Tag Archives: Security Blog

IAM policy types: How and when to use them

2022-06-03 Matt Luttrell

Post Syndicated from Matt Luttrell original https://aws.amazon.com/blogs/security/iam-policy-types-how-and-when-to-use-them/

You manage access in AWS by creating policies and attaching them to AWS Identity and Access Management (IAM) principals (roles, users, or groups of users) or AWS resources. AWS evaluates these policies when an IAM principal makes a request, such as uploading an object to an Amazon Simple Storage Service (Amazon S3) bucket. Permissions in the policies determine whether the request is allowed or denied.

In this blog post, we will walk you through a scenario and explain when you should use which policy type, and who should own and manage the policy. You will learn when to use the more common policy types: identity-based policies, resource-based policies, permissions boundaries, and AWS Organizations service control policies (SCPs).

Different policy types and when to use them

AWS has different policy types that provide you with powerful flexibility, and it’s important to know how and when to use each policy type. It’s also important for you to understand how to structure your IAM policy ownership to avoid a centralized team from becoming a bottleneck. Explicit policy ownership can allow your teams to move more quickly, while staying within the secure guardrails that are defined centrally.

Service control policies overview

Service control policies (SCPs) are a feature of AWS Organizations. AWS Organizations is a service for grouping and centrally managing the AWS accounts that your business owns. SCPs are policies that specify the maximum permissions for an organization, organizational unit (OU), or an individual account. An SCP can limit permissions for principals in member accounts, including the AWS account root user.

SCPs are meant to be used as coarse-grained guardrails, and they don’t directly grant access. The primary function of SCPs is to enforce security invariants across AWS accounts and OUs in an organization. Security invariants are control objectives or configurations that you apply to multiple accounts, OUs, or the whole AWS organization. For example, you can use an SCP to prevent member accounts from leaving your organization or to enforce that AWS resources can only be deployed to certain Regions.

Permissions boundaries overview

Permissions boundaries are an advanced IAM feature in which you set the maximum permissions that an identity-based policy can grant to an IAM principal. When you set a permissions boundary for a principal, the principal can perform only the actions that are allowed by both its identity-based policies and its permissions boundaries.

A permissions boundary is a type of identity-based policy that doesn’t directly grant access. Instead, like an SCP, a permissions boundary acts as a guardrail for your IAM principals that allows you to set coarse-grained access controls. A permissions boundary is typically used to delegate the creation of IAM principals. Delegation enables other individuals in your accounts to create new IAM principals, but limits the permissions that can be granted to the new IAM principals.

Identity-based policies overview

Identity-based policies are policy documents that you attach to a principal (roles, users, and groups of users) to control what actions a principal can perform, on which resources, and under what conditions. Identity-based policies can be further categorized into AWS managed policies, customer managed policies, and inline policies. AWS managed policies are reusable identity-based policies that are created and managed by AWS. You can use AWS managed policies as a starting point for building your own identity-based policies that are specific to your organization. Customer managed policies are reusable identity-based policies that can be attached to multiple identities. Customer managed policies are useful when you have multiple principals with identical access requirements. Inline policies are identity-based policies that are attached to a single principal. Use inline-policies when you want to create least-privilege permissions that are specific to a particular principal.

You will have many identity-based policies in your AWS account that are used to enable access in scenarios such as human access, application access, machine learning workloads, and deployment pipelines. These policies should be fine-grained. You use these policies to directly apply least privilege permissions to your IAM principals. You should write the policies with permissions for the specific task that the principal needs to accomplish.

Resource-based policies overview

Resource-based policies are policy documents that you attach to a resource such as an S3 bucket. These policies grant the specified principal permission to perform specific actions on that resource and define under what conditions this permission applies. Resource-based policies are inline policies. For a list of AWS services that support resource-based policies, see AWS services that work with IAM.

Resource-based policies are optional for many workloads that don’t span multiple AWS accounts. Fine-grained access within a single AWS account is typically granted with identity-based policies. AWS Key Management Service (AWS KMS) keys and IAM role trust policies are two exceptions, and both of these resources must have a resource-based policy even when the principal and the KMS key or IAM role are in the same account. IAM roles and KMS keys behave this way as an extra layer of protection that requires the owner of the resource (key or role) to explicitly allow or deny principals from using the resource. For other resources that support resource-based policies, here are some use cases where they are most commonly used:

Granting cross-account access to your AWS resource.
Granting an AWS service access to your resource when the AWS service uses an AWS service principal. For example, when using AWS CloudTrail, you must explicitly grant the CloudTrail service principal access to write files to an Amazon S3 bucket.
Applying broad access guardrails to your AWS resources. You can see some examples in the blog post IAM makes it easier for you to manage permissions for AWS services accessing your resources.
Applying an additional layer of protection for resources that store sensitive data, such as AWS Secrets Manager secrets or an S3 bucket with sensitive data. You can use a resource-based policy to deny access to IAM principals that shouldn’t have access to sensitive data, even if granted access by an identity-based policy. An explicit deny in an IAM policy always overrides an allow.

How to implement different policy types

In this section, we will walk you through an example of a design that includes all four of the policy types explained in this post.

