: Use the constraints/compute.skipDefaultNetworkCreation organization policy constraint to disable the creation of default networks in new projects.

Policy Application: Apply this constraint at the organization level to ensure it affects all projects within your organization, preventing the creation of default networks.

Best Practices Compliance: Following this best practice helps maintain a clean and secure network configuration by avoiding the use of default networks, which may not be properly segmented or secured.

Verification: Verify the policy application by creating new projects and ensuring that default networks are not created. References:

Google Cloud - Organization Policy Constraints

Google Cloud - Best Practices for Enterprise Organizations

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

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

Extracts:

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

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

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

Cloud Identity-Aware Proxy (Cloud IAP) provides a way to control access to your web applications and resources running on Google Cloud. It works by verifying the identity of a user trying to access the application and supports multi-factor authentication (MFA). Cloud IAP can restrict access to users on the corporate network and also supports access over the internet securely.

Steps:

Enable Cloud IAP: In the Google Cloud Console, navigate to the IAP section and enable IAP for your web application.

Configure OAuth Consent Screen: Set up the OAuth consent screen to manage how users grant access.

Set Up Authentication: Use Google Identity Platform to manage users and enable two-factor authentication.

Add Users: Grant users access to the application by adding their identities in the IAP settings.

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.

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

Create a Cloud Storage Bucket:

Go to the Google Cloud Console.

Navigate to Cloud Storage and create a new bucket.

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

Configure Log Sink:

Go to the Logging section in the Google Cloud Console.

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

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

Verify Configuration:

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

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

References

Creating and Managing Log Sinks

Cloud Storage Locations

The requirement is to protect data while in use (meaning data in memory or CPU registers, during processing). This is a concept addressed by Confidential Computing using Trusted Execution Environments (TEEs).

Extracts:

"Confidential VMs are an IaaS solution... Confidential VMs offer: Encryption for 'data in use', including the processor state and the virtual machine's memory." (Source 4.1)

"Confidential computing protects data during processing by isolating workloads inside hardware-based trusted execution environments (TEEs), ensuring even cloud operators cannot access them." (Source 4.3)

"Confidential VMs extend the standard virtual machine concept by adding hardware-enforced confidentiality controls... they ensure data remains encrypted not only at rest and in transit, but also while in use." (Source 4.4)

Options A (CMEK) and B (CSEK) protect data at rest (disk encryption). Option D (Shielded VM) protects integrity and prevents rootkit compromise but does not encrypt memory while the data is actively being processed. Only Confidential VM (or TEE) protects data in use.

Rewriting the objects in-place within the same bucket, specifying the new CMEK for encryption, allows you to re-encrypt the data without downloading and re-uploading it, thus minimizing costs and time.

TCP Proxy Load Balancing is implemented on GFEs that are distributed globally. If you choose the Premium Tier of Network Service Tiers, a TCP proxy load balancer is global. In Premium Tier, you can deploy backends in multiple regions, and the load balancer automatically directs user traffic to the closest region that has capacity. If you choose the Standard Tier, a TCP proxy load balancer can only direct traffic among backends in a single region.

To provide users with SSO-based access to selected cloud apps, Cloud Identity as your IdP supports the OpenID Connect (OIDC) and Security Assertion Markup Language 2.0 (SAML) protocols.

Generate Supply Chain Levels for Software Artifacts (SLSA) level 3 assurance by using Cloud Build: SLSA is a framework for ensuring the integrity of software artifacts. By using Cloud Build, you can automate the build process and generate SLSA level 3 compliance, which includes verifiable build steps and provenance.

View the build provenance in the Security insights side panel within the Google Cloud console: The build provenance provides a detailed history of how the software was built, including the source code, build process, and any dependencies. This information is accessible through the Security insights side panel in the Google Cloud console, allowing you to verify the integrity and authenticity of your software artifacts.

References

Supply Chain Levels for Software Artifacts (SLSA) documentation

Cloud Build documentation

Security insights in Google Cloud console

To maintain a historical record of what was running in Google Cloud Platform at any point in time, you should use Forseti Security to automate inventory snapshots. Forseti Security is an open-source toolkit that helps to automate security and compliance in GCP by taking inventory snapshots of GCP resources.

Step-by-Step:

Install Forseti Security:

Follow the installation guide to deploy Forseti Security on your GCP environment.

Configure Inventory:

Set up the inventory module in Forseti to capture and store snapshots of GCP resources.

Schedule Snapshots:

Use Forseti’s configuration to schedule regular inventory snapshots.

Access Historical Data:

Review and access historical records through Forseti’s dashboard or by querying the Forseti database.

