Professional-Cloud-Security-Engineer Google Cloud Certified - Professional Cloud Security Engineer Questions and Answers

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.

To ensure that your organization’s record data is retained for at least seven years in Cloud Storage, you need to apply a retention policy and enable bucket lock. This prevents the policy from being altered or the data from being deleted before the retention period ends.

Identify Buckets: Determine which Cloud Storage buckets contain the record data that needs to be retained.

Apply Retention Policy:

Go to the Google Cloud Console and navigate to "Cloud Storage".

Select the bucket you identified.

Go to the "Retention" tab and set a retention policy to retain objects for seven years.

Enable Bucket Lock:

Once the retention policy is set, you need to lock the bucket to make the retention policy permanent.

This is done by enabling the bucket lock. Go to the "Retention" tab and click "Lock".

Confirm and Monitor:

Confirm that the bucket lock is applied.

Monitor the bucket using log-based alerts to ensure compliance.

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

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.​

The Resource Location Restriction organization policy constraint ensures that business data is stored in specific geographic locations, which is critical for compliance with regulatory requirements.

Organization Level: Setting the constraint at the organization level ensures that all resources within the organization, including those in different folders or projects, adhere to the location restrictions. This provides a unified policy application across the entire organization, ensuring compliance with regulatory requirements.

Policy Application: The policy will propagate down the resource hierarchy, ensuring that all relevant services within the organization comply with the specified data residency requirements.

This approach provides centralized control and simplifies the management of data residency constraints.

References

Organization Policy Service Documentation

https://cloud.google.co m/load-balancing/docs/tcp

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. https://cloud.google.com/load-balancing/docs/load-balancing-overview#tcp-proxy-load-balancing

"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."

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.

https://cloud.google.com/architecture/best-practices-vpc-design#l7

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.

Use Cloud Data Loss Prevention (DLP) with cryptographic hashing:

Cloud DLP allows you to de-identify sensitive data using several techniques, including cryptographic hashing.

Choose a suitable hashing algorithm like SHA-256 for non-reversible anonymization.

This method converts the original data into a fixed-length hash that does not preserve the original data's format or character set.

Set up a Cloud DLP job to scan your data sources, identify PHI, and apply the cryptographic hashing transformation.

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.

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

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

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

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.

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

Steps:

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

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

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

By generating a key in your on-premises environment and storing it in an HSM that you manage, you're ensuring that the key material is fully under your control. Using the key as an external key in Cloud KMS allows you to use the key with Google Cloud services without having the key stored on Google Cloud. Activating Key Access Justifications (KAJ) provides a reason every time the key is accessed, and you can configure the external key system to reject unauthorized access attempts.

Firewall Rule Analysis: Analyze the existing VPC firewall rules to identify any rules that might allow traffic between VM instances based on the same service account.

Priority Check: Check the priority of these rules. A rule with a priority lower than 1000 (such as 999) will take precedence over your tag-based rules.

Service Account Configuration: Since your VM instances are deployed without any service account customization, they are likely using the default service account. A firewall rule allowing traffic between instances using this default service account will override the tag-based rules if it has a higher priority.

Testing and Validation: Disable or adjust the priority of the rule with priority 999 to test if the tag-based segmentation works correctly. Validate that the traffic is segmented according to your intended configuration. References:

Google Cloud - VPC Firewall Rules

Google Cloud - Service Accounts

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

Steps to access and use the document:

Access the Document:

Go to the Google Cloud compliance resource center.

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

Review Inherent Controls:

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

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

Analyze PCI Compliance:

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

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

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

The problem requires restricting admin access to Google Cloud APIs based on geographic location (Canada and Germany) and environment (development and production projects).

VPC Service Controls (VPC SC): VPC Service Controls is designed to create security perimeters around Google Cloud resources and services. Its primary purpose is to prevent data exfiltration and control access to Google Cloud APIs based on the context of the request, which includes the source IP address.

