Security, Compliance and Governance for AI Solutions

A healthcare company is deploying a machine learning model on Amazon SageMaker to analyze patient records. The model requires access to a DynamoDB table containing patient data. Which combination of AWS services and features should the company use to restrict access to only the necessary resources?

A company uses Amazon Rekognition to analyze images stored in an S3 bucket. The security team requires that all image analysis be logged to AWS CloudTrail for auditing. What is the minimum configuration needed to meet this requirement?

A financial services company is building a predictive model using Amazon SageMaker. The model training data contains personally identifiable information (PII). The company must ensure that the data is encrypted at rest and in transit, and that access to the data is logged. Which combination of AWS services meets these requirements?

A data scientist needs to grant an IAM user access to a specific Amazon SageMaker notebook instance. The user should only be able to start and stop the notebook instance, but not delete it. Which IAM policy statement should be used?

A company is using Amazon Comprehend to extract entities from customer support tickets. The compliance team requires that the text sent to Comprehend be encrypted in transit and that Comprehend does not store any data beyond the processing time. How should the company configure the API call?

A company uses Amazon SageMaker to host a real-time inference endpoint. The model was trained on sensitive data, and the company wants to ensure that the data sent to the endpoint is encrypted in transit. Additionally, the company wants to restrict access to the endpoint to only traffic originating from a specific VPC. Which configuration meets these requirements?

A company is using Amazon Textract to extract text from scanned documents stored in an S3 bucket. The security team requires that all access to the documents be logged and that the documents be encrypted at rest using a customer-managed key. What should the company do to meet these requirements?

A company is using Amazon SageMaker to train machine learning models. The security team wants to ensure that the training data is encrypted at rest and that the SageMaker notebook instances cannot access the internet. Which TWO actions should the company take? (Choose TWO.)

A company is deploying an Amazon Lex chatbot that processes customer credit card information. The company must ensure that the chatbot does not log sensitive data and that the data is encrypted in transit. Which THREE actions should the company take? (Choose THREE.)

A company is using Amazon Rekognition to detect objects in images stored in an S3 bucket. The company needs to ensure that the Rekognition service has permission to read images from the S3 bucket. Which TWO methods can achieve this? (Choose TWO.)

Refer to the exhibit. An IAM policy is attached to a role used by an Amazon SageMaker notebook instance. The notebook instance attempts to upload a model artifact to the S3 bucket 'my-bucket' without specifying server-side encryption. What will happen?

Refer to the exhibit. A company has the S3 bucket policy shown above. The company uses Amazon Rekognition to analyze images in the 'my-images' bucket. An IAM role used by a Lambda function calls Rekognition. Why might Rekognition be unable to read images from the bucket?

A company is deploying a generative AI model on Amazon Bedrock. The model is accessed by an application running on Amazon ECS Fargate. The security team requires that all data sent to and from the Bedrock model be encrypted in transit, and that the ECS task does not have internet access. The ECS tasks are launched in a private VPC subnet with a VPC endpoint for Bedrock configured. However, when the application attempts to invoke the Bedrock model, the call fails with a timeout error. The VPC endpoint policy is set to allow all actions from all principals. What is the most likely cause of the failure?

A healthcare company is using Amazon SageMaker to train and deploy a model that predicts patient readmission risk. The model uses sensitive protected health information (PHI). The company must ensure that data is encrypted at rest and in transit, and that access to the model endpoint is restricted to authorized applications only. The security team has configured AWS KMS customer managed keys for encryption, and IAM roles for SageMaker execution. However, during a security audit, it was discovered that the model endpoint is accessible from the internet and that the data used for training was stored in an S3 bucket with default encryption enabled. The compliance team requires that all PHI data be encrypted with a key that is rotated annually, and that no public access is allowed to the endpoint or training data. Which combination of actions should the ML engineer take to remediate these issues?

A company is using Amazon Bedrock to generate responses for customer support. They want to ensure that the model does not expose personally identifiable information (PII) in its outputs. Which AWS feature can be configured to automatically redact PII from model responses?

A machine learning team needs to share a trained model with multiple teams across different AWS accounts. The model artifacts are stored in an S3 bucket in the central account. What is the most secure way to grant cross-account read access to the model artifacts?

