The correct actions are to configure Amazon Bedrock Guardrails to block or mask PII and to use a custom AWS Lambda function to scan and redact PII from inputs and outputs. Amazon Bedrock Guardrails provides a managed, policy-based layer that can automatically detect and filter sensitive data like names or social security numbers before the model processes a prompt or returns a response, while a Lambda function offers a flexible, code-driven approach using services like Amazon Comprehend or regex patterns for deeper sanitization. On the AWS Certified AI Practitioner AIF-C01 exam, this question tests your understanding of how to prevent PII in Bedrock through both native guardrails and custom integration, with a common trap being to rely solely on the model’s built-in safety settings, which are not sufficient for compliance. Remember the mnemonic “Guard and Lambda” to recall that you need both a managed policy layer and a programmable redaction step to fully prevent PII in Bedrock.
AIF-C01 Fundamentals of Generative AI Practice Question
This AIF-C01 practice question tests your understanding of fundamentals of generative ai. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is building a generative AI application using Amazon Bedrock and needs to ensure that the model does not generate outputs containing personally identifiable information (PII). Which TWO actions should the company take? (Choose 2)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement a custom AWS Lambda function to scan and redact PII from inputs and outputs.
Option A is correct because a custom AWS Lambda function can be integrated into the application workflow to programmatically scan and redact PII from both inputs and outputs before they reach or leave the Bedrock model. This provides a flexible, code-driven approach to data sanitization, allowing the use of libraries like Amazon Comprehend or regex patterns to detect and mask PII entities such as names, addresses, and social security numbers.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Implement a custom AWS Lambda function to scan and redact PII from inputs and outputs.
Why this is correct
Lambda can use PII detection libraries to filter sensitive data.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use AWS Identity and Access Management (IAM) policies to restrict model access.
Why it's wrong here
IAM controls who can invoke the model, not what the model generates.
✗
Enable Amazon CloudWatch Logs to capture and audit model outputs.
Why it's wrong here
Logging helps audit but does not prevent PII from being generated.
✓
Configure Amazon Bedrock Guardrails to block or mask PII.
Why this is correct
Guardrails can detect and redact PII in both prompts and responses.
Related concept
Read the scenario before looking for a memorised answer.
✗
Place the Bedrock model endpoint within a private VPC.
Why it's wrong here
VPC provides network security, not content filtering.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between network-level security controls (like VPCs) and content-level data protection mechanisms, leading candidates to mistakenly choose VPC isolation as a solution for PII redaction.
Detailed technical explanation
How to think about this question
Amazon Bedrock Guardrails (Option D) provides a managed, policy-based mechanism to define content filters, including PII detection and masking, at the service level without custom code. Under the hood, Guardrails uses pattern matching and machine learning to identify PII entities and can either block the entire response or mask the sensitive data with placeholders. In a real-world scenario, combining Guardrails with a Lambda function for pre-processing inputs ensures defense in depth, as Guardrails handles known PII patterns while Lambda can apply custom business logic or integrate with external data classification services.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement a custom AWS Lambda function to scan and redact PII from inputs and outputs. — Option A is correct because a custom AWS Lambda function can be integrated into the application workflow to programmatically scan and redact PII from both inputs and outputs before they reach or leave the Bedrock model. This provides a flexible, code-driven approach to data sanitization, allowing the use of libraries like Amazon Comprehend or regex patterns to detect and mask PII entities such as names, addresses, and social security numbers.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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