Pass the Amazon Web Services AWS Certified Specialty SCS-C02 Questions and answers with CertsForce

The correct answer is A because GuardDuty can detect and alert on EC2 instance credential exfiltration events. These events indicate that the credentials obtained from the EC2 instance metadata service are being used from an IP address that is owned by a differentAWS account than the one that owns the instance1. GuardDuty can also provide details such as the source and destination IP addresses, the AWS account ID of the attacker, and the API calls made using the exfiltrated credentials2.

The other options are incorrect because they do not provide the information needed to determine if the credentials were used to access the company’s resources from an external account. Option B is incorrect because Audit Manager does not generate InstanceCredentialExfiltration events. Audit Manager is a service that helpsyou continuously audit your AWS usage to simplify how you assess risk and compliance with regulations and industry standards3. Option C is incorrect because CloudTrail logs do not show the account ID of the caller for GetSessionToken API calls to AWS STS. CloudTrail logs show the account ID of the identity whose credentials were used to call the API4. Option D is incorrect because CloudWatch logs do not show the GetSessionToken API calls to AWS STS by default. CloudWatch logs can show the API calls made by AWS Lambda functions, Amazon API Gateway, and other AWS services that integrate with CloudWatch5.

Comprehensive Detailed Explanation with all AWS References

To monitor EC2 instances for software vulnerabilities without installing agents and to display findings in AWS Security Hub,Amazon Inspectoris the most appropriate solution.

Amazon Inspector Overview:

Amazon Inspector is a vulnerability management service that automatically scans Amazon EC2 instances and container images in Amazon Elastic Container Registry (ECR) for known vulnerabilities.

It does not require agent installation as it integrates directly with EC2 metadata and uses network-based scanning.

Comprehensive Detailed Explanation with all AWS References

To provide a single management portal for access and integrate with an external IdP for SSO,AWS IAM Identity Center(formerly AWS Single Sign-On) is the best solution:

AWS IAM Identity Center:

IAM Identity Center enables centralized management of access to AWS accounts within an organization.

Supports external IdPs (e.g., Okta, Azure AD) using SAML 2.0 for workforce SSO.

The requirement is to remediate both existing and future noncompliant S3 buckets across multiple accounts and Regions in an AWS Organizations structure.

AWS Config Aggregator with organization-wide aggregation ensures that all accounts and Regions are continuously monitored for compliance.

By integrating a Lambda function with AWS Config rules, you can automatically remediate noncompliant resources (e.g., by applying encryption settings or blocking public access).

This solution provides both visibility and automated enforcement across the entire organization.

Options using SCPs (B and D) only prevent future actions and do not remediate existing noncompliant resources. Furthermore, scoping the aggregator to only some accounts/Regions (as in C and D) fails to meet the requirement for organization-wide remediation.

This approach aligns with Data Protection and Governance best practices in the AWS Certified Security – Specialty guidelines.

To resolve the issue of the Lambda function failing to create the report while adhering to the principle of least privilege, follow these steps:

Identify Required Permissions:

Determine the specific AWS Security Hub and Amazon Inspector actions the Lambda function needs to perform.

Common actions include:

securityhub:Get*

securityhub:List*

securityhub:Batch*

securityhub:Describe*

Create a Custom IAM Policy:

In the AWS Management Console, navigate to the IAM service.

Create a new policy with permissions tailored to the Lambda function's needs.

Define the policy to allow the necessary actions on the specific Security Hub resource.

For example:

{

"Version": "2012-10-17",

"Statement": [

{

"Effect": "Allow",

"Action": [

"securityhub:Get*",

"securityhub:List*",

"securityhub:Batch*",

"securityhub:Describe*"

],

"Resource": "arn:aws:securityhub:us-west-2::product/aws/inspector"

}

]

}

This policy grants the Lambda function the necessary read-only permissions to interact with Security Hub and Amazon Inspector.

Attach the Policy to the Lambda Execution Role:

Identify the IAM role associated with your Lambda function.

Attach the newly created custom policy to this role.

This ensures the Lambda function has the required permissions when invoked.

Test the Lambda Function:

Invoke the Lambda function to verify it can successfully create the report without permission errors.

Monitor the function's execution to ensure it operates as expected.