A company is using Amazon SageMaker to train a model. The training data is stored in an S3 bucket that is encrypted with an AWS KMS customer managed key (CMK). The training job fails with an error indicating that the SageMaker execution role does not have permission to decrypt the data. The administrator has verified that the execution role has the kms:Decrypt permission. What additional permission might be missing?

A company wants to monitor for malicious activity in their machine learning pipelines, such as unauthorized access to training data or model artifacts. Which AWS service can provide automated threat detection and continuous monitoring?

A data scientist is using Amazon SageMaker Studio. The company policy requires that all data used in SageMaker Studio notebooks be encrypted at rest and in transit. Which configuration should be enabled to meet this requirement?

An organization uses Amazon Bedrock to generate content. They have implemented guardrails to block toxic content. However, some users are able to bypass the guardrails by encoding their prompts. What step should be taken to improve security?

A company is deploying a machine learning model that processes personal data of EU citizens. Which AWS service can help them comply with the General Data Protection Regulation (GDPR) by tracking data lineage and usage?

A machine learning engineer wants to ensure that a SageMaker notebook instance only has access to a specific S3 bucket containing training data. The notebook instance is in a VPC. What is the most secure way to restrict access?

A company uses Amazon SageMaker for model training. To comply with data residency requirements, they must ensure that the training data never leaves a specific AWS region. However, during training, the SageMaker service might use resources in other regions for auto-scaling. Which configuration should they use to enforce data residency?

A company is using Amazon Bedrock to deploy a chatbot. They want to ensure that the chatbot does not produce harmful or biased content. Which TWO AWS services or features can be used together to implement content moderation and monitoring?

A financial services company is deploying a machine learning model that must comply with SOC 2 and PCI DSS. They need to ensure that the model artifacts and training data are encrypted, access is audited, and the environment is protected from network threats. Which THREE AWS services should they implement?

A data science team is using Amazon SageMaker to build a model. They want to ensure that only authorized users can deploy models to production. Which TWO methods can they use to enforce this?

Refer to the exhibit. A security officer has attached this IAM policy to a user to allow invocation of a SageMaker endpoint. However, the user is unable to invoke the endpoint from an EC2 instance in the same VPC. What is the most likely cause?

Refer to the exhibit. A data scientist is trying to run a SageMaker training job that uses training data from an S3 bucket encrypted with the specified KMS key. The training job fails with an access denied error. The IAM role shown is attached to the training job. What is the missing permission?

Refer to the exhibit. A security analyst is reviewing CloudTrail logs and notices a training job creation from an IP address (203.0.113.5) that is not associated with the company's network. What is the most likely cause?

A company is using Amazon Bedrock to deploy a foundation model. To comply with GDPR, they need to ensure that the model does not generate outputs containing personally identifiable information (PII). Which AWS service can best help detect and redact PII from the model's responses?

A data science team is using Amazon SageMaker Studio. To meet compliance requirements, they need to ensure that all user activity in the environment is logged and that any unauthorized access attempts are detected. Which approach should they take?

A company uses Amazon Bedrock to generate content. They need to guarantee that the model does not produce toxic or biased outputs and that any violations are logged for review. Which service should they integrate with Bedrock?

A company uses Amazon Rekognition to analyze images for a user-generated content platform. To comply with data residency requirements, they must ensure that images are not processed outside a specific AWS region. What should the company do?

A team is using Amazon SageMaker to deploy a real-time inference endpoint. The endpoint must be accessible only from a specific IP range and must automatically scale based on request volume. Which configuration meets these requirements?

An organization uses Amazon Macie to discover sensitive data in S3. The compliance team needs to receive notifications when Macie finds PII. Which AWS service should they use to send notifications?

A data engineer needs to ensure that all data uploaded to an S3 bucket for SageMaker training is automatically encrypted with a customer-managed key. Which S3 feature should they enable?

A security analyst is reviewing CloudTrail logs for SageMaker API calls to identify which user executed a particular training job. The logs show assumed roles. In which CloudTrail event field can the analyst find the name of the user who assumed the role?

A company uses Amazon SageMaker to host a model for fraud detection. The model must be re-evaluated for bias on a monthly basis. Which SageMaker feature can be used to detect bias in a trained model?

A company uses Amazon Bedrock to build a generative AI application. They need to secure the application by restricting access to the model and preventing sensitive data from being stored in prompts. Which TWO actions should they take? (Choose two.)

