Amazon Web Services SCS-C02 - AWS Certified Security - Specialty

Comprehensive Detailed Explanation with all AWS References

To log object-level activity and validate log file integrity:

CloudTrail Data Events with Log File Validation:

CloudTrail data events log object-level activity in S3 buckets.

Enable log file validation to ensure integrity using a digital signature.

Verify NAT Gateway Configuration (Option A):

Ensure that a NAT gateway exists in each public subnet to allow private subnet instances to access the internet for updates or API calls without exposing them directly.

Modify Private Subnet Route Tables (Option D):

Update the route tables associated with private subnets to route traffic destined for0.0.0.0/0through the NAT gateway in the same Availability Zone.

Advantages:

Network Segmentation: Ensures private subnets route traffic securely through NAT gateways.

Availability: Distributes NAT gateway resources across Availability Zones.

NAT Gateway Documentation

VPC Route Table Documentation

To rotate database credentials every 30 days, the most secure and efficient solution is to store the database credentials in AWS Secrets Manager and configure automatic credential rotation for every 30 days. Secrets Manager can handle the rotation of the credentials in both the secret and the database, and it can use AWS KMS to encrypt the credentials. Option B is incorrect because it requires creating a custom Lambda function to rotate the credentials, which is more effort than using Secrets Manager. Option C is incorrect because it stores the database credentials in an environment file or a configuration file, which is less secure than using Secrets Manager. Option D is incorrect because it combines the drawbacks of option B and option C. Verified References:

https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotating-secrets.html

https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotate-secrets_turn-on-for-other.html

The correct answer is C. Specify Amazon CloudWatch as the destination for the access logs. Export the CloudWatch logs to an Amazon S3 bucket. Use Amazon Athena to query the logs and to filter the logs by host.

According to the AWS documentation1, AWS WAF offers logging for the traffic that your web ACLs analyze. The logs include information such as the time that AWS WAF received the request from your protected AWS resource, detailed information about the request, and the action setting for the rule that the request matched. You can send yourlogs to an Amazon CloudWatch Logs log group, an Amazon Simple Storage Service (Amazon S3) bucket, or an Amazon Kinesis Data Firehose.

To create a log analysis solution for the AWS WAF web ACLs, you can use Amazon Athena, which is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL2. You can use Athena to query and filter the AWS WAF logs by host or any other criteria. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

To use Athena with AWS WAF logs, you need to export the CloudWatch logs to an S3 bucket.You can do this by creating a subscription filter that sends your log events to a Kinesis Data Firehose delivery stream, which then delivers the data to an S3 bucket3.Alternatively, you can use AWS DMS to migrate your CloudWatch logs to S34.

After you have exported your CloudWatch logs to S3, you can create a table in Athena that points to your S3 bucket and use the AWS service log format that matches your log schema5. For example, if you are using format for your AWS WAF logs, you can use the AWSSerDe serde. Then you can run SQL queries on your Athena table and filter the results by host or any other field in your log data.

Therefore, this solution meets the requirements of creating a log analysis solution for the AWS WAF web ACLs with the most operational efficiency. This solution does not require setting up any additional infrastructure or services, and it leverages the existing capabilities of CloudWatch, S3, and Athena.

The other options are incorrect because:

A. Specifying Amazon Redshift as the destination for the access logs is not possible, because AWS WAF does not support sending logs directly to Redshift. You would need to use an intermediate service such as Kinesis Data Firehose or AWS DMS to load the data from CloudWatch or S3 to Redshift.Deploying the Amazon Athena Redshift connector is not necessary, because you can query Redshift data directly from Athena without using a connector6. This solution would also incur additional costs and operational overhead of managing a Redshift cluster.