Extract Reference: "VPC Service Controls provides an extra layer of security defense for Google Cloud services that is independent of Identity and Access Management (IAM). While IAM enables granular identity-based access control, VPC Service Controls enables broader context-based perimeter security, including controlling data egress across the perimeter." (Google Cloud Documentation: "Overview of VPC Service Controls" - https://cloud.google.com/vpc-service-controls/docs/overview)

Service Perimeters for Environments: Creating dedicated perimeters for development and production projects allows for logical separation of environments, which aligns with the "dedicated projects for development and production" structure.

Ingress Policies with Geographic Restrictions: VPC Service Controls uses "ingress rules" to define who and from where requests can enter a service perimeter. These ingress rules can be configured to allow access based on various attributes, including the source IP address of the request. By allowing access from specific IP ranges corresponding to Canada and Germany, you effectively restrict administrative access to APIs from those countries. You can define "access levels" (which can include IP subnets or geographical origins) and attach them to ingress policies.

Extract Reference: "To allow ingress to resources, VPC Service Controls evaluates sources and identityType attributes as an AND condition... You must specify an accessLevel or a resource (Google Cloud project or VPC network), or set accessLevel attribute to *." (Google Cloud Documentation: "Ingress and egress rules | VPC Service Controls" - https://cloud.google.com/vpc-service-controls/docs/ingress-egress-rules)

Extract Reference (for Context-Aware Access which underpins access levels): "You can create different types of Context-Aware Access policies for accessing apps: IP, device, geographic origin, and custom access-level attributes." (Google Workspace Admin Help: "Protect your business with Context-Aware Access" - https://support.google.com/a/answer/9275380) - While this references Workspace apps, the underlying mechanism of Access Context Manager (used by VPC SC) supports geographic restrictions.

Let's evaluate the other options:

A. Create dedicated firewall policies... restrict access based on geolocations: VPC firewall rules operate at the network level (Layers 3/4) within a VPC. They control traffic between VM instances or to/from the internet for network services. They do not directly control admin access to Google Cloud APIs (e.g., via the console or gcloud CLI calls) originating from outside the VPC.

B. Activate the organization policy on the folders to restrict resource location: The Resource Location Restriction organization policy constraint restricts where new resources can be created or stored (e.g., data residency requirements). It does not restrict where administrators can connect from to manage these resources or access APIs.

D. Create dedicated IAM Groups... Grant access: IAM (Identity and Access Management) controls who can access what resources and what actions they can perform. It does not natively provide control over where the access originates from (e.g., country-specific IP addresses).

Therefore, VPC Service Controls with properly configured ingress policies based on source IP/Access Levels is the recommended and most effective method for restricting admin access to Google Cloud APIs by geographic location and environment.

For a client concerned about the control of their encryption keys and not wanting to store these keys within the same cloud service provider (CSP) as the data, the following solutions are suitable:

Customer-supplied encryption keys (A):

With customer-supplied encryption keys, clients manage their own encryption keys outside of Google Cloud and supply them to encrypt and decrypt data. This ensures that the keys are not stored in Google Cloud, providing full control over the key management process.

Cloud External Key Manager (D):

Cloud External Key Manager (EKM) allows clients to integrate an external key management system (KMS) with Google Cloud services. This setup enables the client to keep their encryption keys outside Google Cloud while still allowing the data to be encrypted and decrypted within Google Cloud services. This method offers an additional layer of security and control over the encryption keys.

These options provide robust solutions for clients requiring external key management and enhanced control over their encryption processes.

References

Customer-Supplied Encryption Keys

Cloud External Key Manager

Objective: Implement external web application protection and validate policy changes before enforcement.

Solution: Use Google Cloud Armor's preconfigured rules in preview mode.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Google Cloud Armor section.

Step 3: Create or select a security policy.

Step 4: Apply preconfigured rules to the policy.

Step 5: Enable preview mode to simulate the effects of the rules without enforcing them.

Step 6: Monitor the logs to validate the policy changes.

