Google Professional-Cloud-Security-Engineer Google Cloud Certified - Professional Cloud Security Engineer Exam Practice Test

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

Grant logging.admin Role to the Security Team:

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

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

Grant logging.viewer Role to the Developer Team:

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

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

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

IAM Roles for Cloud Logging

Resource Hierarchy in Google Cloud

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

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

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the VPC Service Controls page.

Step 3: Create a new service perimeter.

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

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

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

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

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.

https://cloud.google.com/compute/docs/vm-manager

Set the Resource Location Restriction organization policy constraint at the Folder level:

Setting the constraint at the folder level allows for very granular control over data residency requirements.

Each folder can represent a specific geographical location, and projects within those folders will inherit the location constraint, ensuring compliance with regulatory requirements.

This approach provides flexibility to manage data residency across different regions within the same organization.

SSO/SAML Integration: Implement SSO (Single Sign-On) with SAML integration through Cloud Identity to streamline user authentication and lifecycle management. This ensures centralized management of user identities and access.

Predefined Roles: Use predefined roles to provide granular access control. These roles are designed to follow the principle of least privilege, ensuring that users have the minimum necessary permissions to perform their tasks.

User Management: By leveraging SSO/SAML, user provisioning and de-provisioning become more efficient and secure. This integration helps maintain consistent access policies across your organization.

Access Control: Predefined roles reduce the risk of over-permission by offering well-defined access levels, enhancing security and compliance. References:

Google Cloud - SSO with SAML

Google Cloud - IAM Best Practices

"The service evaluates all changes and remote access attempts to detect runtime attacks in near-real time." : https://cloud.google.com/security-command-center/docs/concepts-container-threat-detection-overview This has nothing to do with KNOWN security Vulns in images

"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."

Configure Binary Authorization:

Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on GKE. It uses attestations to verify the authenticity and integrity of the images.

Enable Binary Authorization in your project through the Google Cloud Console or using the gcloud command-line tool.

Define attestation policies that specify which attestors (trusted entities) must sign off on container images before deployment.

Set Up Attestors:

Create and configure attestors that will sign the container images. This involves generating cryptographic keys and setting up trusted authorities.

Attestors can be configured to sign images based on criteria such as vulnerability scanning results, compliance checks, and other security policies.

Create a Custom Organization Policy Constraint:

Define an organization policy constraint that enforces Binary Authorization across your GKE clusters.

This custom constraint ensures that all clusters in the organization must adhere to the Binary Authorization policy, preventing the deployment of unsigned or unauthorized container images.

Implement and Enforce the Policies:

Apply the Binary Authorization policy and the organization policy constraint to your GKE clusters.

Regularly review and update the policies and attestation rules to align with your security and compliance requirements.

When integrating applications that require access to sensitive data stored in Cloud Storage, managing service account keys securely is crucial to prevent unauthorized access or data loss.​

Option A: Defining a VPC Service Controls perimeter enhances security by restricting access to Google Cloud services. However, configuring ingress rules to allow external access for the service account may introduce complexities and potential security gaps, especially if the partner's infrastructure is outside the defined perimeter.​

Option B: Scanning and masking customer data addresses data sensitivity but does not mitigate risks associated with compromised service account keys. This approach focuses on data content rather than access control mechanisms.​

Option C: Encrypting data at rest using customer-managed encryption keys (CMEK) ensures data confidentiality but does not directly address the security of service account keys or access controls.​

Option D: Implementing a secret management service to handle service account keys is a best practice. By configuring the service to frequently rotate keys, you reduce the window of opportunity for malicious actors to exploit compromised keys. Additionally, enforcing strict access controls ensures that only authorized personnel can create or manage service account keys, minimizing the risk of unauthorized access. This approach directly addresses the security concerns related to service account key management.​

Therefore, Option D is the most appropriate recommendation, as it focuses on securely managing service account keys through rotation and access controls, thereby minimizing the risk of data loss due to compromised keys.​

https://cloud.google.com/vpc/docs/packet-mirroring

Packet Mirroring clones the traffic of specified instances in your Virtual Private Cloud (VPC) network and forwards it for examination. Packet Mirroring captures all traffic and packet data, including payloads and headers.