B. Specifying Amazon CloudWatch as the destination for the access logs is possible, but using Amazon CloudWatch Logs Insights to design a query to filter the logs by host is not efficient or scalable.CloudWatch Logs Insights is a feature that enables you to interactively search and analyze your log data in CloudWatch Logs7.However, CloudWatch Logs Insights has somelimitations, such as a maximum query duration of 20 minutes, a maximum of 20 log groups per query, and a maximum retention period of 24 months8. These limitations may affect your ability to perform complex and long-running analysis on your AWS WAF logs.

D. Specifying Amazon CloudWatch as the destination for the access logs is possible, but using Amazon Redshift Spectrum to query the logs and filter them by host is not efficient or cost-effective.Redshift Spectrum is a feature of Amazon Redshift that enables you to run queries against exabytes of data in S3 without loading or transforming any data9. However, Redshift Spectrum requires a Redshift cluster to process the queries, which adds additional costs and operational overhead.Redshift Spectrum also charges you based on the number ofbytes scanned by each query, which can be expensive if you have large volumes of log data10.

To redesign the edge security to help mitigate the DDoS attack risk in the future, the engineer could do the following:

Move the static content to Amazon S3, and front this with an Amazon CloudFront distribution. This allows the engineer to use a global content delivery network that can cache static content at edge locations and reduce the load on the origin servers.

Use AWS WAF security rules to inspect the inbound traffic. This allows the engineer to use web application firewall rules that can filter malicious requests based on IP addresses, headers, body, or URI strings, and block them before they reach the web servers.

Use Amazon Route 53 to distribute traffic. This allows the engineer to use a scalable and highly available DNS service that can route traffic based on different policies, such as latency, geolocation, or health checks.

Comprehensive Detailed Explanation with all AWS References

To implement WORM in Amazon S3 where no user, including the root account, can modify or delete objects:

S3 Object Lock in Compliance Mode:

Compliance mode ensures that the WORM policy cannot be bypassed, even by the root user.

Objects cannot be overwritten or deleted during the specified retention period.

For increased security while ensuring functionality, adjusting NACL3 to allow inbound traffic on port 5432 from the CIDR blocks of the application instance subnets, and allowing outbound traffic on ephemeral ports (1024-65536) back to those subnets creates a secure path for database access. Removing default allow-all rules enhances security by implementing the principle of least privilege, ensuring that only necessary traffic is permitted.

The error message indicates that the private key file permissions are too open, meaning that other users can read or write to the file. This is a security risk, as the private key should be accessible only by the owner of the file. To fix this error, the security administrator should use the chmod command to change the permissions of the private key file to 0400, which means that only the owner can read the file and no one else can read or write to it.

The chmod command takes a numeric argument that represents the permissions for the owner, group, and others in octal notation. Each digit corresponds to a set of permissions: read (4), write (2), and execute (1). The digits are added together to get the final permissions for each category. For example, 0400 means that the owner has read permission (4) and no other permissions (0), and the group and others have no permissions at all (0).

The other options are incorrect because they either do not change the permissions at all (D), or they give too much or too little permissions to the owner, group, or others (A, C).

Verified References:

https://superuser.com/questions/215504/permissions-on-private-key-in-ssh-folder

https://www.baeldung.com/linux/ssh-key-permissions

The correct answer is A, C, and E because they provide the most secure and efficient way to implement private connectivity to AWS services. Using interface VPC endpoints for Amazon SQS and gateway VPC endpoints for Amazon S3 allows the application to access these services without using public IP addresses or internet gateways. Modifying the endpoint policies on all VPC endpoints enables the security engineer to specify the SQS and S3 resources that the application uses and restrict access to other resources.

The other options are incorrect because they do not provide private connectivity to AWS services or they introduce unnecessary complexity or cost. Option B is incorrect because AWS Transit Gateway is used to connect multiple VPCs and on-premises networks, not to connect to AWS services. Option D is incorrect because modifying the IAM role applied to the EC2 instances is not sufficient to allow outbound traffic to the interface endpoints. The security group and route table associated with the interface endpoints also need to be configured. Option F is incorrect because AWS Firewall Manager is used to centrally manage firewall rules across multiple accounts and resources, not to connect to AWS services.