Google Cloud Armor's preview mode allows you to test and validate the impact of security policies on your application traffic before applying them, ensuring that they work as intended without disrupting the service.

The Organization Administrator and Super Admin roles have extensive administrative privileges at the organization level. Restricting these roles is crucial to limit the number of users who have the ability to manage critical resources and configurations within the organization, thereby enhancing security and minimizing potential risks.

Organization Administrator: Has comprehensive permissions to manage all aspects of the Google Cloud organization, including projects, folders, and IAM policies.

Super Admin: In Google Workspace (formerly G Suite), the Super Admin has access to all administrative features and can manage user accounts, services, and settings across the organization.

To enable Engineering Group A to attach a Compute Engine instance to a specific subnet (10.1.1.0/24) in a Shared VPC, you should grant the Compute Network User Role at the subnet level. This role allows users to use the subnetwork for their instances without giving them broader permissions at the project level.

Step-by-Step:

Identify the Subnet: Locate the subnet (10.1.1.0/24) in the host project.

Grant Role:

Navigate to the GCP Console > VPC network > VPC networks.

Select the Shared VPC host project and locate the specific subnet.

Click on "Edit" and go to the "IAM & Admin" section.

Assign the "Compute Network User" role to Engineering Group A at the subnet level.

Verification: Ensure that Engineering Group A can now attach Compute Engine instances to the specified subnet.

To ensure that data is encrypted while in use by the virtual machines (VMs) and enforce this policy across your organization, you should use Confidential VM instances. Here are the steps:

Enable Confidential VM:

Ensure that Confidential VMs are available in your selected regions and enabled for your project.

Set Organization Policy:

Implement an organization policy to enforce the use of Confidential VM instances for all VMs across your organization.

Use the Google Cloud Console or the gcloud command-line tool to set this policy. Example command:

gcloud resource-manager org-policies set-policy my_policy.yaml

Example my_policy.yaml:

name: organizations/1234567890/policies/compute.requireConfidentialCompute spec: rules: - enforce: true

Verify and Monitor:

Ensure that all newly created VMs across your organization are Confidential VMs.

Regularly monitor compliance through the Google Cloud Console and set up alerts if non-compliant VMs are created.

Benefits:

Data Encryption in Use: Confidential VMs ensure that data is encrypted not just at rest and in transit but also while in use.

Policy Enforcement: Organization policies provide a way to enforce security configurations across all projects under your organization.

References

Confidential Computing Documentation

Creating and Managing Organization Policies

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

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

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

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

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

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

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

https://cloud.google.com/resource-manager/docs/organization-policy/org-policy-constraints - 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.

Uniform Bucket-Level Access: Enable uniform bucket-level access for all your Cloud Storage buckets. This feature ensures that access control is applied consistently at the bucket level, simplifying management and improving security.

Domain Restricted Sharing: Enforce domain-restricted sharing through an organization policy. This policy ensures that only users within your organization’s domain can access the data in the buckets, preventing public exposure.

Policy Enforcement: Apply the necessary IAM policies and ensure that no buckets are configured to allow public access. This combination of settings ensures that data in Cloud Storage buckets remains private and accessible only to authorized users within your organization. References:

Google Cloud - Uniform Bucket-Level Access

Google Cloud - Organization Policy Service

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

Solution: Modify IAM roles and permissions.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the IAM & Admin page.

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

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

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

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

Enable Security Command Center (SCC):

SCC provides centralized visibility and control over your cloud resources' security status.

Ensure that SCC is enabled in your Google Cloud environment.

Configure Virtual Machine Threat Detection (VMTD):

VMTD is part of SCC and specializes in detecting threats within VM instances, such as cryptocurrency mining malware.

Navigate to the SCC settings in the Google Cloud Console.

Activate VMTD:

Enable VMTD for the projects or resources where you want to monitor and detect potential threats.

VMTD uses behavioral analysis to identify anomalies indicative of unauthorized mining activities.