The example that follows shows an application that runs on an Amazon Elastic Compute Cloud (Amazon EC2) instance and needs to read from and write files to an S3 bucket in the same account. The application also reads (but doesn’t write) files from an S3 bucket in a different account. The company in this example, Example Corp, uses a multi-account strategy, and each application has its own AWS account. The architecture of the application is shown in Figure 1.

Figure 1: Sample application architecture that needs to access S3 buckets in two different AWS accounts

There are three teams that participate in this example: the Central Cloud Team, the Application Team, and the Data Lake Team. The Central Cloud Team is responsible for the overall security and governance of the AWS environment across all AWS accounts at Example Corp. The Application Team is responsible for building, deploying, and running their application within the application account (111111111111) that they own and manage. Likewise, the Data Lake Team owns and manages the data lake account (222222222222) that hosts a data lake at Example Corp.

With that background in mind, we will walk you through an implementation for each of the four policy types and include an explanation of which team we recommend own each policy. The policy owner is the team that is responsible for creating and maintaining the policy.

Service control policies

The Central Cloud Team owns the implementation of the security controls that should apply broadly to all of Example Corp’s AWS accounts. At Example Corp, the Central Cloud Team has two security requirements that they want to apply to all accounts in their organization:

All AWS API calls must be encrypted in transit.
Accounts can’t leave the organization on their own.

The Central Cloud Team chooses to implement these security invariants using SCPs and applies the SCPs to the root of the organization. The first statement in Policy 1 denies all requests that are not sent using SSL (TLS). The second statement in Policy 1 prevents an account from leaving the organization.

This is only a subset of the SCP statements that Example Corp uses. Example Corp uses a deny list strategy, and there must also be an accompanying statement with an Effect of Allow at every level of the organization that isn’t shown in the SCP in Policy 1.

Policy 1: SCP attached to AWS Organizations organization root

{
    "Id": "ServiceControlPolicy",
    "Version": "2012-10-17",
    "Statement": [{
        "Sid": "DenyIfRequestIsNotUsingSSL",    
        "Effect": "Deny",    
        "Action": "*",    
        "Resource": "*",    
        "Condition": {
            "BoolIfExists": {
                "aws:SecureTransport": "false"        
            }
        }
    },
    {
        "Sid": "PreventLeavingTheOrganization",
        "Effect": "Deny",
        "Action": "organizations:LeaveOrganization",
        "Resource": "*"
    }]
}

Permissions boundary policies

The Central Cloud Team wants to make sure that they don’t become a bottleneck for the Application Team. They want to allow the Application Team to deploy their own IAM principals and policies for their applications. The Central Cloud Team also wants to make sure that any principals created by the Application Team can only use AWS APIs that the Central Cloud Team has approved.

At Example Corp, the Application Team deploys to their production AWS environment through a continuous integration/continuous deployment (CI/CD) pipeline. The pipeline itself has broad access to create AWS resources needed to run applications, including permissions to create additional IAM roles. The Central Cloud Team implements a control that requires that all IAM roles created by the pipeline must have a permissions boundary attached. This allows the pipeline to create additional IAM roles, but limits the permissions that the newly created roles can have to what is allowed by the permissions boundary. This delegation strikes a balance for the Central Cloud Team. They can avoid becoming a bottleneck to the Application Team by allowing the Application Team to create their own IAM roles and policies, while ensuring that those IAM roles and policies are not overly privileged.

An example of the permissions boundary policy that the Central Cloud Team attaches to IAM roles created by the CI/CD pipeline is shown below. This same permissions boundary policy can be centrally managed and attached to IAM roles created by other pipelines at Example Corp. The policy describes the maximum possible permissions that additional roles created by the Application Team are allowed to have, and it limits those permissions to some Amazon S3 and Amazon Simple Queue Service (Amazon SQS) data access actions. It’s common for a permissions boundary policy to include data access actions when used to delegate role creation. This is because most applications only need permissions to read and write data (for example, writing an object to an S3 bucket or reading a message from an SQS queue) and only sometimes need permission to modify infrastructure (for example, creating an S3 bucket or deleting an SQS queue). As Example Corp adopts additional AWS services, the Central Cloud Team updates this permissions boundary with actions from those services.

Policy 2: Permissions boundary policy attached to IAM roles created by the CI/CD pipeline

{
    "Id": "PermissionsBoundaryPolicy",
    "Version": "2012-10-17",
    "Statement": [{   
        "Effect": "Allow",    
        "Action": [
            "s3:PutObject",
            "s3:GetObject",
            "sqs:ChangeMessageVisibility",
            "sqs:DeleteMessage",
            "sqs:ReceiveMessage",
            "sqs:SendMessage",
            "sqs:PurgeQueue",
            "sqs:GetQueueUrl",
            "logs:PutLogEvents"        
         ],    
        "Resource": "*"
    }]
}

In the next section, you will learn how to enforce that this permissions boundary is attached to IAM roles created by your CI/CD pipeline.

Identity-based policies

In this example, teams at Example Corp are only allowed to modify the production AWS environment through their CI/CD pipeline. Write access to the production environment is not allowed otherwise. To support the different personas that need to have access to an application account in Example Corp, three baseline IAM roles with identity-based policies are created in the application accounts:

A role for the CI/CD pipeline to use to deploy application resources.
A read-only role for the Central Cloud Team, with a process for temporary elevated access.
A read-only role for members of the Application Team.

All three of these baseline roles are owned, managed, and deployed by the Central Cloud Team.

