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.

Amazon GuardDuty findings provide high-level detection of suspicious activity but are not designed for deep investigation on their own. The AWS Certified Security - Specialty documentation explains that Amazon Detective is purpose-built to support rapid investigations by automatically collecting, correlating, and visualizing data from GuardDuty, AWS CloudTrail, and VPC Flow Logs. Detective enables security engineers to analyze API calls, user behavior, and resource interactions in context without making any changes to the environment.
Using read-only credentials ensures that the investigation does not impact the production application. Amazon Detective allows investigators to pivot directly from a GuardDuty finding into a detailed activity graph, showing which IAM user made anomalous calls, what resources were accessed, and how behavior deviated from the baseline. This significantly accelerates incident investigation.
Options A and C involve applying DenyAll policies, which are containment actions and could affect application availability. Option D requires manual analysis and setup and is slower than using Amazon Detective, which is designed for immediate investigative workflows.
AWS incident response guidance recommends using Detective for rapid, non-intrusive analysis after GuardDuty findings.
Referenced AWS Specialty Documents:
AWS Certified Security - Specialty Official Study Guide
Amazon GuardDuty and Amazon Detective Integration
AWS Incident Response Investigation Best Practices

AWS WAF provides managed and custom rules that can immediately mitigate common web exploits such as SQL injection without modifying application code. According to AWS Certified Security - Specialty documentation, placing AWS WAF in front of an Application Load Balancer is a recommended rapid- response control for legacy applications with known vulnerabilities.
Creating an ALB in front of the existing EC2 instances allows seamless traffic migration. AWS WAF SQL injection rules can be deployed and tested without downtime. Updating Route 53 to point to the ALB preserves normal operations. Restricting EC2 security groups afterward prevents bypassing the WAF.
Option B introduces CloudFront changes and single-origin testing, increasing complexity. Option C cannot be completed within 24 hours and risks downtime. Option D is invalid because AWS WAF cannot be attached directly to EC2 instances.
Referenced AWS Specialty Documents:
AWS Certified Security - Specialty Official Study Guide
AWS WAF Web ACL Architecture
AWS Application Load Balancer Security

Amazon GuardDuty provides continuous monitoring for anomalous and malicious network activity by analyzing VPC Flow Logs, DNS logs, and CloudTrail events. Enabling GuardDuty across accounts requires minimal configuration and immediately satisfies the requirement to monitor endpoints for anomalous network traffic, as described in the AWS Certified Security - Specialty Study Guide.
Encrypting data in transit for applications behind Elastic Load Balancing is most efficiently achieved by using AWS Certificate Manager (ACM). ACM provisions and manages TLS certificates automatically, and integrating ACM with ELB enables encrypted communication without manual certificate management.
For encryption at rest in Amazon S3, AWS best practices recommend enforcing server-side encryption using AWS KMS. An S3 bucket policy that denies PutObject requests unless the x-amz-server-side-encryption condition is present ensures that all uploaded objects are encrypted at rest using KMS-managed keys. This provides strong encryption guarantees with minimal operational effort.
Option A is unnecessary because Amazon Inspector focuses on vulnerability assessment, not encryption or network anomaly detection. Option C adds network complexity and is not required to meet the stated requirements. Option E is incorrect because x-amz-meta-side-encryption is not a valid enforcement mechanism.
Referenced AWS Specialty Documents:
AWS Certified Security - Specialty Official Study Guide
Amazon GuardDuty Threat Detection
AWS Certificate Manager and ELB Integration
Amazon S3 Encryption Best Practices

Option A satisfies all requirements with the most direct, purpose-built AWS logging workflow. By using the CloudWatch Agent (or fluent-bit / unified logging configuration) on each EC2 instance-regardless of whether it is On-Demand or Spot-the application logs can be centralized into asingle Amazon CloudWatch Logs log group. Centralization ensures the logs remain available even as Spot Instances are interrupted and replaced. Access control is handled withIAM policies(and optionally resource policies/KMS encryption) so that only a specific set of users can read/query the log group.
For analysis,CloudWatch Logs Insightsprovides an interactive query language that is SQL-like and commonly treated as "SQL queries" for troubleshooting. It enables fast filtering, aggregation, and pattern detection across large log volumes without building a separate data lake pipeline. This supports event-pattern analysis and root cause investigation directly from the centralized log group.
Option B is incorrect because Logs Insights queries CloudWatch Logs data, not arbitrary log files sitting in S3. Option C is inefficient (many log groups) and Athena cannot directly query CloudWatch log groups as a native data source. Option D is incorrect because Amazon Detective is for security investigations across supported data sources and is not the primary service for ad-hoc SQL-style querying of application logs.