A data science team uses Amazon SageMaker to train models. To comply with SOC 2, they must ensure that access to training data is logged, that the data is encrypted at rest, and that model training jobs are isolated from each other. Which THREE actions should they take? (Choose three.)

A financial services company uses Amazon SageMaker Feature Store to manage features for machine learning models. The compliance auditor requires that all changes to feature definitions are logged and that feature data is immutable once written. Which TWO approaches should the team implement? (Choose two.)

A company is using Amazon SageMaker to train machine learning models on sensitive customer data. Which AWS service can be used to encrypt the data at rest in the S3 bucket used by SageMaker?

A data science team needs to grant a SageMaker notebook instance access to an S3 bucket containing training data. Which IAM policy should be attached to the notebook instance's execution role?

A financial services company is deploying a fraud detection model using Amazon SageMaker. They need to ensure that inference requests are encrypted in transit and that the model endpoint is only accessible from within a VPC. What is the MOST secure way to achieve this?

A company wants to track API calls made to Amazon SageMaker for audit purposes. Which AWS service should they enable?

A machine learning engineer notices that a SageMaker training job failed due to insufficient permissions to access a KMS-encrypted S3 bucket. The training job's IAM role has S3 access permissions. What should be done to resolve the issue?

A healthcare company needs to use Amazon SageMaker Ground Truth for data labeling. The data includes protected health information (PHI) that must remain in the US. Which configuration meets the compliance requirements?

A company wants to ensure that only approved machine learning models are deployed to production on Amazon SageMaker. Which combination of services can enforce this governance requirement?

A company is using Amazon Comprehend to analyze customer feedback. They need to ensure that the documents are encrypted at rest. What should they do?

During a security review, it is found that an Amazon SageMaker notebook instance has outbound internet access, which could lead to data exfiltration. The notebook must only access resources within the VPC. Which step should be taken to restrict internet access?

An IAM policy allows creation of SageMaker training jobs only if they use a specific VPC security group. A user tries to create a training job without specifying that security group. What will happen?

An administrator reviews a CloudTrail log entry for a CreateModel API call. Which security concern should they investigate?

A data scientist sets up a Model Monitoring schedule for data quality. What is a potential security issue with this configuration?

A company needs to secure data used for training machine learning models in Amazon SageMaker. Which TWO actions should be taken to protect data at rest and in transit? (Choose TWO.)

A company uses Amazon SageMaker to build and deploy models. They want to enforce compliance that all model endpoints are encrypted in transit and use least privilege access. Which THREE steps should they take? (Choose THREE.)

Which TWO AWS services can be used to monitor and detect security anomalies in Amazon SageMaker model inference data? (Choose TWO.)

A company wants to use Amazon SageMaker to train a model on sensitive healthcare data. What is the MOST secure way to ensure that the training data is encrypted at rest and in transit, and that only authorized users can access the model artifacts?

A company deploys an Amazon Bedrock agent that uses a knowledge base with sensitive financial documents. The security team requires that all data retrieval queries be logged for auditing, and that the LLM responses do not contain any personally identifiable information (PII). What combination of services should the company use?

A financial institution uses Amazon SageMaker to host a model for credit scoring. The model was trained on data that includes demographic attributes. During a routine audit, the compliance team finds that the model produces significantly different approval rates for applicants of different ethnicities, even when credit profiles are similar. The institution must continue using the model but needs to ensure compliance with fair lending laws. What should the company do FIRST?

A company is using Amazon Bedrock to build a generative AI application. The company wants to prevent the model from generating toxic or harmful content while still allowing creative responses. Which feature should the company enable?

A research organization is using Amazon SageMaker Studio to collaborate on building machine learning models. The security policy requires that all data and code remain within a VPC and cannot be accessed from the public internet. Additionally, the organization wants to enforce that only approved base images are used for the Studio environment. How should the organization configure SageMaker Studio to meet these requirements?

A company uses Amazon SageMaker to train a model on customer transaction data. The data is stored in an S3 bucket encrypted with SSE-KMS. The data scientists are using a SageMaker notebook instance to preprocess the data. The security team notices that the notebook instance can access the KMS key directly through the SageMaker console, even when the data scientists do not have explicit KMS permissions. What is the MOST likely reason for this behavior?

A company is deploying an AI-based customer service chatbot using Amazon Lex and AWS Lambda. The company must ensure compliance with GDPR by allowing users to request deletion of their personal data collected during conversations. Which TWO actions should the company take? (Choose two.)