Enable automatic key version rotation on a regular schedule:

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

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

Limit the number of messages encrypted with each key version:

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

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

Comprehensive and Detailed Explanation From Exact Extract:

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)

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

Steps:

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

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

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

Comprehensive and Detailed Explanation From Exact Extract: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)

Comprehensive and Detailed Explanation From Exact Extract:

The immediate goal is to improve password security and enforce the change due to a recent event. This is done through the Google Workspace Admin console, which controls the identity provider for Google Cloud users.

Improve Password Security: The most effective control is to Enforce strong password policy, which requires users to use long, complex, and unguessable passwords, addressing the core security weakness.

Immediate Enforcement: Checking the option to Enforce password policy at the next sign-in ensures that all current users are immediately prompted to change their weak passwords to ones that meet the new strong policy requirements.

Option C is based on the outdated security practice of frequent password expiration, which often leads to users choosing weaker, predictable passwords (e.g., Spring2025 -> Summer2025). The modern recommendation is strong passwords and multi-factor authentication, not frequent expiration.

Option A is a detective control, not a preventative measure to improve password strength.

Extracts:

"In the Google Workspace Admin console, you can require users to use passwords that meet a strong password policy. A strong password must meet minimum complexity requirements, such as a minimum length and a mix of characters." (Source 6.1)

"After changing the password policy, you can select the option to Require all users to change their password at the next sign-in. This is the fastest way to enforce the new policy immediately across the organization." (Source 6.2)

"Google Cloud's recommended security best practice for identity is to prioritize strong passwords and Multi-Factor Authentication (MFA) over frequent password expiry." (Source 6.3)

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.

Comprehensive and Detailed Explanation From Exact Extract:

The requirements are a combination of preventative and detective controls (prevent and detect misconfigurations) applied at the Folder level to meet both industry-specific (predefined standards) and internal/custom policies. The dedicated Google Cloud feature for this is Security Posture Management in Security Command Center (SCC).

Postures and Enforcement: A Security Posture is a feature within SCC Premium/Enterprise that allows you to define, deploy, and monitor the security status of your cloud assets. You can deploy postures at the organization, folder, or project level to enforce standards.

Custom and Predefined Policies: A posture combines both:

Predefined Policies: Using Security Health Analytics (SHA) detectors and mapped standards (like CIS, ISO 27001, PCI DSS) covers the industry-specific compliance requirements (detection).

Custom Policies: Using custom Organization Policy constraints and custom SHA modules allows you to enforce and detect your internal company policies (prevention and detection).

Extracts:

"In Google Cloud, you can use the security posture service in Security Command Center to define and deploy a security posture, monitor the security status of your Google Cloud resources..." (Source 2.3)

"You can deploy postures at the organization level, folder level, or project level." (Source 2.3)

"The security posture service includes the following components: Posture. One or more policy sets that enforce the preventative and detective controls that your organization requires to meet its security standard... Supported policies are the following: Organization Policy constraints, including custom constraints [Preventative]. Security Health Analytics detectors, including custom modules [Detective]." (Source 2.3, 8.2)

Option C correctly identifies the comprehensive solution for both prevention and detection using a Posture file, which supports custom and predefined policies enforced at the required scope (folder).

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

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

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

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

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

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

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

Implementation Steps:

Obtain an SSL certificate.

Configure the L7 Load Balancer in the GCP Console.

Associate the SSL certificate with the load balancer.

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

Google Cloud Load Balancing Documentation

Setting up HTTPS Load Balancing

”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.

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

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

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

When dealing with VPC Service Controls (VPC SC), it's important to ensure that only authorized resources can access sensitive data and services. To allow a resource in Project B to access Pub/Sub in Project A without compromising security, you should configure an ingress policy for the service perimeter in Project A.

Identify the Service Account: Determine the service account in Project B that requires access to the Pub/Sub topic in Project A.

Configure Ingress Policy:

Go to the Google Cloud Console.

Navigate to Security > VPC Service Controls.

Select the service perimeter for Project A.

Add an ingress rule specifying the service account from Project B and allowing it access to the necessary Pub/Sub resources.

Define Conditions: Ensure that the ingress policy adheres to the principle of least privilege, granting only the necessary permissions to collect messages from the Pub/Sub topic.

Save and Apply: Save the policy and apply the changes to enforce the new access controls.

This approach maintains the security boundaries set by VPC SC while enabling the required access from Project B to Project A.

VPC Service Controls Documentation

Configuring Ingress Policies

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

The problem has two key requirements:

All applications must send data to a centralized security service.