Monitor and Respond to Alerts:

VMTD generates alerts when it detects suspicious activities, such as unauthorized cryptocurrency mining.

Set up appropriate response actions, such as notifications, automatic remediation, or manual investigation, to handle these alerts.

The problem requires ensuring that only images that have passed vulnerability scanning and meet corporate policies are allowed to be deployed to GKE, with the process being automated and integrated into the existing CI/CD pipeline.

Binary Authorization: This Google Cloud service is purpose-built to enforce deployment policies on images before they are run on Google Kubernetes Engine (GKE), Cloud Run, and other deployable platforms. It acts as a policy gate that prevents the deployment of non-compliant images.

Extract Reference: "Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE), Cloud Run, and Anthos clusters." and "With Binary Authorization, you can require images to be signed by trusted authorities and enforce validation policies during deployment." (Google Cloud Documentation: "Binary Authorization overview" - https://cloud.google.com/binary-authorization/docs/overview)

Artifact Analysis (part of Container Analysis): Artifact Analysis (which includes Container Analysis) provides vulnerability scanning capabilities for container images stored in Artifact Registry. It generates findings and metadata about vulnerabilities.

Extract Reference: "Container Analysis is a service that scans your images for known vulnerabilities and provides metadata about them." (Google Cloud Documentation: "Overview | Container Analysis" - https://cloud.google.com/container-analysis/docs/overview)

Binary Authorization can be configured to integrate with Artifact Analysis (or other attestors) to check for vulnerability scan results as part of its deployment policy.

Integration and Automation: Binary Authorization policies can require attestations before deployment. An attestation confirms that an image meets specific criteria (e.g., it has passed a vulnerability scan, it was signed by an approved CI/CD process, it adheres to corporate policies). Cloud Build can be configured to generate these attestations after a successful vulnerability scan (using Artifact Analysis). This fully automates the process and integrates directly into the CI/CD pipeline.

Extract Reference: "With Binary Authorization, you create a policy that enforces your requirements. The policy defines rules that govern deployment. For example, a policy can require all images to be signed by a trusted authority before deployment." (Google Cloud Documentation: "Binary Authorization overview" - https://cloud.google.com/binary-authorization/docs/overview)

Let's evaluate the other options:

A. Custom script in Cloud Build... Fail the build: While scanning during the build is good practice (shift-left security), failing the build only prevents the image from being pushed. It doesn't prevent a developer or an automated process from manually deploying an old or non-compliant image that might already exist in Artifact Registry, or from bypassing the build system. The enforcement needs to happen at deployment time.

B. Configure GKE to use only images from a specific... trusted Artifact Registry repository. Manually inspect all images: Manually inspecting images is not automated and does not scale for a "large number of containerized applications." It also doesn't programmatically enforce vulnerability scan results or corporate policies.

D. Enable Artifact Analysis vulnerability scanning and regularly scan images... Remove any images that do not meet... before deployment: This describes scanning and remediation, which are important. However, it's a reactive approach ("remove any images") rather than a proactive enforcement ("only images that... are allowed to be deployed"). There's still a window where a non-compliant image could be deployed before it's removed. Binary Authorization is the enforcement gate.

Therefore, configuring Binary Authorization with a policy that integrates with Artifact Analysis (or requires attestations based on its findings) is the most robust, automated, and Google-recommended solution for enforcing deployment policies based on vulnerability scanning and corporate compliance.

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

Steps:

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

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

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

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.

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

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

"Isolate VMs using service accounts when possible" "even though it is possible to uses tags for target filtering in this manner, we recommend that you use service accounts where possible. Target tags are not access-controlled and can be changed by someone with the instanceAdmin role while VMs are in service. Service accounts are access-controlled, meaning that a specific user must be explicitly authorized to use a service account. There can only be one service account per instance, whereas there can be multiple tags. Also, service accounts assigned to a VM can only be changed when the VM is stopped." https://cloud.google.com/solutions/best-practices-vpc-design#isolate-vms-service-accounts

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.

