Free Amazon Web Services SCS-C03 Practice Exam with Questions & Answers | Set: 5

Amazon Macie’sautomated sensitive data discoveryis designed for exactly this: at scale, Macie continuously evaluates andsamplesobjects across S3 buckets to identify where sensitive data (PII, financial data, credentials, etc.) is likely present. This gives the security engineer a low-touch way toidentify which buckets contain sensitive datawithout having to orchestrate per-bucket scanning workflows. Once Macie flags buckets with sensitive data findings, the engineer can then prioritize and runadditional, more targeted scanning(for example, deeper classification jobs on those specific buckets) rather than scanning everything exhaustively all the time.

The other options increase operational burden significantly. CRR to another Region (A) doubles storage/transfer complexity and is not needed for discovery. An event-driven Lambda scan per object (B) is expensive and complex at high object volumes and is not how Macie classification is intended to be orchestrated. Aggregating results into DynamoDB (D) adds an extra system to maintain when Macie already provides centralized findings, dashboards, and integrations.

Therefore, enabling Macie automated discovery and then performing deeper scans only on buckets where Macie detects sensitive data provides the least administrative overhead.

Option C best meets the requirements because Amazon GuardDuty provides Kubernetes-focused threat detection for Amazon EKS by analyzingEKS control plane audit logs(EKS Protection) and combining that signal withruntime telemetryfrom the worker nodes (Runtime Monitoring). EKS audit logs capture Kubernetes API activity and authorization decisions, allowing GuardDuty to detect suspicious cluster actions such as unusual API calls, unexpected access patterns, or indicators of compromise within the cluster. Runtime Monitoring extends coverage tooperating system/process activity, network connections, and file activityon the nodes, which directly aligns with the need to monitor OS, networking, and file events in addition to audit logs.

For notifications, GuardDuty generatesfindingsthat can be delivered throughAmazon EventBridgerules. EventBridge can route relevant GuardDuty findings to anAmazon SNS topic, and SNS can sendemail alertsto the security team by subscribing the team’s mailing list to the topic. This approach is fully managed, near real time, and avoids building custom log-parsing pipelines while still providing actionable alerts based on GuardDuty’s curated EKS threat detections.

AWS incident response guidance emphasizes immediate containment, credential invalidation, and removal of malicious resources. According to the AWS Certified Security – Specialty documentation, compromised credentials must be rotated or deleted immediately to prevent further unauthorized actions. Rotating or deleting access keys directly mitigates ongoing abuse.

Deleting unrecognized or unauthorized resources, such as the malicious S3 bucket, removes the active threat and limits further damage. Enabling Amazon GuardDuty provides continuous monitoring and helps identify additional compromised resources or malicious behavior that may not yet be visible.

Changing passwords for all IAM users is disruptive and unnecessary if compromise scope is limited. Encrypting CloudTrail logs does not reduce active impact. Taking EBS snapshots is primarily for forensic investigation, not immediate consequence minimization.

AWS best practices recommend GuardDuty activation, credential rotation, and removal of malicious resources as first-response actions.

Referenced AWS Specialty Documents:

AWS Certified Security – Specialty Official Study Guide

AWS Incident Response Best Practices

Amazon GuardDuty Threat Detection

AWS IAM Access Analyzer policy generation is specifically designed to help security engineers generate least-privilege IAM policies based on actual usage recorded in AWS CloudTrail. According to the AWS Certified Security – Specialty documentation, policy generation analyzes historical CloudTrail data to identify the exact API actions and resources that a role has accessed over a specified time period.

Because the role has been actively used for three months, there is sufficient CloudTrail data for IAM Access Analyzer to generate a refined customer managed policy automatically. This significantly reduces manual effort and eliminates the need to analyze logs or infer permissions. The generated policy can be reviewed and attached directly to the role, ensuring least privilege access with minimal engineering effort.

Option B only validates existing policies for security warnings and does not reduce permissions. Option C requires manual analysis of CloudWatch logs, which is time-consuming and error-prone. Option D does not analyze real usage and cannot generate role-specific least privilege policies.

AWS documentation explicitly recommends IAM Access Analyzer policy generation as the fastest and most accurate method to refine IAM permissions based on observed behavior.

Referenced AWS Specialty Documents:

AWS Certified Security – Specialty Official Study Guide

AWS IAM Access Analyzer Policy Generation

AWS IAM Least Privilege Best Practices

The company uses two different identity systems, and password policy must be enforcedat the system that actually stores and manages the passwords. For users authenticating throughIAM federation with on-premises Active Directory, IAM is not storing the users’ passwords; the password policy is enforced byActive Directory. Therefore, the minimum password length must be configured in theon-premises AD password policyso federated users are subject to the requirement during password creation/changes.

For the cloud application that usesAmazon Cognito user poolsas its user database, Cognitodoesstore and manage user passwords for those users. Cognito user pools include a configurable password policy (minimum length and complexity requirements). Updating the Cognito user pool password policy enforces the required minimum length for the application’s users going forward.

Options D and E are not applicable. Service control policies (SCPs) restrict AWS API actions; they cannot enforce end-user password-length rules inside AD or Cognito. Similarly, IAM policies control authorization to AWS resources and APIs, not password complexity/length requirements across external IdPs or Cognito user databases. Updating IAM password policy (Option A) would apply only toIAM users(local users in AWS), which is not the authentication model described for the federated workforce.

Amazon CloudFront includes a native geo restriction (geoblocking) capability that allows content owners to control access to their distributions based on the geographic location of the viewer. The viewer’s country is determined using the IP address from which the request originates. According to the AWS Certified Security – Specialty Official Study Guide and the Amazon CloudFront Developer Guide, geo restriction is specifically designed for scenarios where organizations must comply with regional regulations, licensing requirements, or data sovereignty policies.