Developers need high autonomy over firewall rules within their projects.

Prevent accidental blockage of access to the central security service.

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

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

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

Let's evaluate the other options:

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

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

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

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

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.

Comprehensive and Detailed Explanation From Exact Extract:

The critical requirements are:

De-identify PII (protect individual privacy).

Retain original format and consistency (analytical integrity).

Avoid full irreversible deletion (the process must be reversible/re-identifiable).

Sensitive Data Protection (SDP), also known as Cloud DLP, is Google Cloud's specialized service for discovering, classifying, and de-identifying sensitive data. The specific de-identification technique that meets the need to retain the original format and consistency is Format-Preserving Encryption (FPE).

Extracts:

"Sensitive Data Protection supports several types of tokenization, including transformations that can be reversed, or 're-identified.'" (Source 5.3)

"Pseudonymization by replacing with cryptographic format preserving token (CryptoReplaceFfxFpeConfig)... Preserves format... Reversible transformations can be reversed to re-identify the sensitive data using the content.reidentify method." (Source 5.3)

"Format Preserving Encryption (FPE) is an encryption algorithm that preserves the format of the original data set, but it replaces it with tokens that have no inherent meaning or value... FPE ensures the ciphertext maintains the same format (length, number of hyphens, etc.) as the original plaintext." (Source 5.1)

FPE is necessary for analytical integrity when the structure/format (e.g., 9-digit SSN, 16-digit credit card number) is required for processing in downstream systems.

Challenge:

Ensuring secure access to Google Cloud resources from GitHub Actions CI/CD pipelines without directly managing service account keys.

Workload Identity Federation:

Allows for the delegation of access to Google Cloud resources based on federated identities, such as those from GitHub.

Benefits:

This approach eliminates the need to manage service account keys, reducing the risk of key leakage.

It leverages GitHub's identity provider capabilities to authenticate and authorize access.

Steps to Configure Workload Identity Federation:

Step 1: Create a workload identity pool in Google Cloud.

Step 2: Add GitHub as an identity provider within the pool.

Step 3: Configure the necessary permissions and bindings for the identity pool to allow GitHub Actions to access Google Cloud resources.

Step 4: Update the GitHub Actions workflow to use the identity federation for authentication.

Managing IAM permissions at the KeyRing level is more efficient and scalable compared to managing them at the individual Key level. By creating a single KeyRing and placing all encryption keys within it, you can apply uniform IAM permissions to the entire KeyRing, simplifying the management of permissions.

Steps:

Create a KeyRing: Set up a single KeyRing in Cloud KMS for all the encryption keys required for the persistent disks.

Create Encryption Keys: Generate the necessary encryption keys within this KeyRing.

Set IAM Permissions: Assign IAM roles and permissions to the KeyRing to manage access control at this level, ensuring that all keys within the KeyRing inherit these permissions.

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.

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.

Comprehensive and Detailed Explanation From Exact Extract:

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)

Comprehensive and Detailed Explanation From Exact Extract:Layer 7 attacks like XSS and SQL injection are application-level threats that require a Web Application Firewall (WAF) for protection. Google Cloud Armor provides this functionality, integrated with the load balancer.

Cloud Armor: Google Cloud's distributed denial-of-service (DDoS) and WAF service.

WAF Rules: Cloud Armor offers pre-configured OWASP Top 10 rules, which directly defend against XSS, SQL injection, and other common application vulnerabilities.

Deployment: Cloud Armor security policies are applied to a backend service that is behind an external HTTP(S) Load Balancer.

Extracts:

"Cloud Armor WAF capabilities help protect web applications from the OWASP Top 10 vulnerabilities... This includes rulesets specifically designed to detect and mitigate SQL injection (SQLi) and cross-site scripting (XSS) attacks." (Source 4.1)

"Cloud Armor security policies are implemented at the edge of the Google Cloud network, applied to the backend services of an external HTTP(S) Load Balancer." (Source 4.2)

Option A is close but incomplete; WAF rules are implemented via a security policy (Option D). Option B relies on Adaptive Protection, which is primarily for volumetric DDoS and advanced attacks, but the direct protection for known XSS/SQLi signatures comes from explicit WAF rules.

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.

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.

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

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 handle PII data ingestion and ensure both redaction and re-identification for analytics purposes, you can use Cloud Data Loss Prevention (DLP) with appropriate techniques for masking and encryption.