Implement Least Privilege Principle:

Regularly review and adjust the permissions to ensure they remain aligned with the function's requirements.

Remove any unnecessary permissions to minimize security risks.

Defining Lambda function permissions with an execution role: This AWS documentation provides guidance on creating and managing execution roles for Lambda functions, emphasizing the importance of granting least privilege access.

AWS Documentation

Managing permissions in AWS Lambda: This resource offers insights into best practices for managing permissions, including the use of identity-based and resource-based policies to control access to Lambda resources.

AWS Documentation

Grant least privilege access: Part of the AWS Well-Architected Framework, this document discusses the principle of least privilege and provides strategies for implementing it effectively within AWS environments.

AWS Documentation

AWS managed policies for AWS Lambda: This page details the AWS managed policies available for Lambda, which can serve as a starting point for creating custom policies tailored to specific needs.

AWS Documentation

Applying the principles of least privilege in AWS Lambda: This guide explores how to apply the principle of least privilege in AWS Lambda functions, focusing on avoiding granting wildcard permissions in IAM policies.

Orchestra

By following these steps and utilizing the referenced AWS documentation, you can ensure that your Lambda function has the necessary permissions to create the report while adhering to the principle of least privilege.

The correct answer is D. Remove Amazon SES from the root SCP.

This answer is correct because the root SCP is the most restrictive policy that applies to all accounts in the organization. The root SCP explicitly denies access to Amazon SES by using the NotAction element, which means that any action that is not listed in the element is denied. Therefore, removing Amazon SES from the root SCP will allow the developers to access it, as long as there are no other SCPs or IAM policies that deny it.

The other options are incorrect because:

A.Adding a resource policy that allows each member of the group to access Amazon SES is not a solution, because resource policies are not supported by Amazon SES1.Resource policies are policies that are attached to AWS resources, suchas S3 buckets or SNS topics, to control access to those resources2. Amazon SES does not have any resources that can have resource policies attached to them.

B.Adding a resource policy that allows “Principal”: {“AWS”: “arn:aws:iam::account-number:group/Dev”} is not a solution, because resource policies do not support IAM groups asprincipals3.Principals are entities that can perform actions on AWS resources, such as IAM users, roles, or AWSaccounts4.IAM groups are not principals, but collections of IAM users that share the same permissions5.

C.Removing the AWS Control Tower control (guardrail) that restricts access to Amazon SES is not a solution, because AWS Control Tower does not have any guardrails that restrict access to Amazon SES6.Guardrails are high-level rules that govern the overall behavior of an organization’s accounts7.AWS Control Tower provides a set of predefined guardrails that cover security, compliance, and operations domains8.

To meet the requirement of changing the key material for new files whenever a potential key breach occurs, the most appropriate solution would be to create a new customer managed key, add a key rotation schedule to the key, and invoke the key rotation schedule every time the security team requests a key change.

To preserve the data for 7 years and prevent anyone from changing or deleting it, the security officer needs to use a service that can store the data securely and enforce compliance controls. The most cost-effective way to do this is to use Amazon S3 Glacier, which is a low-cost storage service for data archiving and long-term backup. S3 Glacier allows you to create a vault, which is a container for storing archives. Archives are any data such as photos, videos, or documents that you want to store durably and reliably.

S3 Glacier also offers a feature called Vault Lock, which helps you to easily deploy and enforce compliance controls for individual vaults with a Vault Lock policy. You can specify controls such as “write once read many” (WORM) in a Vault Lock policy and lock the policy from future edits. Once a Vault Lock policy is locked, the policy can no longer be changed or deleted. S3 Glacier enforces the controls set in the Vault Lock policy to help achieve your compliance objectives. For example, you can use Vault Lock policies to enforce data retention by denying deletes for a specified period of time.

To use S3 Glacier and Vault Lock, the security officer needs to follow these steps:

Create a vault in S3 Glacier using the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs.

Create a Vault Lock policy in S3 Glacier that meets all the regulatory requirements using the IAM policy language. The policy can include conditions such as aws:CurrentTime or aws:SecureTransport to further restrict access to the vault.

Initiate the lock by attaching the Vault Lock policy to the vault, which sets the lock to an in-progress state and returns a lock ID. While the policy is in the in-progress state, you have 24 hours to validate your Vault Lock policy before the lock ID expires. To prevent your vault from exiting the in-progress state, you must complete the Vault Lock process within these 24 hours.Otherwise, your Vault Lock policy will be deleted.

