AWS Certified AI Practitioner AIF-C01 Practice Question
An organization wants to protect a generative AI application running on Amazon Bedrock from prompt injection attacks that could trick the model into exposing its hidden system instructions. Which action helps reduce this risk?
Filter and sanitize user input to remove or reject malicious instructions before forwarding it to the model.
Store all user prompts in an encrypted Amazon S3 bucket.
Increase the Amazon Bedrock inference endpoint's concurrency to reduce latency.
Attach an IAM read-only policy to the foundation model resource.
Prompt injection attempts to manipulate a model by inserting malicious content into the user prompt. A common first-line defense is to validate and sanitize every user-supplied prompt-removing or rejecting disallowed tokens, keywords, or patterns-before the text is passed to the foundation model. This limits an attacker's ability to override system instructions. Increasing concurrency, encrypting stored prompts, or changing IAM permissions do not directly prevent malicious instructions from reaching the model, so they have little effect on prompt injection.
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What is a prompt injection attack?
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How does filtering and sanitizing user input prevent prompt injection attacks?
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What role does Amazon Bedrock play in generative AI applications?
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What is a prompt injection attack in generative AI?
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How does input sanitization help prevent prompt injection attacks?
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Why don't measures like encryption or IAM policies prevent prompt injection attacks?
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AWS Certified AI Practitioner AIF-C01
Security, Compliance, and Governance for AI Solutions
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