SCS-C03 Detection Practice Question
Which AWS service uses machine learning to detect unusual activity, such as unauthorized access to S3 buckets or atypical API calls?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
AWS GuardDuty.
AWS GuardDuty is an intelligent threat detection service that continuously monitors for malicious or unauthorized behavior. It leverages machine learning to analyze CloudTrail events, VPC Flow Logs, and DNS logs. This is essential for organizations because it identifies threats without requiring the management of complex rule sets, helping teams respond quickly to compromised accounts or malicious instances within the environment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Macie.
Why it's wrong here
AWS Macie is a data security service that uses machine learning to discover, classify, and protect sensitive data in S3. While it detects sensitive data exposure, it is not the primary service for detecting anomalous API activity or unauthorized access patterns across the entire AWS infrastructure.
- ✓
AWS GuardDuty.
Why this is correct
GuardDuty uses machine learning, anomaly detection, and integrated threat intelligence to monitor and protect AWS accounts. It is specifically designed to identify anomalous activity, such as unusual API calls or unauthorized access to sensitive resources like S3 buckets, based on baseline behavioral patterns.
- ✗
AWS WAF.
Why it's wrong here
AWS WAF is a web application firewall that protects web applications from common exploits and bots. It filters HTTP/S traffic based on rules, but it does not perform machine learning-based analysis of internal AWS API activity or account-level anomalous behaviors like unauthorized S3 access.
- ✗
AWS CloudTrail.
Why it's wrong here
CloudTrail records API activity logs but does not inherently use machine learning to detect anomalous behavior. It provides the data that other services like GuardDuty analyze, but on its own, it is a logging and auditing service, not an intelligent threat detection engine.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
About these practice questions
Courseiva writes every SCS-C03 question from scratch — 99 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SCS-C03 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SCS-C03 exam.