A healthcare organisation is deploying a generative AI assistant that may receive sensitive patient queries. The security team requires that data submitted to the model is NEVER used by the model provider to retrain their models. Which Amazon Bedrock feature addresses this requirement?
- AActivating Amazon Bedrock Guardrails to filter harmful content from both inputs and outputs before they reach the underlying model.
- BConfiguring a VPC endpoint (PrivateLink) for Amazon Bedrock so that all traffic stays within the AWS network and never traverses the public internet.
- CUsing Amazon Bedrock's data privacy commitment, which ensures that customer prompts and responses are not used to train or improve AWS or third-party foundation models. Correct
- DEnabling server-side encryption with a customer-managed KMS key on all Bedrock invocations to retain cryptographic control over model input data.
Why A is wrong: Guardrails filter content for safety and policy compliance but do not govern whether the model provider uses invocation data for retraining. Content filtering and data usage policies are separate concerns.
Why B is wrong: A VPC endpoint keeps traffic off the public internet and reduces network-level exposure, but the data still reaches the Bedrock service. Network routing does not affect the contractual or technical mechanisms governing whether prompt data is used for model training.
Why C is correct: AWS explicitly commits that data submitted to Amazon Bedrock - including prompts and completions - is not used to train the underlying foundation models. This is a contractual and architectural guarantee built into the service, directly addressing the organisation's requirement without any additional configuration.
Why D is wrong: Customer-managed KMS keys give the customer control over who can decrypt their data, which is a confidentiality and access-control measure. It does not prevent the model provider from processing the plaintext during inference or address the data-use policy for training.