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

Step-by-Step:

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

Create Folders for Business Units:

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

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

Move Projects to Folders:

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

Set IAM Policies:

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

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

Enable the compute.restrictXpnProjectLienRemoval organization-level policy constraint:

This constraint prevents users from removing liens from Shared VPC host projects.

By enabling this constraint, you ensure that the Shared VPC host project cannot be accidentally deleted, as liens prevent deletion without proper authorization.

Apply this constraint via the Google Cloud Console or using the gcloud command-line tool.

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

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

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

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.

Customer-Managed Encryption Keys (CMEK):

CMEK allows you to manage encryption keys using Cloud Key Management Service (KMS). This gives you control over the lifecycle of the keys, including rotation, destruction, and auditing.

Set up a Cloud KMS key ring and create encryption keys that will be used to protect your data in BigQuery, Cloud SQL, and Cloud Storage.

Configure the services to use CMEK for encrypting data at rest, ensuring compliance with your organization's security policies.

Cloud External Key Manager (EKM):

Cloud EKM allows you to use keys managed by an external key management provider to encrypt data in Google Cloud services.

Integrate your external key management system with Google Cloud using supported protocols and APIs.

Configure your data warehouse services to use the external keys for encryption, ensuring that key management is handled outside of the Google Cloud environment.

Key Access Justifications:

Enable Key Access Justifications to provide visibility into why encryption keys are being accessed. This helps in monitoring and auditing key usage to ensure compliance and security.

Set up policies and logging to capture and review key access requests, providing insights into how and why keys are used.

Access Transparency and Approval:

Implement Access Transparency to gain visibility into Google’s access to your data and encryption keys.

Configure Access Approval to require explicit approval for Google support or engineering access to your data, adding an additional layer of security and control.

This approach allows you to control network traffic at the folder level. By attaching external IP addresses to the VMs in scope, you can ensure that the VMs have a unique, routable IP address for outbound connections. Then, by defining and applying a hierarchical firewall policy at the folder level, you can enforce that egress connections are limited to the specified IP range and only from the specified VPC network.

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

To prepare for migrating Google Cloud projects to a new organization node, it's crucial to ensure that the projects' current configurations and dependencies are appropriately managed. The two necessary preparation steps are:

Identify inherited Identity and Access Management (IAM) roles on projects to be migrated (C):

Projects inherit IAM roles from their parent resources. Identifying these roles is essential to understand the permissions and access levels that users have on the projects. This will help in ensuring that after migration, the appropriate roles and permissions are applied correctly.

Remove the specific migration projects from any VPC Service Controls perimeters and bridges (E):

VPC Service Controls provide security boundaries around your Google Cloud resources to mitigate data exfiltration risks. Before migrating the projects, they need to be removed from any existing VPC Service Controls perimeters and bridges to prevent any disruption in access or network communication. After migration, the projects can be added back to the necessary perimeters.

References

Google Cloud IAM documentation

VPC Service Controls documentation

Packet Mirroring Setup: Configure Packet Mirroring in your Google Cloud VPC to capture traffic to and from specific VM instances. This allows you to analyze the traffic for security and compliance purposes.

Security Software: Use specialized security software to inspect the mirrored traffic. This software can detect invalid or malicious content in the IP packets.

Mirroring Configuration: Specify the instances, network, and traffic direction (ingress, egress, or both) to be mirrored. Ensure that the mirrored traffic is directed to an appropriate analysis destination.

Traffic Analysis: Continuously monitor and analyze the mirrored traffic for any signs of malicious activity or anomalies. Use the findings to enhance your security posture and respond to potential threats. References:

Google Cloud - Packet Mirroring

Google Cloud - Packet Mirroring Best Practices

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Let's evaluate the other options:

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

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

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

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

Objective: Ensure VMs can access Cloud Storage without reaching the public internet.

Solution: Enable Private Google Access on the VPC network, allowing VMs with only internal IP addresses to access Google APIs and services privately.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Go to the VPC Network section.