Compliance and Monitoring: Use Forseti to ensure compliance and monitor changes over time.

Forseti Security Overview

Inventory Module

Workload Identity is the Google-recommended method for GKE workloads to access Google Cloud services. It eliminates the need for manual management of service account keys (JSON files), which are a major security risk if leaked.1

According to Google Cloud Documentation (Workload Identity Federation for GKE):

"Workload Identity is the recommended way for your workloads running on GKE to access Google Cloud services in a secure and manageable way. It allows a Kubernetes service account in your GKE cluster to act as a Google IAM service account.2 When you use Workload Identity, you don't need to manage service account keys or store them as Kubernetes secrets."

Why other options are incorrect:

A is incorrect: Service account keys are long-lived and difficult to rotate. Using them increases the risk of credential theft.

C & D are incorrect: Attaching a service account to a Node gives every pod running on that node the same permissions. This violates the Principle of Least Privilege because different workloads on the same node should have different permissions.

To configure the behavior where each department member automatically has read-only access to all new project resources created by any department member, you should use Google Cloud's folder structure and IAM roles effectively. Here are the steps:

Create Folders for Departments: Create a folder under your Organization for each department. Folders help organize resources and provide a hierarchy for applying policies and permissions.

Assign IAM Roles to Google Groups: Assign the Project Viewer role to the Google Group associated with each department at the folder level. This ensures that all members of the group have the necessary permissions.

Inherited Permissions: When a department member creates a new project under their department's folder, the permissions assigned to the folder are inherited by the new project. Thus, all department members will automatically have read-only access to the project's resources.

Navigate to IAM & Admin in the GCP Console.

Select "Folders" from the left-hand menu.

For each department, create a new folder under the organization.

Select the newly created folder, and then go to the "Permissions" tab.

Click on "Add" to assign a new role.

Enter the email address of the Google Group for the department.

Assign the "Project Viewer" role to the group.

Access Restrictions: Since the permissions are applied at the folder level, only the members of the specific department's Google Group will have read-only access to the projects created in that folder. Other departments will not have access unless explicitly granted.

By following these steps, you ensure that department members have the required access to their respective projects without manual configuration for each new project.

Google Cloud IAM Documentation

Google Cloud Resource Manager Documentation

Cloud DNS with DNSSEC (Domain Name System Security Extensions) provides authentication for DNS responses, ensuring that they are legitimate and have not been tampered with. DNSSEC helps protect against DNS spoofing and cache poisoning attacks, which are common techniques used in DDoS attacks.

Steps:

Enable DNSSEC: In the Google Cloud Console, navigate to Cloud DNS and enable DNSSEC for your managed zones.

Configure Key Signing: Set up key signing keys (KSK) and zone signing keys (ZSK) to sign your DNS records.

Monitor DNSSEC Status: Regularly monitor the DNSSEC status and logs to ensure it is functioning correctly.

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.

Billing Account Costs Manager (roles/billing.costsManager)

- Manage budgets and view and export cost information of billing accounts (but not pricing information)

Billing Account Viewer (roles/billing.viewer)

- View billing account cost information and transactions.

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.

Compute Engine doesn't automatically update the OS or the software on your deployed instances. You will need to patch or update your deployed Compute Engine instances when necessary. However, in the cloud it is not recommended that you patch or update individual running instances. Instead it is best to patch the image that was used to launch the instance and then replace each affected instance with a new copy.

Objective: Ensure only front-end Compute Engine instances have public IPs, while others do not.

Solution: Use an organization policy to enforce this requirement.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Organization Policies page.

Step 3: Create a new policy with the constraint constraints/compute.requireOsLogin (or similar constraint to manage public IPs).

Step 4: Define the conditions to allow public IPs only for the front-end instances.

Step 5: Apply the policy to the organization or specific projects as necessary.

By setting up an organization policy with specific conditions, you can control which instances are allowed to have public IPs based on their role or other attributes.

To ensure compliance with strict regulatory requirements for storing and processing sensitive patient data in the cloud, the following measures should be implemented:​

Assured Workloads: Deploying an Assured Workloads environment in an approved region ensures that data residency requirements are met by restricting data storage and processing to specific geographic locations. Assured Workloads provide predefined controls and configurations tailored to meet regulatory compliance needs.​

Access Approval: Configuring Access Approval ensures that certain administrative actions on patient data require explicit approval from designated compliance officers. This adds a layer of control over sensitive operations, aligning with the need for explicit approvals.​

Cloud Audit Logs and Access Transparency: Enabling Cloud Audit Logs provides a detailed record of actions taken on your data, supporting the requirement for auditability. Access Transparency logs offer visibility into Google's administrative access to your content, enhancing transparency and compliance.​

Therefore, Option C is the most appropriate choice, as it comprehensively addresses data residency, administrative control, and auditability requirements.​

MACsec (Media Access Control Security) relies on a shared secret (a pre-shared key, made up of a Connectivity Key Name, CKN, and Connectivity Association Key, CAK) to establish a secure session between the two endpoints. If the session is "operationally down," it indicates a cryptographic mismatch.

