Free Practice Questions for Amazon Web Services SCS-C03 Exam

Password policies are enforced at the identity provider where authentication occurs. According to the AWS Certified Security – Specialty Study Guide, when IAM is federated with an external identity provider such as on-premises Active Directory, IAM does not manage or enforce password policies. Instead, password requirements such as minimum length must be enforced directly in Active Directory Group Policy Objects.

Amazon Cognito user pools maintain their own user directory and authentication logic. Cognito provides configurable password policies, including minimum length, complexity, and expiration. To enforce a minimum password length for application users, the Cognito user pool password policy must be updated.

IAM password policies apply only to IAM users that authenticate directly with IAM and do not affect federated users or Cognito users. SCPs and IAM policies cannot enforce password length requirements.

Referenced AWS Specialty Documents:

AWS Certified Security – Specialty Official Study Guide

AWS IAM Federation and Password Policies

Amazon Cognito User Pool Security Settings

Amazon CloudWatch Logs is designed to collect, store, and analyze log data from ephemeral compute resources such as EC2 instances in Auto Scaling groups. According to the AWS Certified Security – Specialty Study Guide, using the CloudWatch agent to stream logs off instances ensures log durability even when instances are terminated during scale-in events.

CloudWatch Logs Insights provides a fully managed, serverless query engine that enables ad hoc querying, filtering, and aggregation of log data without requiring additional infrastructure. This directly satisfies the requirement to query logs for application sessions and user troubleshooting.

Option A introduces operational risk because logs could be lost between cron executions. Option B requires additional services and data pipelines, increasing cost and complexity. Option E adds storage cost and management overhead and is not necessary for log analytics.

AWS best practices recommend CloudWatch Logs and Logs Insights as the most cost-effective and scalable solution for centralized log retention and analysis in Auto Scaling environments.

Referenced AWS Specialty Documents:

AWS Certified Security – Specialty Official Study Guide

Amazon CloudWatch Logs and Logs Insights

AWS Logging Best Practices

Amazon Cognito identity pools are designed to provide temporary AWS credentials for applications by exchanging an authenticated identity token for AWS Security Token Service (STS) credentials. AWS Certified Security – Specialty guidance distinguishes between Cognito user pools (authentication) and identity pools (authorization to AWS resources). A user pool can authenticate a user and issue tokens, but an identity pool is required to obtain AWS credentials that can be used to sign AWS API requests, such as S3 API calls. The correct mechanism is for the application to use AssumeRoleWithWebIdentity through STS (which is the underlying federation method used by identity pools) to receive temporary credentials for an IAM role that grants S3 permissions. GetId alone does not provide credentials; it returns an identity identifier that is used as part of the credential exchange flow. Options C and D are incorrect because user pool tokens are not AWS credentials and cannot directly sign S3 requests. The solution therefore must use identity pools to map users to IAM roles and retrieve temporary credentials, satisfying the requirement for authenticated API calls using short-lived credentials.

Referenced AWS Specialty Documents:

AWS Certified Security – Specialty Official Study Guide

Amazon Cognito Identity Pools and STS Federation

AWS STS AssumeRoleWithWebIdentity

AWS CloudTrail organization trails are specifically designed to providecentralized, organization-wide loggingwith minimal operational effort. According to the AWS Certified Security – Specialty Official Study Guide, an organization trail recordsall management events for all member accountsand delivers them to asingle Amazon S3 bucket.

To ensure that logscannot be altered or deleted, Amazon S3Object Lock in compliance modemust be used. Compliance mode enforceswrite-once-read-many (WORM)protection, meaningno user, including the root user, can delete or modify objects before the retention period expires. This directly satisfies the requirement that no changes or deletions are allowed for 2 years.

The S3 bucket must reside in thededicated security accountto provide isolation and strong security boundaries. Granting write permissions to theorganization’s management account(Option A) aligns with AWS best practices, because the management account owns and manages the organization trail and centrally delivers logs on behalf of all member accounts.

Option B increases attack surface by allowing all member accounts to write directly. Option C does not meet immutability requirements because lifecycle policies do not prevent deletion. Option E introduces unnecessary services and operational complexity.

AWS documentation explicitly identifies the combination ofCloudTrail organization trails + S3 Object Lock (compliance mode)as therecommended, lowest-overhead solutionfor long-term, immutable audit log retention.

AWS Certified Security – Specialty Official Study Guide

AWS CloudTrail Organization Trail Documentation

Amazon S3 Object Lock Documentation

AWS Well-Architected Framework – Security Pillar

Before beginning an investigation, incident response best practice is topreserve evidence,prevent accidental loss of the asset, andclearly mark and control the potentially affected resource. Enablingtermination protection(Option B) helps ensure the instance is not accidentally terminated during triage, which would destroy volatile evidence and complicate forensics and recovery.

TakingEBS snapshotsof all attached data volumes (Option C) preserves a point-in-time copy of disk evidence for later forensic analysis, malware scanning, or offline investigation. Snapshots allow responders to create forensic volumes or AMIs in an isolated environment without repeatedly touching the potentially compromised instance.