Step 3: Select the relevant VPC network and subnet.

Step 4: Enable Private Google Access for the subnet.

Private Google Access ensures that instances can access Google APIs and services (such as Cloud Storage) over a private network connection, without requiring a public IP address.

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.

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.

To allow Compute Engine instances to access public repositories for security updates while an egress firewall rule is in place to deny all internet traffic, you need to create a more specific egress rule that permits traffic to the CIDR range of the repository. The priority of this rule should be lower (i.e., a higher priority number) than the deny rule.

Steps:

Identify the CIDR Range: Determine the CIDR range of the public repository from which the security updates will be fetched.

Create Egress Firewall Rule: Create a new egress firewall rule allowing traffic to the identified CIDR range with a priority less than 1000.

Apply Firewall Rule: Use the Google Cloud Console or gcloud command-line tool to apply the new firewall rule.

Objective: Create a Service Account that can list Compute Engine instances in the project following Google-recommended practices.

Solution: Create a custom role and assign it to the Service Account.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the IAM & Admin page and select "Roles".

Step 3: Click on "Create Role" and define a new role with a suitable name and description.

Step 4: Add the permission compute.instances.list to the custom role.

Step 5: Save the custom role.

Step 6: Go to the "Service Accounts" section.

Step 7: Create a new Service Account or select an existing one.

Step 8: Assign the newly created custom role to the Service Account.

By creating a custom role with the specific permission to list Compute Engine instances, you follow the principle of least privilege, which is a recommended security practice.

https://cloud.google.com/load-balancing/docs/ssl - SSL Proxy Load Balancing is a reverse proxy load balancer that distributes SSL traffic coming from the internet to virtual machine (VM) instances in your Google Cloud VPC network.

Cloud Identity-Aware Proxy (IAP) allows you to control access to your web applications running on Google Cloud. It ensures that only authenticated users who are part of a specified Google Group can access the application. Here’s how you can restrict access to in-progress sites using IAP:

Enable IAP: First, you need to enable Cloud IAP for your App Engine application. This will require configuring OAuth consent and setting up necessary permissions.

Create a Google Group: Create a Google Group that includes all the customers and company employees who should have access to the in-progress sites.

Configure Access: Configure IAP to allow access only to members of the created Google Group. This involves setting up the necessary IAP policies and ensuring that only authenticated users in the group can access the application.

By using IAP, you ensure that the access control is centrally managed and only authorized users can view the in-progress sites from any location.

References

Cloud Identity-Aware Proxy Documentation

Setting up IAP

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

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

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

Google Cloud - External HTTP(S) Load Balancer Overview

Google Cloud - Shared VPC Overview

To remove personally identifiable information (PII) from files older than 12 months and archive the anonymized files for retention purposes, you can use Google Cloud Data Loss Prevention (DLP).

Create a Cloud DLP Inspection Job:

Go to the Cloud DLP section in the Google Cloud Console.

Create an inspection job that scans files in your Cloud Storage bucket for PII.

Configure the job to only target files that are older than 12 months.

Configure De-identification:

In the inspection job settings, configure de-identification actions to remove or obfuscate PII in the files.

Specify the transformation techniques appropriate for your data, such as masking or tokenization.

Archive Anonymized Files:

Set up the job to move the de-identified files to another Cloud Storage bucket designated for archival.

Ensure this bucket has the appropriate retention policies and access controls in place.

Delete Original Files:

After de-identification and archiving, configure the job to delete the original files from the source bucket.

This approach ensures that PII is effectively removed from old files and that the anonymized data is securely archived, maintaining compliance with data retention and privacy policies.

Enable Dry Run Mode: Start by enabling the dry run mode for your VPC Service Controls perimeter. This mode allows you to test changes without actually enforcing them, thus preventing any disruption to your current setup.

Add Access Level: Add your new access level to the dry run configuration. This way, you can monitor how the new access level would behave and interact with your existing setup without any real impact.