The Central Cloud Team is given a default read-only role (CentralCloudTeamReadonlyRole) that allows read access to all resources within the account. This is accomplished by attaching the AWS managed ReadOnlyAccess policy to the Central Cloud Team role. You can use the IAM console to attach the ReadOnlyAccess policy, which grants read-only access to all services. When a member of the team needs to perform an action that is not covered by this policy, they follow a temporary elevated access process to make sure that this access is valid and recorded.

A read-only role is also given to developers in the Application Team (DeveloperReadOnlyRole) for analysis and troubleshooting. At Example Corp, developers are allowed to have read-only access to Amazon EC2, Amazon S3, Amazon SQS, AWS CloudFormation, and Amazon CloudWatch. Your requirements for read-only access might differ. Several AWS services offer their own read-only managed policies, and there is also the previously mentioned AWS managed ReadOnlyAccess policy that grants read only access to all services. To customize read-only access in an identity-based policy, you can use the AWS managed policies as a starting point and limit the actions to the services that your organization uses. The customized identity-based policy for Example Corp’s DeveloperReadOnlyRole role is shown below.

Policy 3: Identity-based policy attached to a developer read-only role to support human access and troubleshooting

{
    "Id": "DeveloperRoleBaselinePolicy",
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "cloudformation:Describe*",
                "cloudformation:Get*",
                "cloudformation:List*",
                "cloudwatch:Describe*",
                "cloudwatch:Get*",
                "cloudwatch:List*",
                "ec2:Describe*",
                "ec2:Get*",
                "ec2:List*",
                "ec2:Search*",
                "s3:Describe*",
                "s3:Get*",
                "s3:List*",
                "sqs:Get*",
                "sqs:List*",
                "logs:Describe*",
                "logs:FilterLogEvents",
                "logs:Get*",
                "logs:List*",
                "logs:StartQuery",
                "logs:StopQuery"
            ],
            "Resource": "*"
        }
    ]
}

The CI/CD pipeline role has broad access to the account to create resources. Access to deploy through the CI/CD pipeline should be tightly controlled and monitored. The CI/CD pipeline is allowed to create new IAM roles for use with the application, but those roles are limited to only the actions allowed by the previously discussed permissions boundary. The roles, policies, and EC2 instance profiles that the pipeline creates should also be restricted to specific role paths. This enables you to enforce that the pipeline can only modify roles and policies or pass roles that it has created. This helps prevent the pipeline, and roles created by the pipeline, from elevating privileges by modifying or passing a more privileged role. Pay careful attention to the role and policy paths in the Resource element of the following CI/CD pipeline role policy (Policy 4). The CI/CD pipeline role policy also provides some example statements that allow the passing and creation of a limited set of service-linked roles (which are created in the path /aws-service-role/). You can add other service-linked roles to these statements as your organization adopts additional AWS services.

Policy 4: Identity-based policy attached to CI/CD pipeline role

{
    "Id": "CICDPipelineBaselinePolicy",
    "Version": "2012-10-17",
    "Statement": [{
        "Effect": "Allow",    
        "Action": [
            "ec2:*",
            "sqs:*",
            "s3:*",
            "cloudwatch:*",
            "cloudformation:*",
            "logs:*",
            "autoscaling:*"           
        ],
        "Resource": "*"
    },
    {
        "Effect": "Allow",
        "Action": "ssm:GetParameter*",
        "Resource": "arn:aws:ssm:*::parameter/aws/service/*"
    },
    {
        "Effect": "Allow",
        "Action": [
            "iam:CreateRole",
            "iam:PutRolePolicy",
            "iam:DeleteRolePolicy"
        ],
        "Resource": "arn:aws:iam::111111111111:role/application-roles/*",
        "Condition": {
            "ArnEquals": {
                "iam:PermissionsBoundary": "arn:aws:iam::111111111111:policy/PermissionsBoundary"
            }            
        }
    }, 
    {
        "Effect": "Allow",
        "Action": [
            "iam:AttachRolePolicy",
            "iam:DetachRolePolicy"
        ],
        "Resource": "arn:aws:iam::111111111111:role/application-roles/*",
        "Condition": {
            "ArnEquals": {
                "iam:PermissionsBoundary": "arn:aws:iam::111111111111:policy/PermissionsBoundary"
            },
            "ArnLike": {
                "iam:PolicyARN": "arn:aws:iam::111111111111:policy/application-role-policies/*"
            }          
        }
    }, 
    {
        "Effect": "Allow",
        "Action": [
            "iam:DeleteRole",
            "iam:TagRole",
            "iam:UntagRole",
            "iam:GetRole",
            "iam:GetRolePolicy"
        ],
        "Resource": "arn:aws:iam::111111111111:role/application-roles/*"
    },
      
