CCSK Exam Dumps - Cloud Security Alliance Cloud Security Knowledge Questions and Answers

Using IAM roles/identities provided by cloud providers instead of static secrets (like passwords or API keys) significantly reduces the risk of credential leakage. IAM roles enable dynamic and temporary credentials, meaning that they are automatically rotated and do not need to be manually stored or managed. This eliminates the need for hardcoding sensitive credentials into code or configuration files, which can often lead to accidental exposure or misuse if not properly secured.

Lowering storage costs is not a direct benefit of using IAM roles over static secrets. Facilitating data encryption is important for security, but IAM roles are not specifically focused on data encryption. Improving system performance is not a primary benefit of using IAM roles over static secrets. The main advantage is security-related, specifically the reduction in credential leakage risks.

In the context of server-side encryption handled by cloud providers, the data is encrypted after transmission to the cloud using either provider-managed keys or customer-managed keys. The cloud provider takes responsibility for encrypting the data when it is stored in the cloud, ensuring that the data at rest is protected.

Server-side encryption typically uses symmetric encryption for performance reasons, but this attribute is not what defines the encryption process. Also, server-side encryption focuses on protecting data once it's in the cloud, not before transmission. Encryption in transit is typically handled separately from server-side encryption and applies to data as it moves between the client and the cloud.

The correct answer is C. To distribute incoming network traffic across multiple destinations.

A Load Balancer Service in an SDN environment is responsible for efficiently distributing network traffic across multiple servers or instances. This ensures high availability, reliability, and optimized resource usage.

Key Functions:

Traffic Distribution: Balances incoming requests to various servers based on predefined algorithms (round-robin, least connections, etc.).

High Availability: Prevents server overload and reduces downtime by distributing workload.

Scalability: Automatically adjusts as the number of requests or available resources changes.

Health Monitoring: Continually checks server availability and responsiveness to avoid directing traffic to non-responsive instances.

Why Other Options Are Incorrect:

A. Isolated virtual networks: Creating isolated networks is a function of network virtualization, not load balancing.

B. Monitor network performance: Monitoring is done by network monitoring tools, not load balancers.

D. Encrypt data for secure transmission: Encryption is handled by security protocols like TLS/SSL, not load balancers.

Real-World Example:

Services like AWS Elastic Load Balancer (ELB) and Azure Load Balancer ensure that traffic is distributed efficiently across instances, maintaining performance and uptime.

A cloud workload refers to the application software or services that are deployed and run on cloud infrastructure or platform. It can include a variety of computing tasks such as processing data, running applications, or performing computations, depending on the type of workload. Cloud workloads are typically virtualized and managed within cloud environments, utilizing resources like compute, storage, and networking provided by the cloud infrastructure or platform.

A network of servers connected to execute processes refers more to the underlying infrastructure, not the workload itself. A collection of physical hardware used to run applications describes the infrastructure, not the workload. A single software application hosted on the cloud is a partial description but doesn’t capture the broader concept of workloads, which could include multiple services or applications.

Many cloud providers offer default encryption for data at rest, which is typically enabled automatically for data stored within the cloud. In these cases, the encryption is often done using the cloud provider's keys as part of the provider’s security infrastructure, and it is usually provided at no additional cost to the customer. This ensures that data is protected while at rest, reducing the risk of unauthorized access.

The key outcomes of implementing robust cloud risk management practices focus on ensuring the security and resilience of cloud environments. This involves identifying, assessing, and mitigating risks associated with the use of cloud services, such as security threats, data privacy issues, and service availability concerns. By adopting strong risk management practices, organizations can better protect their data, ensure business continuity, and maintain compliance with regulations, which ultimately strengthens the overall security and reliability of their cloud environments.

Negotiating shared responsibilities is an important aspect of cloud security but is not the direct outcome of risk management practices. It's about clarifying roles between the customer and provider. Transferring compliance to the cloud service provider via inheritance is not the complete picture. While cloud service providers may help with compliance, the responsibility for compliance and risk management is still shared. Reducing the need for compliance with regulatory requirements is incorrect. Robust risk management practices help ensure compliance with regulatory requirements, not reduce the need for them.

Automating security and compliance checks helps minimize human error in long-running cloud workloads by continuously monitoring for security vulnerabilities, misconfigurations, or compliance issues without relying on manual intervention. This approach ensures consistent, repeatable security processes and can quickly identify and address potential risks, reducing the chances of oversight or mistakes that might occur with manual management.

Manual audits and restrictions can help but do not fully address the continuous nature of cloud workload security, which is why automation is critical for minimizing errors in long-running workloads.

To reduce vulnerabilities in virtual machines (VMs) in a cloud environment, it is critical to use secure base images that are free from known vulnerabilities, ensure regular patching to fix any discovered security issues, and implement configuration management to ensure that VMs are properly configured according to security best practices. This combination of practices ensures that VMs are both secure from the start and remain secure over time as new vulnerabilities are discovered.

Disabling unnecessary VM services and using containers is a good security practice but does not directly address vulnerabilities in VMs specifically. Encryption and SBOM is important for securing data and understanding dependencies but does not specifically focus on reducing vulnerabilities in VMs. Network isolation and monitoring are key network security practices but do not directly address the security of the VMs themselves.

The most effective way to identify security vulnerabilities in an application is to conduct automated and manual security testing throughout the development lifecycle. This approach ensures that security is continuously evaluated at every stage of development, rather than waiting until the end. Automated tools can help identify common vulnerabilities quickly, while manual testing allows for more in-depth analysis, including testing for complex, contextual security issues. This proactive and ongoing approach reduces the risk of vulnerabilities being overlooked and helps ensure that security is integrated into the application from the start.

Performing code reviews just prior to release is valuable, but it’s not comprehensive enough. Security testing should be done early and continuously, not just before release. Relying solely on secure coding practices is important but not sufficient. Even with secure coding practices, testing is essential to identify vulnerabilities. Waiting for a single penetration test after development is not effective because waiting until the end can allow many vulnerabilities to go unnoticed during development, leaving the application exposed.