Vetting Process: Carefully vet the new access level by analyzing logs and monitoring the behavior in the dry run mode. Ensure that the new configuration meets your security and operational requirements.

Update Perimeter: Once you are confident that the new access level will not disrupt existing services and meets all requirements, update the actual perimeter configuration with the new access level. This approach minimizes risk by allowing you to test changes before they take effect, ensuring seamless updates with minimal disruption. References:

Google Cloud - Configuring VPC Service Controls

Google Cloud - Using Dry Run Mode

”This encryption method is reversible, which helps to maintain referential integrity across your database and has no character-set limitations.” https://cloud.google.com/blog/products/identity-security/take-charge-of-your-data-how-tokenization-makes-data-usable-without-sacrificing-privacy

https://cloud.google.com/dlp/docs/pseudonymization

FPE provides fewer security guarantees compared to other deterministic encryption methods such as AES-SIV. For these reasons, Google strongly recommends using deterministic encryption with AES-SIV instead of FPE for all security sensitive use cases. Other methods like deterministic encryption using AES-SIV provide these stronger security guarantees and are recommended for tokenization use cases unless length and character set preservation are strict requirements—for example, for backward compatibility with a legacy data system.

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

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

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

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

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

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

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

Since the domain is already being used by G Suite, the best course of action is to minimize disruption by discovering any existing uses of Google-managed services. Collaborate with the existing Super Administrator to align the setup with the company's requirements.

Step-by-Step:

Identify Existing Usage: Have the customer's management identify all current uses of the domain within Google-managed services.

Collaboration: Work closely with the existing Super Administrator of the domain.

Provision Required Accounts: Ask the Super Administrator to provision necessary accounts and permissions for the data science manager or other relevant personnel.

Integrate SAML IdP: Ensure that the existing domain integrates with the company’s SAML 2.0 IdP for user authentication.

Set Up Cloud Identity: Configure Cloud Identity under the guidance of the Super Administrator without disrupting current services.

To enhance the security of your microservices architecture on Google Kubernetes Engine (GKE) and ensure that only approved container images are deployed, implementing Binary Authorization is a robust solution.​

Option A: Enforcing Binary Authorization in your GKE clusters ensures that only container images that meet your organization's security policies are deployed. By integrating container image vulnerability scanning into your Continuous Integration/Continuous Deployment (CI/CD) pipeline, you can assess images for known vulnerabilities before they are deployed. Binary Authorization can be configured to use these vulnerability scan results to make policy decisions, effectively preventing the deployment of insecure images. This approach leverages managed services provided by Google Cloud, ensuring scalability and compliance with security standards.​

Option B: Developing custom organization policies to restrict deployments to images within a specific Artifact Registry project helps in controlling the source of images but does not inherently assess the security posture of those images. Without integrated vulnerability scanning and enforcement mechanisms, this approach may not fully mitigate the risk of deploying vulnerable images.​

Option C: Building a system using third-party vulnerability databases and custom scripts requires significant maintenance and may not integrate seamlessly with GKE. This approach can be error-prone and lacks the efficiency of managed services designed for this purpose.​

Option D: Automatically deploying new images upon successful CI/CD builds ensures rapid deployment but does not address the need for security assessments of the images. While setting up firewall rules is good practice, it does not prevent the deployment of potentially vulnerable images.​

Therefore, Option A is the most effective approach, as it utilizes Google Cloud's managed services to enforce security policies and integrate vulnerability assessments directly into the deployment process, ensuring that only approved and secure container images are deployed to your GKE clusters.​

"Date shifting techniques randomly shift a set of dates but preserve the sequence and duration of a period of time. Shifting dates is usually done in context to an individual or an entity. That is, each individual's dates are shifted by an amount of time that is unique to that individual."

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.

https://cloud.google.com/vpc-service-controls/docs/overview

Objective: Understand the security characteristics of VPC peering.

