Amazon Bedrock is a powerful AI service, and managing access securely is crucial for organizations utilizing its capabilities. In Part 1, we explored data protection and encryption in Amazon Bedrock, covering how to secure sensitive data and ensure compliance.
AWS Identity and Access Management (IAM) enables fine-grained control over authentication and authorization for Amazon Bedrock resources. This guide explores how IAM works with Amazon Bedrock and provides best practices for securing access.
IAM Roles and Responsibilities
1. Service Users
Service users interact with Amazon Bedrock for various AI-driven tasks. These users require permissions to perform specific actions, such as invoking models or managing data. If a service user encounters access restrictions, they must contact an IAM administrator to request necessary permissions.
2. Service Administrators
Administrators manage Amazon Bedrock resources and determine access permissions for service users. They work with IAM administrators to implement access policies that align with organizational security requirements.
3. IAM Administrators
IAM administrators configure identity-based policies and define permissions for Amazon Bedrock users. They manage roles, resource access, and permissions boundaries to enforce security best practices.
Authentication and Access Control
1. Authentication Methods
Users authenticate using one of the following methods:
AWS Root User: Provides full access but should only be used for critical administrative tasks.
IAM Users and Groups: Assigns specific permissions to individuals or groups.
Federated Identities: Uses external authentication providers such as AWS IAM Identity Center (formerly AWS SSO).
IAM Roles: Grants temporary permissions for cross-account access or application access to AWS resources.
2. Managing Access with IAM Policies
IAM policies define what actions users and roles can perform on Amazon Bedrock resources. AWS supports the following policy types:
Identity-Based Policies: Attach policies to IAM users, groups, or roles to control access.
Resource-Based Policies: Not supported for Amazon Bedrock.
Access Control Lists (ACLs): Not supported for Amazon Bedrock.
Attribute-Based Access Control (ABAC): Uses tags to control access dynamically.
Permissions Boundaries: Sets limits on the maximum permissions granted to users.
Service Control Policies (SCPs): Used within AWS Organizations to restrict permissions.
Session Policies: Temporarily define permissions for federated users.
3. Policy Actions and Resources
Administrators can specify permissions using JSON policies. Actions in policies use the bedrock: prefix. Example actions include:
"Action": [
"bedrock:InvokeModel",
"bedrock:ListFoundationModels"
]
Resource-based permissions use Amazon Resource Names (ARNs) to define access scope:
"Resource": "arn:aws:bedrock:aws-region:111122223333:provisioned-model/my-provisioned-model"
IAM Best Practices for Amazon Bedrock
1. Implement Least-Privilege Access
Grant only the minimum permissions required for users to perform their tasks. Use AWS-managed policies such as AmazonBedrockReadOnly for read-only access and AmazonBedrockFullAccess for administrative control.
2. Use Multi-Factor Authentication (MFA)
Enable MFA for IAM users and enforce it for privileged actions.
3. Monitor and Audit IAM Activity
Use AWS CloudTrail and IAM Access Analyzer to track changes and detect unauthorized access attempts.
4. Use Temporary Credentials
Avoid long-term access keys by using IAM roles and temporary security credentials.
5. Implement Role-Based Access Control (RBAC)
Define IAM roles with specific permissions for different user groups, such as data scientists, engineers, and administrators.
Example IAM Policies for Amazon Bedrock
1. Allow a User to View Their Own Permissions
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"iam:GetUserPolicy",
"iam:ListGroupsForUser",
"iam:ListAttachedUserPolicies",
"iam:ListUserPolicies",
"iam:GetUser"
],
"Resource": "arn:aws:iam::*:user/${aws:username}"
}
]
}
2. Deny Access to Model Inference
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Deny",
"Action": [
"bedrock:InvokeModel"
],
"Resource": "arn:aws:bedrock:*::foundation-model/*"
}
]
}
3. Allow Role-Based Model Invocation
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": "bedrock:InvokeModel",
"Resource": "arn:aws:bedrock:aws-region:111122223333:provisioned-model/my-provisioned-model"
}
]
}
Conclusion
Managing IAM for Amazon Bedrock is essential for maintaining security and compliance. By following best practices, implementing least-privilege access, and leveraging AWS-managed policies, organizations can ensure secure and efficient use of Amazon Bedrock. For further details, consult the AWS IAM User Guide.
Have questions or want to dive deeper? Reach out on LinkedIn or drop a comment below!