Cloud Data Loss Prevention (DLP) with Cryptographic Hashing (C):

Use Cloud DLP to apply cryptographic hashing to PII data. Hashing transforms the data into a fixed-length string that is not directly readable, providing a layer of obfuscation. This helps in masking the PII while retaining the ability to verify data integrity.

Cloud Data Loss Prevention (DLP) with Deterministic Encryption using AES-SIV (E):

Apply deterministic encryption using AES-SIV through Cloud DLP. Deterministic encryption ensures that the same input will always produce the same encrypted output, allowing you to re-identify the PII when necessary. This method enables secure encryption while allowing data re-identification for analytics.

By combining these two approaches, you can effectively mask PII for privacy protection and later re-identify it when required for analysis.

References

Cloud Data Loss Prevention Documentation

Data Redaction and Masking Techniques

https://cloud.google.com/vpc/docs/firewalls#service-accounts-vs-tags

https://cloud.google.com/vpc/docs/firewalls#service-accounts-vs-tags

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).

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.​

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

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.

This option directly addresses the needs of the business user who must access curated reports. By creating curated tables in a separate dataset, you can control access to specific data. Assigning the roles/bigquery.dataViewer role allows the business user to view the data in BigQuery.

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.

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

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

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

References

Service Accounts documentation

Organization Policy Service documentation

The problem requires exposing a sensitive AI model endpoint internally (strictly isolated from the internet) to a defined list of projects within the organization.

Internal Exposure and Isolation: An "internal Application Load Balancer" is suitable for exposing services within your VPC network, ensuring they are not accessible from the internet.

Private Service Connect (PSC): This is the key technology for securely and privately exposing services from one VPC network (the service producer, where the model is) to other VPC networks (the service consumers, the defined list of projects) within the same or different organizations. PSC allows consumers to access services using internal IP addresses, with traffic remaining on Google's private network. You can configure a service attachment that points to the internal load balancer, and then permit specific consumer projects to connect to this service attachment.Extract Reference: "Private Service Connect is a capability of Google Cloud networking that allows consumers to access managed services privately from inside their VPC network. Similarly, it allows managed service producers to host these services in their own separate VPC networks and offer a private connection to their consumers." (Google Cloud Documentation: "Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private-service-connect)

Extract Reference: "Private Service Connect endpoints are internal IP addresses in a consumer VPC network that can be directly accessed by clients in that network. Endpoints are created by deploying a forwarding rule that references a service attachment or a bundle of Google APIs." (Google Cloud Documentation: "About Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private-service-connect)

Extract Reference: "Private Service Connect can be used to access managed services that are owned by Google, third-party software as a service (SaaS) companies, or other teams within the consumer's own company. Both published services and Google APIs can be targets of Private Service Connect." (Google Cloud Documentation: "About Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private-service-connect)

Let's evaluate the other options:

A. Shared VPC and central firewall rules: While Shared VPC centralizes network management, it does not provide a direct managed service exposure mechanism like PSC for a model endpoint to specific projects. It's more about sharing subnets and network resources. Administering all firewall rules centrally would also not meet the need for exposing only this specific model to a defined list of projects in a managed, private service pattern.

B. Activate Private Google Access (PGA): Private Google Access allows VMs without external IP addresses to access Google APIs and services (like Cloud Storage, BigQuery, etc.) privately from within their VPC network. It's for consuming Google services, not for exposing custom services hosted in a Google Cloud project to other projects.

D. External Application Load Balancer + Cloud Armor: An "external Application Load Balancer" exposes the service to the internet. While Cloud Armor can restrict access based on IP addresses, it still involves internet exposure, which contradicts the "strictly isolated from the internet" requirement. Restricting to "Google Cloud IP addresses" doesn't guarantee access only to a defined list of projects and still exposes the service externally.

Therefore, creating an internal Application Load Balancer and exposing it via Private Service Connect is the most suitable and secure solution for this scenario.

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

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

Steps:

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

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

Source IP Range: Subnet A's IP range.

Target Tag: "data-tag".

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

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

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

Create a Service Account:

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

Assign Limited Permissions:

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

Grant Service Account User Role:

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

Access Control During Incidents:

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

Automation and Monitoring:

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

Benefits:

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

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

References

Creating and Managing Service Accounts

Service Account User Role

Google Cloud Directory Sync (GCDS): Install and configure GCDS to synchronize your on-premises Active Directory with Google Cloud Identity. This tool helps in maintaining consistency between your local directory and Google Cloud.