From a cost perspective, CloudFront geo restriction is the most cost-effective solution because it is configured directly within the CloudFront distribution and does not require AWS WAF. AWS WAF introduces additional costs for web ACLs, rules, and request processing, which is unnecessary when the requirement is limited strictly to blocking or allowing access based on country.

Option A is incorrect because maintaining IP ranges for entire countries is operationally complex, error-prone, and not scalable. Country-level IP ranges frequently change, making this approach unsuitable and inefficient. Option B, although technically valid, is not the most cost-effective choice because AWS WAF geo match rules incur additional charges and are intended for advanced Layer 7 security controls such as application-layer attacks. Option D is incorrect because geolocation headers provided by CloudFront are informational only and cannot independently enforce access control decisions.

AWS documentation explicitly recommends CloudFront geo restriction when the sole requirement is country-based access control, reserving AWS WAF for advanced security inspection and threat mitigation use cases.

AWS Certified Security – Specialty Official Study Guide

Amazon CloudFront Developer Guide – Geo Restriction

AWS Well-Architected Framework – Security Pillar

AWS Security Best Practices Documentation

To performcustom validation at sign-upand explicitlyaccept or denyregistrations, Amazon Cognito providesLambda triggers. APre sign-up triggerruns synchronously during the sign-up flow (including the Hosted UI) and can implement custom checks (for example, IP reputation checks, email/domain validation, velocity checks, allow/deny lists, or geo checks using an external service). Based on the trigger logic, the function can allow the sign-up to proceed or reject it, meeting the “custom validation” and “accept/deny” requirement directly.

Because the observed fraud largely originatesoutside France, adding a front-door geographic control reduces unwanted traffic before it reaches Cognito.AWS WAFsupportsGeo matchconditions in a web ACL to allow/deny requests by country, which is a common mitigation for region-scoped applications. Associating a WAF web ACL to protect the Hosted UI endpoint helps block sign-up requests from non-French locations early, reducing fraud attempts and load.

The other options do not meet the requirement: Cognito user pools do not provide a native “geographic restriction setting” for sign-up (D), app client ID validation does not stop fraudulent sign-ups (C), and using a social IdP does not provide custom accept/deny validation for all sign-ups (E).

The most secure and AWS-recommended pattern for cross-account access is to create anIAM role in the target account (production)and allow trusted principals from the source account (developer) toassume the roleby using AWS STS. This avoids long-term credentials in the production account, supports short-lived session credentials, and enables strong controls such as MFA requirements, session duration limits, and precise least-privilege permissions attached to the role. It also centralizes ownership of production permissions in the production account, which is important for separation of duties and governance.

Option A is insecure because it requires password sharing and uses a long-lived IAM user credential, which is against AWS best practices. Option C is also poor because it relies on a long-lived IAM user in the production account and encourages credential sharing/duplication. Option B places the role in the developer account; while you can attach permissions there, access to production resources is governed by the production account. The standard approach is a production-account role with a trust policy that names the developer account principals (or a role) as allowed to assume it. Therefore, Option D is the most secure solution.

An RPO of1 hourmeans the company must be able to restore data with at most60 minutes of loss. Option A directly meets this by usingAWS Backupto takehourly backupsof both the compute layer (EC2) and the data layer (S3). AWS Backup provides centralized policy-based scheduling, retention, and (when configured) immutable protections such as Backup Vault Lock to help defend backups from tampering—important in ransomware recovery scenarios. Backing up the S3 buckets hourly also addresses recovery of critical objects such as images and music that users rely on.

In addition, recovery to “normal operations” is not only about data restoration; it also requires rapidly re-creating infrastructure reliably. UsingAWS CloudFormation templatesstored in aversion-controlled Git repositorysupports consistent, repeatable rebuilds of the ALB, EC2 fleet configuration, IAM roles, security groups, and related components. This infrastructure-as-code approach reduces human error under incident pressure and accelerates disaster recovery execution.

Option B fails the RPO because daily backups can lose up to 24 hours of data. Option C focuses on logging/governance rather than backups and does not establish a 1-hour recovery point. Option D also fails the RPO (4-hour snapshots) and is reactive to a specific finding type rather than a comprehensive DR plan for EC2 and S3.

AWS Config is a fully managed service that providescontinuous monitoring and evaluation of AWS resource configurationsagainst desired configuration baselines. According to the AWS Certified Security – Specialty Official Study Guide, AWS Config is the primary service used totrack configuration changes, evaluate compliance in near real time, and display compliance statesfor individual AWS resources.

AWS Config providesmanaged rulesthat directly map to the listed Aurora MySQL security requirements, including encryption at rest, public accessibility, deletion protection, and log exports to CloudWatch Logs. These managed rules continuously evaluate resources and mark them as compliant or noncompliant whenever a configuration change occurs.

The AWS Config dashboard enables security engineers to viewper-resource and per-rule compliance states at any point in time, satisfying the requirement to display compliance status for each part of the policy.

AWS Audit Manager (Option A) is designed for audit evidence collection and reporting, not continuous monitoring. AWS Security Hub (Option C) aggregates findings from other services but relies on AWS Config for configuration compliance data. Option D introduces unnecessary custom logic and does not provide a native compliance dashboard.

AWS documentation explicitly identifiesAWS Config as the authoritative service for continuous compliance monitoring and visibility.

AWS Certified Security – Specialty Official Study Guide

AWS Config Developer Guide

Amazon Aurora Security Best Practices

AWS Well-Architected Framework – Security Pillar