    {
        "Effect": "Allow",
        "Action": [
            "iam:CreatePolicy",
            "iam:DeletePolicy",
            "iam:CreatePolicyVersion",            
            "iam:DeletePolicyVersion",
            "iam:GetPolicy",
            "iam:TagPolicy",
            "iam:UntagPolicy",
            "iam:SetDefaultPolicyVersion",
            "iam:ListPolicyVersions"
         ],
        "Resource": "arn:aws:iam::111111111111:policy/application-role-policies/*"
    },
    {
        "Effect": "Allow",
        "Action": [
            "iam:CreateInstanceProfile",
            "iam:AddRoleToInstanceProfile",
            "iam:RemoveRoleFromInstanceProfile",
            "iam:DeleteInstanceProfile"
        ],
        "Resource": "arn:aws:iam::111111111111:instance-profile/application-instance-profiles/*"
    },
    {
        "Effect": "Allow",
        "Action": "iam:PassRole",
        "Resource": [
            "arn:aws:iam::111111111111:role/application-roles/*",
            "arn:aws:iam::111111111111:role/aws-service-role/autoscaling.amazonaws.com/AWSServiceRoleForAutoScaling*"
        ]
    },
    {
        "Effect": "Allow",
        "Action": "iam:CreateServiceLinkedRole",
        "Resource": "arn:aws:iam::111111111111:role/aws-service-role/*",
        "Condition": {
            "StringEquals": {
                "iam:AWSServiceName": "autoscaling.amazonaws.com"
            }
        }
    },
    {
        "Effect": "Allow",
        "Action": [
            "iam:DeleteServiceLinkedRole",
            "iam:GetServiceLinkedRoleDeletionStatus"
        ],
        "Resource": "arn:aws:iam::111111111111:role/aws-service-role/autoscaling.amazonaws.com/AWSServiceRoleForAutoScaling*"
    },
    {
        "Effect": "Allow",
        "Action": "iam:ListRoles",
        "Resource": "*"
    },
    {
        "Effect": "Allow",
        "Action": "iam:GetRole",
        "Resource": [
            "arn:aws:iam::111111111111:role/application-roles/*",
            "arn:aws:iam::111111111111:role/aws-service-role/*"
        ]
    }]
}

In addition to the three baseline roles with identity-based policies in place that you’ve seen so far, there’s one additional IAM role that the Application Team creates using the CI/CD pipeline. This is the role that the application running on the EC2 instance will use to get and put objects from the S3 buckets in Figure 1. Explicit ownership allows the Application Team to create this identity-based policy that fits their needs without having to wait and depend on the Central Cloud Team. Because the CI/CD pipeline can only create roles that have the permissions boundary policy attached, Policy 5 cannot grant more access than the permissions boundary policy allows (Policy 2).

If you compare the identity-based policy attached to the EC2 instance’s role (Policy 5 on left) with the permissions boundary policy described previously (Policy 2 on the right), you can see that the actions allowed by the EC2 instance’s role are also allowed by the permissions boundary policy. Actions must be allowed by both policies for the EC2 instance to perform the s3:GetObject and s3:PutObject actions. Access to create a bucket would be denied even if the role attached to the EC2 instance was given permission to perform the s3:CreateBucket action because the s3:CreateBucket action exceeds the permissions allowed by the permissions boundary.

Policy 5: Identity-based policy bound by permissions boundary and attached to the application’s EC2 instance

{
"Id": "ApplicationRolePolicy",
"Version": "2012-10-17",
"Statement": [{   
 "Effect": "Allow",    
 "Action": [
    "s3:PutObject",
    "s3:GetObject"
 ],    
 "Resource": "arn:aws:s3:::DOC-EXAMPLE-
 BUCKET1/*"
},
{   
 "Effect": "Allow",    
 "Action": [
    "s3:GetObject"
 ],    
 "Resource": "arn:aws:s3:::DOC-EXAMPLE-
 BUCKET2/*"
}]
}

Policy 2: Permissions boundary policy attached to IAM roles created by the CI/CD pipeline.

{
    "Id": "PermissionsBoundaryPolicy"
    "Version": "2012-10-17",
    "Statement": [{   
        "Effect": "Allow",    
        "Action": [
            "s3:PutObject",
            "s3:GetObject",
            "sqs:ChangeMessageVisibility",
            "sqs:DeleteMessage",
            "sqs:ReceiveMessage",
            "sqs:SendMessage",
            "sqs:PurgeQueue",
            "sqs:GetQueueUrl",
            "logs:PutLogEvents"        
         ],    
        "Resource": "*"
    }]
}

Resource-based policies

The only resource-based policy needed in this example is attached to the bucket in the account external to the application account (DOC-EXAMPLE-BUCKET2 in the data lake account in Figure 1). Both the identity-based policy and resource-based policy must grant access to an action on the S3 bucket for access to be allowed in a cross-account scenario. The bucket policy below only allows the GetObject action to be performed on the bucket, regardless of what permissions the application’s role (ApplicationRole) is granted from its identity-based policy (Policy 5).

This resource-based policy is owned by the Data Lake Team that owns and manages the data lake account (222222222222) and the policy (Policy 6). This allows the Data Lake Team to have complete control over what teams external to their AWS account can access their S3 bucket.

Policy 6: Resource-based policy attached to S3 bucket in external data lake account (222222222222)

{
    "Version": "2012-10-17",
    "Statement": [{
        "Principal": {
            "AWS": "arn:aws:iam::111111111111:role/application-roles/ApplicationRole"
        },
        "Effect": "Allow",    
        "Action": [
            "s3:GetObject"
        ],    
        "Resource": "arn:aws:s3:::DOC-EXAMPLE-BUCKET2/*"
    }]
}

No resource-based policy is needed on the S3 bucket in the application account (DOC-EXAMPLE-BUCKET1 in Figure 1). Access for the application is granted to the S3 bucket in the application account by the identity-based policy on its own. Access can be granted by either an identity-based policy or a resource-based policy when access is within the same AWS account.