IAM Groups: Create IAM groups in Google Cloud with permissions that correspond to your Active Directory groups. This mapping ensures that users inherit the appropriate permissions based on their AD group membership.

Synchronization: Set up regular synchronization schedules to keep the user and group information up-to-date between your on-premises AD and Google Cloud.

Access Management: Use these IAM groups to manage access to Google Cloud resources, ensuring that permissions are applied consistently and securely. This approach leverages existing AD infrastructure for identity management, providing a seamless integration with Google Cloud. References:

Google Cloud - Google Cloud Directory Sync

Google Cloud - IAM Groups

Disable service account key creation You can use the iam.disableServiceAccountKeyCreation boolean constraint to disable the creation of new external service account keys. This allows you to control the use of unmanaged long-term credentials for service accounts. When this constraint is set, user-managed credentials cannot be created for service accounts in projects affected by the constraint. https://cloud.google.com/resource-manager/docs/organization-policy/restricting-service-accounts#example_policy_boolean_constraint

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.​

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

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

References

Resource Location Restriction documentation

GDPR compliance on Google Cloud

Provision a Cloud NAT Instance:

Cloud NAT (Network Address Translation) allows instances without external IP addresses to access the internet securely.

In the Google Cloud Console, navigate to the VPC Network section and select Cloud NAT.

Create a new Cloud NAT configuration, specifying the VPC and region where your Compute Engine VMs are deployed.

Configure Cloud NAT:

Ensure that the Cloud NAT instance is configured to provide outbound internet connectivity for the VMs in your specified subnet.

This setup allows the VMs to access the internet for package updates and external installations without requiring public IP addresses.

Enable Private Google Access:

Private Google Access allows VMs in a subnet to reach Google APIs and services using internal IP addresses.

In the Google Cloud Console, navigate to the VPC Network section and select Subnets.

Edit the subnet used by your Compute Engine VMs and enable Private Google Access.

Update DevOps Scripts:

Ensure that your DevOps scripts are updated to work with the new network configuration.

Test the build process to confirm that the VMs can access necessary resources and complete the build pipeline successfully.

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.

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. https://cloud.google.com/solutions/exporting-stackdriver-logging-for-splunk

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

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

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

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

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

Steps to Implement:

Choose a Minimal Base Image:

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

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

Optimize Container Image:

Remove unnecessary tools and libraries.

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

Regularly Update Base Images:

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

Distroless Images

Best Practices for Building Containers

To ensure user-uploaded comments and product reviews do not include sensitive data before publication, use the Cloud Data Loss Prevention (DLP) API.

Enable DLP API:

Go to the Cloud Console and navigate to APIs & Services > Library.

Search for "Data Loss Prevention API" and enable it.

Configure DLP API:

Create an inspection template specifying the types of sensitive data to detect.

Set up de-identification templates if you want to redact or mask sensitive data.

Implement DLP in Application:

Use the Google Cloud DLP Client Library for the desired programming language.

Send the text data to the DLP API for inspection before saving or publishing.

from google.cloud import dlp_v2 dlp_client = dlp_v2.DlpServiceClient() parent = f"projects/{project_id}" item = {"value": "User comment text here"} inspect_config = {"info_types": [{"name": "PERSON_NAME"}, {"name": "CREDIT_CARD_NUMBER"}]} response = dlp_client.inspect_content(parent=parent, inspect_config=inspect_config, item=item)

Cloud Data Loss Prevention API Documentation

DLP API Client Libraries

Objective: Store and retrieve sensitive configuration data for an application running on Compute Engine.

Solution: Use Secret Manager to securely store and manage access to sensitive configuration data.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Secret Manager section.

Step 3: Create a new secret and add the sensitive configuration data.

Step 4: Set appropriate IAM policies to control access to the secret.

Step 5: Update the application to retrieve the secret from Secret Manager using the appropriate client libraries or APIs.

Secret Manager provides a secure and centralized way to manage sensitive information, with fine-grained access control and audit logging capabilities.

This is a Customer-supplied encryption keys (CSEK). We generate our own encryption key and manage it on-premises. A KEK never leaves Cloud KMS.There is no KEK or KMS on-premises. Encryption at rest by default, with various key management options https://cloud.google.com/security/encryption-at-rest

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

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

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

Google Cloud - Best Practices for Securing Cloud Identity

Google Cloud - Using Security Keys

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.