Capturinginstance metadataand tagging the instance asunder quarantine(Option E) supports both investigation and operational control. Metadata capture (instance ID, IAM role, network interfaces, security groups, user-data, tags, recent changes) provides context for responders. Quarantine tagging enables automated workflows (for example, incident runbooks that isolate the instance, restrict IAM, or move it to a quarantine security group) and signals to other teams/tools that the instance is under investigation.

Option A is the opposite of what you want. Option D destroys evidence. Option F is not an appropriate “before investigation” step; altering metadata risks losing evidence and is not the primary containment approach.

The correct Config rule for finding buckets that are not usingSSE-KMS by defaultiss3-default-encryption-kms. It evaluates the bucket’s default encryption settings and flags buckets that do not have KMS default encryption enabled. The s3-bucket-ssl-requests-only rule focuses on enforcing HTTPS-only requests and does not validate encryption-at-rest settings, so it cannot satisfy the “identify not encrypted with KMS” requirement.

For preventing uploads of objects that are not encrypted with KMS, an organization-wide control is needed. AnSCPcan restrict s3:PutObject so that uploads succeed only when the request specifiesSSE-KMS(and optionally a specific KMS key). This provides broad, low-touch enforcement across many accounts and buckets. While bucket policies can also enforce SSE-KMS, managing and verifying hundreds of bucket policies is more operationally heavy than a centrally managed SCP guardrail.

Option B enforcesSSE-S3, which does not meet the requirement forKMSencryption. Option D uses the wrong Config rule and relies on an “allow-only” pattern rather than explicit deny logic, making it an unreliable fit for the stated goal. Therefore, A is the best answer.

A rate-based rule in AWS WAF is designed to quickly mitigate spikes and potential layer 7 floods bytracking request rates per originating IPand temporarily blocking (or counting/challenging, depending on configuration) IPs that exceed a defined threshold within a 5-minute rolling window. In this scenario, the malicious traffic is distributed acrosshundreds of IPsin two countries, and the application still needs to remain available globally for legitimate users. A rate-based rule provides fast, targeted throttling that reduces abusive request patterns without permanently blocking entire geographies. This aligns with “quickly limit” while minimizing collateral impact.

Blocking both countries with a geo match rule (Option B) would likely block legitimate users located in those countries, which violates the requirement. Security groups (Options C and D) cannot natively enforcegeographicfiltering, and they are not well suited for large, rapidly changing sets of public source IPs at the application layer. Additionally, WAF operates at layer 7 with richer matching (rate limiting, URI/header patterns, bot controls), which is the appropriate control point when the ALB already has a web ACL associated. Therefore, implementing an AWS WAFrate-basedrule is the most effective and least disruptive immediate mitigation.

AWS Shield Advanced is the AWS-native managed service specifically designed to provide detection, mitigation, and visibility for Distributed Denial of Service (DDoS) attacks at both the network and application layers. Shield Advanced integrates directly with Amazon CloudWatch by publishing DDoS-related metrics such as DDoSDetected, AttackVolume, and AttackVector, which can be monitored using CloudWatch alarms to trigger alerts in near real time. This makes option D the correct and fully supported solution.

Amazon Macie focuses on discovering and protecting sensitive data (such as PII) in Amazon S3 using machine learning and does not provide DDoS detection capabilities, making option A incorrect. Amazon Inspector is a vulnerability management service that assesses EC2 instances, container images, and Lambda functions for software vulnerabilities and unintended network exposure; it does not detect live DDoS attacks, so option B is incorrect. AWS Firewall Manager is a centralized management service for configuring AWS WAF, Shield Advanced, and security groups across accounts, but it does not emit native DDoS detection metrics for alerting, which eliminates option C.

According to AWS Security Specialty documentation, the recommended best practice for DDoS detection and alerting is to enable AWS Shield Advanced and configure Amazon CloudWatch alarms on Shield metrics, optionally integrating with Amazon SNS for notifications and AWS Incident Manager for response automation.

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.

The requirement is to havekey material generated and used inside a custom key store backed by an AWS CloudHSM cluster. This is exactly whatAWS KMS Custom Key Storesprovide: KMS manages the keys and policies, but the cryptographic operations for those KMS keys occur in the associatedCloudHSMcluster, keeping the key material within HSM boundaries. For applications that needlocal-use data keys(both symmetric data keys and asymmetric data key pairs), KMS supports generating data keys and data key pairs that applications can use for envelope encryption and local cryptographic operations, while the master key protections remain within KMS (and within CloudHSM when using a custom key store).

For auditing, AWS best practice isAWS CloudTrail, which records KMS API calls (such as CreateKey, GenerateDataKey, GenerateDataKeyPair, Encrypt/Decrypt, etc.) and provides an immutable event history for compliance and investigation. Athena can query logs, but it is not the primary audit record source; GuardDuty is for threat detection, not authoritative key-usage auditing. Therefore, the correct combination isKMS with a CloudHSM-backed custom key storeplusCloudTrailfor auditability.