Google Professional-Cloud-Security-Engineer - Google Cloud Certified - Professional Cloud Security Engineer

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.​

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

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.

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

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

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

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

Let's evaluate the other options:

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

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

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

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

Comprehensive and Detailed Explanation From Exact Extract:

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

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

Extracts:

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

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

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

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

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

Generate a Backup Code (A):

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

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

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

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

References

Google Admin console 2-Step Verification documentation

Comprehensive and Detailed Explanation From Exact Extract:

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

Extracts:

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

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

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

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

With Google Cloud Directory Sync (GCDS), you can synchronize the data in your Google Account with your Microsoft Active Directory or LDAP server. GCDS doesn't migrate any content (such as email messages, calendar events, or files) to your Google Account. You use GCDS to synchronize your Google users, groups, and shared contacts to match the information in your LDAP server.

https://support.google.com/a/answer/106368?hl=en

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.​

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.