Google Cloud Identity Administration

Google Support for Domain Issues

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

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

Comprehensive and Detailed Explanation From Exact Extract:

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

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

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

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

Extracts:

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

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

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

The problem requires granting an external partner team access solely to a database, without extending to other network resources, and following Google-recommended practices.

Workforce Identity Federation: This Google Cloud IAM feature is specifically designed for scenarios where an organization needs to grant Google Cloud access to external identities (like partners, contractors, or customers) who are managed by their own identity provider (IdP). It allows these external users to authenticate using their existing credentials and then gain access to specified Google Cloud resources.

Extract Reference: "Workforce Identity Federation lets you use an external identity provider (IdP) to authenticate and authorize a workforce—a group of users, such as employees, partners, and contractors—using IAM, so that the users can access Google Cloud services." (Google Cloud Documentation: "Workforce Identity Federation | IAM Documentation" - https://cloud.google.com/iam/docs/workforce-identity-federation)

Extract Reference: "Secure access for partners and vendors. Workforce Identity Federation can enable enterprises to selectively federate users from partner or vendor IdPs without requiring IT teams to sync or create a separate identity store to use Google Cloud resources." (Google Cloud Documentation: "Introducing Workforce Identity Federation..." - https://www.azalio.io/introducing-workforce-identity-federation-to-easily-manage-workforce-access-to-google-cloud/)

Least Privilege and Isolation: With Workforce Identity Federation, you create an identity pool and a provider that trusts the partner's IdP. You then grant IAM roles only to the workforce pool (or specific identities within it) on the specific database resource. This ensures fine-grained access control and prevents access to other resources in your network, directly addressing the least privilege and isolation requirements. The partner's identities are never synced into your internal Cloud Identity directory.

Let's evaluate the other options:

A. Add a public IP address... Securely distribute credentials: Adding a public IP address exposes the database to the internet, which is a major security risk and contradicts "restricted solely to the database and can not extend to any other resources within your company's network" as it allows any external network to potentially reach it. Distributing credentials manually is also not a Google-recommended secure practice.

B. Create accounts for the partner team in your corporate identity provider. Synchronize these accounts with Google Cloud Identity: This means you become responsible for managing the partner's identities within your own corporate IdP and syncing them. This is an unnecessary operational burden and blurs the lines of identity management. It also may inadvertently grant them broader network access if your corporate IdP is connected to your internal network resources.

C. Ask the partner team to set up Cloud Identity accounts within their own corporate environment and identity provider. Grant the partner’s Cloud Identity accounts access: While better than B, this implies the partner managing Cloud Identity accounts themselves and you directly granting IAM roles to their Cloud Identity users. Workforce Identity Federation is a more robust and scalable solution for federating any external IdP with Google Cloud IAM, rather than requiring partners to adopt Cloud Identity directly. Workforce Identity Federation is the explicit pattern for cross-organization access using existing external IdPs.

Therefore, Workforce Identity Federation is the most secure, scalable, and Google-recommended solution for granting restricted access to external partner teams.

Objective: Identify the layers of the stack the customer shares responsibility for in a shared security responsibility model for IaaS.

Solution: Understand the shared responsibility model.

Explanation:

Network Security: Customers are responsible for configuring network security, such as setting up firewalls, managing VPCs, and ensuring secure network traffic.

Access Policies: Customers are responsible for managing access policies, including IAM roles and permissions, to ensure only authorized users can access resources.

In IaaS, the cloud provider is typically responsible for the underlying infrastructure, while the customer is responsible for securing their applications and data on the cloud.

Comprehensive and Detailed Explanation From Exact Extract:The requirement to log access by Google personnel (e.g., Google administrators or support) is the specific function of Access Transparency.

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

Extracts:

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

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

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

https://cloud.google.com/vpc/docs/private-service-connect

An API bundle:

All APIs (all-apis): most Google APIs

(same as private.googleapis.com).

VPC-SC (vpc-sc): APIs that VPC Service Controls supports

(same as restricted.googleapis.com).

VMs in the same VPC network as the endpoint (all regions)

On-premises systems that are connected to the VPC network that contains the endpoint

Comprehensive and Detailed Explanation From Exact Extract:

The requirement is to establish a network security boundary around a specific service (BigQuery) for resources in a Folder, while allowing the team to manage that boundary. This is the definition of using VPC Service Controls (VPC SC) with scoped policies.