Putting it all together

Figure 2 shows the architecture and includes the seven different policies and the resources they are attached to. The table that follows summarizes the various IAM policies that are deployed to the Example Corp AWS environment, and specifies what team is responsible for each of the policies.

Figure 2: Sample application architecture with CI/CD pipeline used to deploy infrastructure

The numbered policies in Figure 2 correspond to the policy numbers in the following table.

Policy number	Policy description	Policy type	Policy owner	Attached to
1	Enforce SSL and prevent member accounts from leaving the organization for all principals in the organization	Service control policy (SCP)	Central Cloud Team	Organization root
2	Restrict maximum permissions for roles created by CI/CD pipeline	Permissions boundary	Central Cloud Team	All roles created by the pipeline (ApplicationRole)
3	Scoped read-only policy	Identity-based policy	Central Cloud Team	DeveloperReadOnlyRole IAM role
4	CI/CD pipeline policy	Identity-based policy	Central Cloud Team	CICDPipelineRole IAM role
5	Policy used by running application to read and write to S3 buckets	Identity-based policy	Application Team	ApplicationRole on EC2 instance
6	Bucket policy in data lake account that grants access to a role in application account	Resource-based policy	Data Lake Team	S3 Bucket in data lake account
7	Broad read-only policy	Identity-based policy	Central Cloud Team	CentralCloudTeamReadonlyRole IAM role

Conclusion

In this blog post, you learned about four different policy types: identity-based policies, resource-based policies, service control policies (SCPs), and permissions boundary policies. You saw examples of situations where each policy type is commonly applied. Then, you walked through a real-life example that describes an implementation that uses these policy types.

You can use this blog post as a starting point for developing your organization’s IAM strategy. You might decide that you don’t need all of the policy types explained in this post, and that’s OK. Not every organization needs to use every policy type. You might need to implement policies differently in a production environment than a sandbox environment. The important concepts to take away from this post are the situations where each policy type is applicable, and the importance of explicit policy ownership. We also recommend taking advantage of policy validation in AWS IAM Access Analyzer when writing IAM policies to validate your policies against IAM policy grammar and best practices.

For more information, including the policies described in this solution and the sample application, see the how-and-when-to-use-aws-iam-policy-blog-samples GitHub respository. The repository walks through an example implementation using a CI/CD pipeline with AWS CodePipeline.

If you have any questions, please post them in the AWS Identity and Access Management re:Post topic or reach out to AWS Support.

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Correlate IAM Access Analyzer findings with Amazon Macie

2022-06-03 Nihar Das

Post Syndicated from Nihar Das original https://aws.amazon.com/blogs/security/correlate-iam-access-analyzer-findings-with-amazon-macie/

In this blog post, you’ll learn how to detect when unintended access has been granted to sensitive data in Amazon Simple Storage Service (Amazon S3) buckets in your Amazon Web Services (AWS) accounts.

It’s critical for your enterprise to understand where sensitive data is stored in your organization and how and why it is shared. The ability to efficiently find data that is shared with entities outside your account and the contents of that data is paramount. You need a process to quickly detect and report which accounts have access to sensitive data. Amazon Macie is an AWS service that can detect many sensitive data types. Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and help protect your sensitive data in AWS.

AWS Identity and Access Management (IAM) Access Analyzer helps to identify resources in your organization and accounts, such as S3 buckets or IAM roles, that are shared with an external entity. When you enable IAM Access Analyzer, you create an analyzer for your entire organization or your account. The organization or account you choose is known as the zone of trust for the analyzer. The analyzer monitors the supported resources within your zone of trust. This analyzer enables IAM Access Analyzer to detect each instance of a resource shared outside the zone of trust and generates a finding about the resource and the external principals that have access to it.

Currently, you can use IAM Access Analyzer and Macie to detect external access and discover sensitive data as separate processes. You can join the findings from both to best evaluate the risk. The solution in this post integrates IAM Access Analyzer, Macie, and AWS Security Hub to automate the process of correlating findings between the services and presenting them in Security Hub.

How does the solution work?

First, IAM Access Analyzer discovers S3 buckets that are shared outside the zone of trust. Next, the solution schedules a Macie sensitive data discovery job for each of these buckets to determine if the bucket contains sensitive data. Upon discovery of shared sensitive data in S3, a custom high severity finding is created in Security Hub for review and incident response.