Extracts:

"MACsec is operationally down on my Cloud Interconnect connection... The issue could be caused by one of the following: The active keys on your on-premises router and Google's edge routers don't match." (Source 3.1)

The troubleshooting guide further specifies checking that the "active CKN, CAK, and start times on your on-premises router match the values that MACsec for Cloud Interconnect displays." (Source 3.1)

Therefore, the primary and most common step to resolve a "MACsec is operationally down" status is to verify that the cryptographic keys (the pre-shared key) are correctly configured and match on both the on-premises and Google Cloud routers.

Enable Firewall Rules Logging on the latest rules that were changed. Use Logs Explorer to analyze whether the rules are working correctly:

Enable Firewall Rules Logging for the specific firewall rules in question through the Google Cloud Console.

Once logging is enabled, use Logs Explorer to filter and review the firewall logs.

Analyze the logs to determine if the rules are allowing or blocking traffic as intended, identifying any misconfigurations or issues.

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 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

Access approval Explicitly approve access to your data or configurations on Google Cloud. Access Approval requests, when combined with Access Transparency logs, can be used to audit an end-to-end chain from support ticket to access request to approval, to eventual access.

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

VM Manager is a suite of tools that can be used to manage operating systems for large virtual machine (VM) fleets running Windows and Linux on Compute Engine. It helps drive efficiency through automation and reduces the operational burden of maintaining these VM fleets. VM Manager includes several services such as OS patch management, OS inventory management, and OS configuration management. By using VM Manager, you can apply patches, collect operating system information, and install, remove, or auto-update software packages. The suite provides a high level of control and automation for managing large VM fleets on Google Cloud.

Assured Workloads for Google Cloud allows you to deploy regulated workloads with data residency, access, and support requirements. It helps you configure your environment in a manner that aligns with specific compliance frameworks and standards.

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

To comply with FIPS 140-2 for the messaging app, you need to ensure that both data at rest and data in transit are encrypted according to the standard. Using customer-managed encryption keys (CMEK) ensures that you have control over the encryption keys, and BoringSSL is a library that meets FIPS 140-2 standards for encrypting data in transit.

Steps:

Encrypt Local SSDs: Modify the instance template for the Managed Instance Group (MIG) to use customer-managed encryption keys (CMEK) for encrypting Local SSDs.

Enable BoringSSL: Update the application to use the BoringSSL library for all instance-to-instance communication to ensure that all data in transit is encrypted according to FIPS 140-2 standards.

To ensure that application teams can only add users from within your organization to their groups, you need to configure the group settings in the Google Workspace Admin console. Here are the steps:

Access Google Workspace Admin Console:

Go to the Google Workspace Admin console.

Navigate to the Groups section.

Configure Group Settings:

Select the relevant groups used by the application teams.

Go to the group settings and set the group to only allow members from your domain.

This prevents external users from being added to these groups.

Apply and Save Changes:

Apply the changes to ensure that only users from within your organization can be added to these groups.

Verify Configuration:

Test the configuration by attempting to add an external user to the group and verifying that it is not allowed.

Benefits:

Security: Prevents unauthorized access by ensuring that only internal users can be added to groups.

Compliance: Helps in adhering to organizational policies regarding user access and management.

References

Google Workspace Admin Help: Groups

A service account represents an identity associated with an instance. Only one service account can be associated with an instance. You control access to the service account by controlling the grant of the Service Account User role for other IAM principals. For an IAM principal to start an instance by using a service account, that principal must have the Service Account User role to at least use that service account and appropriate permissions to create instances (for example, having the Compute Engine Instance Admin role to the project).

Objective: Ensure that the analytics workload on Compute Engine instances accessing Cloud Storage does not interact with the public internet.

Solution:

Private Google Access: This allows Compute Engine instances that only have internal IP addresses to reach Google APIs and services through a private connection without the need for a public IP address.

No Public IP Addresses: By avoiding public IP addresses for the instances, you ensure that they are not accessible from the internet and do not initiate internet connections.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the VPC Network page and select the subnet where the Compute Engine instances are located.

Step 3: Enable Private Google Access for the subnet.

Step 4: Ensure that when launching the Compute Engine instances, no public IP addresses are assigned to them.