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| Section | Objectives |
|---|---|
| Configure network security | - Google Cloud network security controls
|
| Configure access within a cloud solution environment | - Identity and Access Management (IAM)
|
| Manage operations within a cloud security environment | - Security monitoring and operations
|
| Ensure data protection | - Encryption and key management
|
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NEW QUESTION # 288
You are in charge of creating a new Google Cloud organization for your company. Which two actions should you take when creating the super administrator accounts? (Choose two.)
Answer: B,E
Explanation:
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
NEW QUESTION # 289
You have a highly sensitive BigQuery workload that contains personally identifiable information (Pll) that you want to ensure is not accessible from the internet. To prevent data exfiltration only requests from authorized IP addresses are allowed to query your BigQuery tables.
What should you do?
Answer: D
Explanation:
Enable VPC Service Controls:
VPC Service Controls help mitigate the risk of data exfiltration by allowing you to define a security perimeter around GCP resources.
Set up a service perimeter around your BigQuery project to restrict data access to within the defined perimeter.
Create Access Levels:
In the Google Cloud Console, navigate to the Access Context Manager.
Define access levels based on IP address conditions, specifying the authorized source IP addresses that are allowed to access your BigQuery resources.
These access levels are used to enforce policies that restrict who can access your sensitive data based on their IP addresses.
Apply Service Perimeter with Access Levels:
Apply the created access levels to the service perimeter to ensure that only requests originating from the specified IP addresses are able to access BigQuery tables.
This setup ensures that the sensitive PII data is not accessible from unauthorized IP addresses, reducing the risk of data exfiltration.
Reference:
VPC Service Controls
Access Context Manager
Defining Access Levels
NEW QUESTION # 290
Your DevOps team uses Packer to build Compute Engine images by using this process:
1. Create an ephemeral Compute Engine VM.
2. Copy a binary from a Cloud Storage bucket to the VM's file system.
3. Update the VM's package manager.
4. Install external packages from the internet onto the VM.
Your security team just enabled the organizational policy, constraints/ compute.vmExternalIpAccess, to restrict the usage of public IP Addresses on VMs. In response, your DevOps team updated their scripts to remove public IP addresses on the Compute Engine VMs; however, the build pipeline is failing due to connectivity issues.
What should you do? (Choose two.)
Answer: A,E
Explanation:
Provision a Cloud NAT instance (Option B): Cloud NAT allows your Compute Engine instances without public IP addresses to access the internet while preserving the security restrictions imposed by your organizational policy. By provisioning a Cloud NAT instance in the same VPC and region as your Compute Engine VMs, you enable outbound connectivity for these VMs.
Enable Private Google Access (Option C): Enabling Private Google Access on the subnet where your Compute Engine VMs are deployed allows these instances to access Google Cloud services over the private IP address range. This can help with accessing external resources needed during the Packer image build process without exposing the VMs to the public internet.
NEW QUESTION # 291
A company is running workloads in a dedicated server room. They must only be accessed from within the private company network. You need to connect to these workloads from Compute Engine instances within a Google Cloud Platform project.
Which two approaches can you take to meet the requirements? (Choose two.)
Answer: A,B
Explanation:
To connect Compute Engine instances within a Google Cloud Platform project to workloads running in a dedicated server room that can only be accessed from within the private company network, you can use the following approaches:
* Cloud VPN: Cloud VPN securely connects your on-premises network to your Google Cloud Virtual Private Cloud (VPC) network through an IPsec VPN connection. This enables secure communication between your GCP instances and your on-premises workloads over the internet.
* Cloud Interconnect: Cloud Interconnect provides direct physical connections between your on- premises network and Google's network. It offers higher bandwidth and lower latency compared to Cloud VPN, making it suitable for workloads that require fast and reliable connectivity.
Both Cloud VPN and Cloud Interconnect allow you to securely connect your on-premises environments to Google Cloud, ensuring that the workloads remain within the private company network.
References
* Cloud VPN Overview
* Cloud Interconnect Overview
NEW QUESTION # 292
A customer's internal security team must manage its own encryption keys for encrypting data on Cloud Storage and decides to use customer-supplied encryption keys (CSEK).
How should the team complete this task?
Answer: A
Explanation:
To use customer-supplied encryption keys (CSEK) for encrypting data on Cloud Storage, follow these steps:
* Generate an Encryption Key: Generate a 256-bit AES encryption key. This key should be base64- encoded.
sh
Copy code
openssl rand -base64 32
* Upload Object with CSEK: Use the gsutil command-line tool to upload the object to Cloud Storage, specifying the location of the encryption key using the -o option.
gsutil -o "GSUtil:encryption_key=<base64-encoded-key>" cp [LOCAL_OBJECT_PATH] gs://
[BUCKET_NAME]/
* Verify Encryption: After uploading the object, you can verify that it is encrypted using the provided CSEK by checking the object's metadata.
gsutil stat gs://[BUCKET_NAME]/[OBJECT_NAME]
* Key Management: Ensure that the encryption key is securely stored and managed. It should not be hard-coded in scripts or applications.
By using the gsutil tool and specifying the encryption key, you ensure that the object is encrypted using the customer-supplied encryption key during the upload process.
References:
* Customer-Supplied Encryption Keys (CSEK) Documentation
* gsutil Command Line Tool Documentation
NEW QUESTION # 293
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