Solution architecture

This solution is based on a serverless architecture, and uses the following services:

AWS Lambda is used to run code
AWS Step Functions orchestrates the workflow steps
Amazon EventBridge triggers the workflows
Amazon DynamoDB stores findings data to reduce the time to deploy and operational overhead
IAM Access Analyzer detects S3 buckets that are shared with external entities
Macie uses machine learning and pattern matching to discover sensitive data in S3 buckets
Security Hub displays the reported results

Figure 1: Architecture diagram

Figure 1 depicts the following process flow:

IAM Access Analyzer detects shared S3 buckets outside of the zone of trust—the organization or account you choose is known as a zone of trust for the analyzer—and creates the event Access Analyzer Finding in EventBridge.
EventBridge triggers the Lambda function sda-aa-save-findings.
The sda-aa-save-findings function records each finding in DynamoDB.
An EventBridge scheduled event periodically starts a new cycle of the Step Function state machine, which immediately runs the Lambda function sda-macie-submit-scan. The template sets a 15-minute interval, but this is configurable.
The sda-macie-submit-scan function reads the IAM Access Analyzer findings that were created by sda-aa-save-findings from DynamoDB.
sda-macie-submit-scan launches a Macie classification job for each distinct S3 bucket that is related to one or more recent IAM Access Analyzer findings.
Macie performs a sensitive discovery scan on each requested S3 bucket.
The sda-macie-submit-scan function initiates the Lambda function sda-macie-check-status.
sda-macie-check-status periodically checks the status of each Macie classification job, waiting for all the Macie jobs initiated by this solution to complete.
Upon completion of the sda-macie-check-status function, the step function runs the Lambda function sda-sh-create-findings.
sda-sh-create-findings joins the resulting IAM Access Analyzer and Macie datasets for each S3 bucket.
sda-sh-create-findings publishes a finding to Security Hub for each bucket that has both external access and sensitive data.

Note: The Macie scan is skipped if the S3 bucket is tagged to be excluded or if it was recently scanned by Macie. See the Cost considerations section for more information on custom configurations.
Information security can review and act on the findings shown in Security Hub.

Sample Security Hub output

Figure 2 shows the sample findings that Security Hub will present. Each finding includes:

Severity
Workflow status
Record state
Company
Product
Title
Resource

Figure 2: Sample Security Hub findings

The output to Security Hub will display a severity of HIGH with workflow NEW, because this is the first time the event has been observed. The record state is ACTIVE because the workflow state is NEW. The title explains the reason for the event.

For example, if potentially sensitive data is discovered in a bucket that is shared outside a zone of trust, selecting an event will display the resources involved in the finding so you can investigate. For more information, see the Security Hub User Guide.

Notes:

Detection of public S3 buckets by IAM Access Analyzer will still occur through Security Hub and will be marked as critical severity. This solution does not add to or augment this finding in Security Hub.

If a finding in IAM Access Analyzer is archived, the solution does not update the related finding in Security Hub.

Prerequisites

To use this solution, you need the following:

Permission to run AWS CloudFormation
Permission to create Lambda functions
Permission to create DynamoDB tables
Permission to create Step Function state machines
Permission to create EventBridge event rules
Permission to enable IAM Access Analyzer on the account where sensitive discovery is required
Permission to enable Macie on the account
Permission to enable Security Hub on the account

Deploy the solution

The solution is deployed through AWS CloudFormation, and you can review the template for options to best suit your specific needs.

Sign in to your AWS account located at https://aws.amazon.com/console/.
In the AWS Management Console, navigate to the AWS CloudFormation service, and then choose Create stack.
Under Prerequisite – Prepare template, choose Template is ready.
Under Specify template, choose Amazon S3 URL and provide the following URL:
https://awsiammedia.s3.amazonaws.com/public/sample/936-correlating-aa-findings-macie/sda-cfn.yml
Choose Next.
Enter the stack name.
The Application code location, S3 Bucket and S3 Key fields will be pre-filled.
Under Service Activations, modify the activations based on the services you presently have running in your account.
Modify the Logging and Monitoring settings if required.
(Optional) Set an alert email address for errors.
Choose Next, then choose Next again.
Under Capabilities, select the check box.
Choose Create Stack. The solution will begin deploying; watch for the CREATE_COMPLETE message.

Figure 3: Sample CloudFormation deployment status

The solution is now deployed and will start monitoring for sensitive data that is being shared. It will send the findings to Security Hub for your teams to investigate.

Cost considerations

When you scan large S3 buckets with sensitive data, remember that Macie cost is based on the amount of data scanned. For more information on Macie costs, see Amazon Macie pricing.

This solution allows the following options, which you can use to help manage costs:

Use environment variables in Lambda to skip specific tagged buckets
Skip recently scanned S3 buckets and reuse prior findings

Figure 4: Screen shot of configurable environment variable

Conclusion

In this post, we discussed how the solution uses Lambda, Step Functions and EventBridge to integrate IAM Access Analyzer with Macie discovery jobs. We reviewed the components of the application, deployed it by using CloudFormation, and reviewed the output a security team would use to take the appropriate actions. We also provided two ways that you can manage the costs associated with the solution.

After you deploy this project, you can modify it to meet your organization’s needs. For example, you can modify the tags to skip specific S3 buckets your organization has already classified to hold sensitive data. Customers who use multiple AWS accounts can designate a centralized Security Hub administrator account to receive the solution alerts from each member account. For more information on this option, see Designating a Security Hub administrator account.

If you have feedback about this post, please submit it in the Comments section below. If you have questions about this post, please start a new thread on the AWS Identity and Access Management forum.

Other resources

For more information on correlating security findings with AWS Security Hub and Amazon EventBridge, refer to this blog post.

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AWS CSA Consensus Assessment Initiative Questionnaire version 4 now available

2022-06-02 Sonali Vaidya

Post Syndicated from Sonali Vaidya original https://aws.amazon.com/blogs/security/aws-csa-consensus-assessment-initiative-questionnaire-version-4-now-available/

Amazon Web Services (AWS) has published an updated version of the AWS Cloud Security Alliance (CSA) Consensus Assessment Initiative Questionnaire (CAIQ). The questionnaire has been completed using the current CSA CAIQ standard, v4.0.2 (06.07.2021 update), and is now available for download.