A company uses Amazon SageMaker Pipelines for MLOps. The security team requires that all pipeline steps use only approved Docker images from a private Amazon ECR repository, and that all pipeline artifacts are encrypted with a customer managed KMS key. Which THREE steps must the company configure to meet these requirements? (Choose three.)

A company is using Amazon Bedrock to generate content for a marketing application. The company wants to ensure that the model does not generate content that violates the company's brand guidelines, which prohibit certain keywords and tones. Which TWO features should the company use to enforce these guidelines? (Choose two.)

A healthcare company is deploying a model to predict patient readmission risk using Amazon SageMaker. The model processes protected health information (PHI). The company must adhere to HIPAA regulations, which require that all PHI is encrypted at rest and in transit, and that access to the data is logged and audited. The data is stored in an S3 bucket encrypted with SSE-S3. The SageMaker training job uses a custom Docker container that reads data from the S3 bucket and writes model artifacts back to another S3 bucket. The security team notices that the model artifacts in the output bucket are not encrypted. Also, the training logs in CloudWatch Logs contain PHI because the training script logs patient features. The company must fix these issues without delaying the deployment. What should the company do?

A company uses Amazon SageMaker to build and deploy machine learning models. The security team has implemented a policy that all SageMaker notebook instances must be launched in a VPC and cannot have direct internet access. However, data scientists need to download open-source datasets from the internet for model training. They also need to install Python packages from PyPI. Currently, the SageMaker notebook instances are in a VPC with no internet gateway. The data scientists cannot download any external data or packages. The VPC has a NAT gateway already configured. What should the company do to allow the necessary internet access while maintaining the security requirement?

A financial services company uses Amazon Bedrock to power a customer-facing chatbot that provides investment advice. The company must ensure that the chatbot's responses comply with regulatory standards, meaning that the model should not generate advice that is speculative or promises returns. The company has implemented Bedrock Guardrails with content filters. However, during testing, the chatbot still generates responses that violate the guidelines. A review of the guardrail configuration shows that the content filters are set to the lowest sensitivity. The company wants to enforce stricter filtering without completely blocking legitimate responses. What should the company do?

A company uses Amazon SageMaker Model Registry to manage model versions. The security team requires that only approved models can be deployed to production. The ML team creates a new model version and registers it in the Model Registry. When trying to deploy the model to a production endpoint, the deployment fails because the model is not approved. The ML team asks the DevOps team to approve the model. However, the DevOps team cannot see the model in the Model Registry. What is the MOST likely reason?

A company is using Amazon SageMaker Ground Truth to create labeled datasets for a computer vision model. The dataset contains images of people in public places. The company must comply with data privacy regulations that require explicit consent for using images of individuals. The company has a privacy team that reviews the images and provides consent lists. The ML team suspects that some images in the dataset might include individuals who have not consented. The company wants to ensure that only those images with consent are used for training. What should the company do?

A company that uses Amazon Bedrock for generating product descriptions wants to ensure that the output does not contain any confidential information from its proprietary database that is used as context. The company uses a knowledge base in Bedrock to augment the model. The security team is concerned that the model might inadvertently regurgitate exact strings from the knowledge base. The company wants to adopt a solution that prevents this while still allowing the model to use the knowledge base for generating relevant descriptions. What should the company do?

A company is deploying a machine learning model using Amazon SageMaker. They need to ensure that the training data, which contains personally identifiable information (PII), is encrypted both in transit and at rest. They also need to control access to the model endpoints. Which TWO actions should the company take?

Refer to the exhibit. A data scientist is training a model in SageMaker using a KMS-encrypted dataset. The training job fails with the error shown. Which action should be taken to resolve this issue?

A healthcare company is developing a machine learning model using Amazon SageMaker to process protected health information (PHI). They have strict security requirements to comply with HIPAA. The company has implemented the following measures: All training data is stored in an S3 bucket with server-side encryption using AWS KMS. The data is accessed exclusively through Amazon SageMaker notebooks running in a private VPC with no internet access. The VPC has a VPC endpoint for S3 to ensure traffic stays within the AWS network. Despite these measures, a recent security audit discovered that the S3 bucket containing the training data is accessible from an IP address outside the company's network. Upon investigation, it was found that the bucket policy allowed access from any IP address due to a misconfigured bucket policy. Which corrective action should the company take to prevent this issue from recurring?