VPC Service Controls (VPC SC): Used to create a service perimeter (a security boundary) around BigQuery and other Google Cloud services, which restricts API access.

Scoped Policy on the Folder: This enforces the boundary exactly at the required Folder level, as opposed to the organization level.

Access Context Manager Editor Role: Access Context Manager is the service that manages VPC SC policies (Service Perimeters and Access Levels). Granting this role on the scoped policy allows the data analytics team to fulfill the requirement to "control the restrictions."

Extracts (Conceptual Basis for VPC SC and Scoped Policies):

"Private Service Connect provides... Explicit authorization. Private Service Connect provides an authorization model that gives consumers and producers granular control, ensuring that only the intended service endpoints and no other resources can connect to a service." (Source 2.4 - VPC SC and PSC share a core architectural concept of explicit, service-oriented boundaries)

Option B is the technical implementation that matches the requirements: using a VPC SC service perimeter (for service restriction) applied as a scoped policy on the folder (for resource hierarchy scope) with Access Context Manager Editor (for team management/control).

To ensure that PII data is separated from non-PII data, using Cloud Pub/Sub and Cloud Functions to trigger a scan by the Data Loss Prevention (DLP) API is an effective approach. This method allows for automated detection and handling of PII.

Steps:

Set Up Cloud Pub/Sub: Configure a Cloud Pub/Sub topic to receive notifications whenever a file is uploaded to the shared Cloud Storage bucket.

Deploy Cloud Functions: Create a Cloud Function that is triggered by the Pub/Sub topic. This function will invoke the DLP API to scan the uploaded file for PII.

Move Detected PII Files: If the scan detects PII, the Cloud Function will move the file to a secure Cloud Storage bucket accessible only by the administrator.

Set Permissions: Ensure that appropriate permissions are set on the Cloud Storage buckets to restrict access to files containing PII.

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 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

The goal is to detect cryptocurrency mining software using Security Command Center (SCC).

Security Command Center Threat Detection Services: SCC Premium and Enterprise tiers offer various specialized threat detection services.

Virtual Machine Threat Detection (VMTD): This service is explicitly designed to scan virtual machines (Compute Engine instances and GKE nodes) for specific threats, including cryptocurrency mining software. It operates at the hypervisor level, performing deep scans of VM memory and disks.Extract Reference: "Virtual Machine Threat Detection (VMTD) helps you detect potential threats, such as cryptocurrency mining and malware, within your Compute Engine instances and GKE nodes." (Google Cloud Documentation: "Virtual Machine Threat Detection overview | Security Command Center" - https://cloud.google.com/security-command-center/docs/concepts-vm-threat-detection-overview)

Extract Reference: "This service scans virtual machines to detect potentially malicious applications, such as cryptocurrency mining software, kernel-mode rootkits, and malware running in compromised cloud environments." (Google Cloud Documentation: "Virtual Machine Threat Detection overview | Security Command Center" - https://cloud.google.com/security-command-center/docs/concepts-vm-threat-detection-overview)

Let's evaluate the other options:

A. Web Security Scanner: This service scans for common web application vulnerabilities like XSS, Flash injection, and mixed content. It is not designed to detect runtime threats like cryptocurrency mining software.

B. Container Threat Detection: While Container Threat Detection (CTD) also detects cryptocurrency mining, it specifically focuses on runtime threats within GKE containers. The question asks for detection of "cryptocurrency mining software" generally, and VMs are a common target for such activity (and GKE nodes are VMs). VMTD provides a more general detection across Compute Engine VMs and GKE nodes for this specific type of threat. If the context explicitly mentioned containers or Cloud Run, CTD would be the more specific answer. However, for a general detection of "software" on "workloads", and given that VMTD explicitly lists "cryptocurrency mining software" for VMs, it is the most direct and broadly applicable answer among the choices.

C. Rapid Vulnerability Detection: This service actively scans internet-exposed assets for network vulnerabilities and misconfigurations. It focuses on finding known vulnerabilities, not detecting active malicious processes like cryptocurrency mining.

Given the direct and explicit mention of cryptocurrency mining detection for VMs in its documentation, Virtual Machine Threat Detection is the correct SCC service to use.

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

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

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.

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

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

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

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

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

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

References

Titan Security Keys

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