The CSA is a not-for-profit organization dedicated to “defining and raising awareness of best practices to help ensure a secure cloud computing environment.” For more information, see the Cloud Security Alliance website. A wide range of industry security practitioners, corporations, and associations participate in CSA.

What is CSA CAIQ and how can you use it?

The CSA Consensus Assessments Initiative Questionnaire provides a set of questions that CSA anticipates a cloud consumer or a cloud auditor would ask of a cloud provider. The AWS CSA CAIQ provides the AWS control implementation descriptions for a series of cloud-specific security questions based on the Cloud Controls Matrix (CCM). The AWS CSA CAIQ also reflects the AWS customer responsibilities according to the shared responsibility model, which can help customers comply with the CSA CCM.

At AWS, we’re committed to helping you achieve and maintain the highest standards of security and compliance. We value your feedback and questions. You can contact the AWS HITRUST team at AWS Compliance Contact Us. If you have feedback about this post, submit comments in the Comments section below.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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AWS Security Profile: CJ Moses, CISO of AWS

2022-06-02 Maddie Bacon

Post Syndicated from Maddie Bacon original https://aws.amazon.com/blogs/security/aws_security_profile_cj_moses_ciso_of_aws/

In the AWS Security Profile series, I interview the people who work in Amazon Web Services (AWS) Security and help keep our customers safe and secure. This interview is with CJ Moses—previously the AWS Deputy Chief Information Security Officer (CISO), he began his role as CISO of AWS in February of 2022.

How did you get started in security? What about it piqued your interest?

I was serving in the United States Air Force (USAF), attached to the 552nd Airborne Warning and Control (AWACS) Wing, when my father became ill. The USAF reassigned me to McGuire Air Force Base (AFB) in New Jersey so that I’d be closer to him in New York. Because I was an unplanned resource, they added me to the squadron responsible for base communications. I ended up being the Base CompuSec (Computer Security) Manager, who was essentially the person who had to figure out what a firewall was and how to install it. That role required me to have a lot of interaction with the Air Force Office of Special Investigations (AFOSI), which led to me being recruited as a Computer Crime Investigator (CCI). Normally, when I’m asked what kind of plan I followed to get where I am today, I like to say, one modeled after Forrest Gump.

How has your time in the Air Force influenced your approach to cybersecurity?

It provided a strong foundation that I’ve built on with each and every experience since. My years as a CCI had me chasing hackers around the world on what was the “Wild West” of the internet. I’ve been kicked out of countries, asked (told) never to come back to others, but in the end the thing that stuck is that there is always a human on the other side of the connection. Keyboards don’t type for themselves, and therefore understanding your opponent and their intent will inform the measures you must put in place to deal with them. In the early days, we were investigating Advanced Persistent Threats (APTs) long before anyone had created that acronym, or given the actors names or fancy number designators. I like to use that experience to humanize the threats we face.

You were recently promoted to CISO of AWS. What are you most excited about in your new role?

I’m most excited by the team we have at AWS, not only the security team I’m inheriting, but also across AWS. As a CISO, it’s a dream to have an organization that truly believes security is the top priority, which is what we have at AWS. This company has a strong culture of ownership, which allows the security team to partner with the service owners to enable their business, rather than being the office of, “no, you can’t do that.” I prefer my team to answer questions with “Yes, but” or “Yes, and,” and then talk about how they can do what they need in a more secure manner.

What’s the most challenging part of being CISO?

There’s a right balance I’m working to find between how much time I’m able to spend focusing on the details and doing security, and communicating with customers about what we do. I lean on our Office of the CISO (OCISO) team to make sure we keep up a high level of customer engagement. I strive to keep the right balance between involvement in details, leading our security efforts, and engaging with our customers.

What’s your short- and long-term vision for AWS Security?

In the short term, my vision is to continue on the strong path that Steve Schmidt, former CISO of AWS and current chief security officer of Amazon, provided. In the longer term, I intend to further mechanize, automate, and scale our abilities, while increasing visibility and access for our customers.

If you could give one piece of advice to all AWS customers at scale, what would it be?

My advice to customers is to take advantage of the robust security services and resources we offer. We have a lot of content that is available for little to no cost, and an informed customer is less likely to encounter challenging security situations. Enabling Amazon GuardDuty on a customer’s account can be done with only a few clicks, and the threat detection monitoring it offers will provide organization-wide visibility and alerting.

What’s been the most dramatic change you’ve seen in the industry?

The most dramatic change I’ve seen is the elevated visibility of risk to the C-suite. These challenges used to be delegated lower in the organization to someone, maybe the CISO, who reported to the chief information officer. In companies that have evolved, you’ll find that the CISO reports to the CEO, with regular visibility to the board of directors. This prioritization of information security ensures the right level of ownership throughout the company.

Tell me about your work with military veterans. What drives your passion for this cause?