Security Characteristics:

Non-transitive Peering: VPC peering connections are non-transitive. This means that peering is strictly between two VPC networks. If VPC A is peered with VPC B, and VPC B is peered with VPC C, VPC A cannot communicate with VPC C unless a direct peering connection is established.

Inter-Organization Peering: VPC peering allows you to connect VPC networks across different Google Cloud Platform organizations, facilitating private communication between distinct organizational units.

These characteristics ensure controlled and secure connectivity between VPC networks while preventing unintended data exposure.

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

Customer-managed encryption keys (B):

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

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

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

References

Customer-Managed Encryption Keys Documentation

Encryption at Rest in Google Cloud

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

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

Objective: Encrypt data using envelope encryption.

Solution: Follow the envelope encryption process.

Steps:

Step 1: Generate a Data Encryption Key (DEK) locally. The DEK is used to encrypt the actual data.

Step 2: Encrypt the data using the DEK.

Step 3: Use a Key Encryption Key (KEK) to wrap the DEK. The KEK is used to encrypt the DEK.

Step 4: Store the encrypted data and the wrapped DEK. This ensures that the data can be securely decrypted in the future using the KEK to unwrap the DEK.

Envelope encryption enhances security by adding an additional layer of encryption to the data encryption key, which is particularly useful for managing large volumes of encrypted data.

To enhance the security of your machine learning (ML) model supply chain within a serverless architecture, it's crucial to implement measures that protect both the development and deployment pipelines.​

Option A: While limiting external dependencies and rotating encryption keys are good security practices, they do not directly address the risks associated with the ML model supply chain.​

Option B: Implementing container image vulnerability scanning during development and pre-deployment helps identify and mitigate known vulnerabilities in your container images. Enforcing Binary Authorization ensures that only trusted and verified images are deployed in your environment. This combination directly strengthens the security of the ML model supply chain by validating the integrity of container images before deployment.​

Option C: Sanitizing training data and applying role-based access controls are important security practices but do not specifically safeguard the deployment pipeline against compromised container images.​

Option D: While strict firewall rules and intrusion detection systems enhance network security, they do not specifically address vulnerabilities within the container images or the deployment process.​

Therefore, Option B is the most effective approach, as it directly addresses the security of the development and deployment pipeline by ensuring that only vetted and secure container images are used in your environment.​

To provide temporary write access to a Cloud Storage bucket with the minimum permissions necessary, you should:

Identify the Compute Engine instance’s default service account: Each Compute Engine instance has a default service account that is used to interact with other Google Cloud services.

Assign the storage.objectCreator role: This predefined IAM role grants permissions to create objects in a Cloud Storage bucket, which is sufficient for temporary write access. It does not grant permissions to read or delete objects, thus adhering to the principle of least privilege.

Avoid using full permissions or long-lived keys: Options A and C suggest using broader permissions than necessary or embedding long-lived keys, which could pose a security risk if compromised.

Service account impersonation (Option D) is not necessary for this task and would be more appropriate for scenarios where you need to assume a different identity with different permissions.

This approach allows you to expose the web interface securely by using Identity-Aware Proxy (IAP), which provides authentication and authorization with Google credentials. The HTTP Load Balancer can distribute traffic to the VMs in the managed group, and the VPC firewall rule ensures that access is allowed from the IAP network range.

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.

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

Steps:

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

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

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

To meet the requirements for exporting and auditing security logs in near real-time for login activity events and API calls:

Organization-Level Log Sink with Pub/Sub: Create a log sink at the organization level to ensure logs from all projects are captured. Use the includeChildren parameter to include logs from all child resources (projects). Set the destination to a Pub/Sub topic to facilitate near real-time log export to an external SIEM.

Enable Data Access Audit Logs: Enable Data Access audit logs at the organization level to capture and export detailed information about API calls that modify configurations of Google Cloud resources across all projects.

These steps ensure comprehensive logging and real-time export capabilities, which are crucial for security auditing and monitoring.

References

Audit Logs Overview

Exporting with Sinks