Use the lock ID to complete the lock process. If the Vault Lock policy doesn’t work as expected, you can stop the Vault Lock process and restart from the beginning.

Upload the data to the vault using either direct upload or multipart upload methods.

For more information about S3 Glacier and Vault Lock, seeS3 Glacier Vault Lock.

The other options are incorrect because:

Option A is incorrect because creating an Amazon S3 bucket and configuring it to use S3 Object Lock in compliance mode will not prevent anyone from changing or deleting the data. S3 Object Lock is a feature that allows you to store objects using a WORM model in S3. You can apply two types of object locks: retention periods and legal holds. A retention period specifies a fixed period of time during which an object remains locked. A legal hold is an indefinite lock on an object until it is removed. However, S3 Object Lock only prevents objects from being overwritten or deleted by any user, including the root user in your AWS account. It does not prevent objects from being modified by other means, such as changingtheir metadata or encryption settings. Moreover, S3 Object Lock requires that you enable versioning on your bucket, which will incur additional storage costs for storing multiple versions of an object.

Option B is incorrect because creating an Amazon S3 bucket and configuring it to use S3 Object Lock in governance mode will not prevent anyone from changing or deleting the data. S3 Object Lock in governance mode works similarly to compliance mode, except that users with specific IAM permissions can change or delete objects that are locked. This means that users who have s3:BypassGovernanceRetention permission can remove retention periods or legal holds from objects and overwrite or delete them before they expire. This option does not provide strong enforcement for compliance controls as required by the regulatory requirements.

Option D is incorrect because creating an Amazon S3 bucket and using a lifecycle rule to transition the data to a vault in S3 Glacier will not prevent anyone from changing or deleting the data. Lifecycle rules are actions that Amazon S3 automatically performs on objects during their lifetime. You can use lifecycle rules to transition objects between storage classes or expire them after a certain period of time. However, lifecycle rules do not apply any compliance controls on objects or prevent them from being modified or deleted by users. Moreover, transitioning objects from S3 to S3 Glacier using lifecycle rules will incur additional charges for retrieval requests and data transfers.

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.

Storing sensitive information in environment variables is not a secure practice, as anyone who has access to the Lambda console or the Lambda function code can view them asplaintext. To address this security issue, the security engineer needs to use a service that can store and encrypt the environment variables, and access them at runtime using IAM permissions. The most cost-effective way to do this is to use AWS Systems Manager Parameter Store, which is a service that provides secure, hierarchical storage for configuration data management and secrets management. Parameter Store allows you to store values as standard parameters (plaintext) or secure string parameters (encrypted). Secure string parameters use a AWS Key Management Service (AWS KMS) customer master key (CMK) to encrypt the parameter value. To access the parameter value at runtime, the Lambda function needs to have IAM permissions to decrypt the parameter using the KMS CMK.

The other options are incorrect because:

Option A is incorrect because setting up IAM policies from the Lambda console to hide access to the environment variables will not prevent someone who has access to the Lambda function code from viewing them as plaintext. IAM policies can only control who can perform actions on AWS resources, not what they can see in the code or the console.

Option B is incorrect because using AWS Step Functions to store the environment variables is not a secure or cost-effective solution. AWS Step Functions is a service that lets you coordinate multiple AWS services into serverless workflows. Step Functions does not provide any encryption or secrets management capabilities, and it will incur additional charges for each state transition in the workflow. Moreover, storing environment variables in Step Functions will make them visible in the execution history of the workflow, which can be accessed by anyone who has permission to view the Step Functions console or API.

Option C is incorrect because storing the environment variables in AWS Secrets Manager and accessing them at runtime is not a cost-effective solution. AWS Secrets Manager is a service that helps you protect secrets needed to access your applications, services, and IT resources. Secrets Manager enables you to rotate, manage, and retrieve secrets throughout their lifecycle. While Secrets Manager can securely store and encrypt environment variables using KMS CMKs, it will incur higher charges than Parameter Store for storing and retrieving secrets. Unless the security engineer needs the advanced features of Secrets Manager, such as automatic rotation of secrets or integration with other AWS services, Parameter Store is a cheaper and simpler option.