I’ve aligned with an organization, Operation Motorsport, that uses motorsports to engage with ill, injured, and wounded service members and disabled veterans. We present them with educational and industry opportunities to aid in their recovery and rehabilitation. Over the past few years we’ve sponsored a number of service members across our race teams, and I’ve personally seen the physical, and even more importantly, mental improvements for the beneficiaries who have become part of our race teams. Having started my military career during Operation Desert Shield/Storm (the buildup to and the first Gulf War), I can connect with these vets and help them to find a path and a new team to be part of.

If you had to pick any other industry, what would you want to do?

Professional motorsports. There is an incredible and not often visible alignment between the two industries. The use of data analytics (metrics focus), the culture, leadership principles, and overall drive to succeed are in complete alignment, and I’ve applied lessons learned between the two interchangeably.

What are you most proud of in your career?

I am very fortunate to come from rather humble beginnings and I’m appreciative of all the opportunities provided for me. Through those opportunities, I’ve had the chance to serve my country and, since joining AWS, to serve many customers across disparate industries and geographies. The ability to help people is something I’m passionate about, and I’m lucky enough to align my personal abilities with roles that I can use to leave the world a better place than I found it.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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Join me in Boston this July for AWS re:Inforce 2022

2022-06-01 CJ Moses

Post Syndicated from CJ Moses original https://aws.amazon.com/blogs/security/join-me-in-boston-this-july-for-aws-reinforce-2022/

I’d like to personally invite you to attend the Amazon Web Services (AWS) security conference, AWS re:Inforce 2022, in Boston, MA on July 26–27. This event offers interactive educational content to address your security, compliance, privacy, and identity management needs. Join security experts, customers, leaders, and partners from around the world who are committed to the highest security standards, and learn how to improve your security posture.

As the new Chief Information Security Officer of AWS, my primary job is to help our customers navigate their security journey while keeping the AWS environment safe. AWS re:Inforce offers an opportunity for you to understand how to keep pace with innovation in your business while you stay secure. With recent headlines around security and data privacy, this is your chance to learn the tactical and strategic lessons that will help keep your systems and tools secure, while you build a culture of security in your organization.

AWS re:Inforce 2022 will kick off with my keynote on Tuesday, July 26. I’ll be joined by Steve Schmidt, now the Chief Security Officer (CSO) of Amazon, and Kurt Kufeld, VP of AWS Platform. You’ll hear us talk about the latest innovations in cloud security from AWS and learn what you can do to foster a culture of security in your business. Take a look at the most recent re:Invent presentation, Continuous security improvement: Strategies and tactics, and the latest re:Inforce keynote for examples of the type of content to expect.

For those who are just getting started on AWS, as well as our more tenured customers, AWS re:Inforce offers an opportunity to learn how to prioritize your security investments. By using the Security pillar of the AWS Well-Architected Framework, sessions address how you can build practical and prescriptive measures to protect your data, systems, and assets.

Sessions are offered at all levels and for all backgrounds, from business to technical, and there are learning opportunities in over 300 sessions across five tracks: Data Protection & Privacy; Governance, Risk & Compliance; Identity & Access Management; Network & Infrastructure Security; and Threat Detection & Incident Response. In these sessions, connect with and learn from AWS experts, customers, and partners who will share actionable insights that you can apply in your everyday work. At AWS re:Inforce, the majority of our sessions are interactive, such as workshops, chalk talks, boot camps, and gamified learning, which provides opportunities to hear about and act upon best practices. Sessions will be available from the intermediate (200) through expert (400) levels, so you can grow your skills no matter where you are in your career. Finally, there will be a leadership session for each track, where AWS leaders will share best practices and trends in each of these areas.

At re:Inforce, hear directly from AWS developers and experts, who will cover the latest advancements in AWS security, compliance, privacy, and identity solutions—including actionable insights your business can use right now. Plus, you’ll learn from AWS customers and partners who are using AWS services in innovative ways to protect their data, achieve security at scale, and stay ahead of bad actors in this rapidly evolving security landscape.

A full conference pass is $1,099. However, if you register today with the code ALUMkpxagvkV you’ll receive a $300 discount (while supplies last).

We’re excited to get back to re:Inforce in person; it is emblematic of our commitment to giving customers direct access to the latest security research and trends. We’ll continue to release additional details about the event on our website, and you can get real-time updates by following @AWSSecurityInfo. I look forward to seeing you in Boston, sharing a bit more about my new role as CISO and providing insight into how we prioritize security at AWS.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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When and where to use IAM permissions boundaries

2022-06-01 Umair Rehmat

Post Syndicated from Umair Rehmat original https://aws.amazon.com/blogs/security/when-and-where-to-use-iam-permissions-boundaries/

Customers often ask for guidance on permissions boundaries in AWS Identity and Access Management (IAM) and when, where, and how to use them. A permissions boundary is an IAM feature that helps your centralized cloud IAM teams to safely empower your application developers to create new IAM roles and policies in Amazon Web Services (AWS). In this blog post, we cover this common use case for permissions boundaries, some best practices to consider, and a few things to avoid.

Background

Developers often need to create new IAM roles and policies for their applications because these applications need permissions to interact with AWS resources. For example, a developer will likely need to create an IAM role with the correct permissions for an Amazon Elastic Compute Cloud (Amazon EC2) instance to report logs and metrics to Amazon CloudWatch. Similarly, a role with accompanying permissions is required for an AWS Glue job to extract, transform, and load data to an Amazon Simple Storage Service (Amazon S3) bucket, or for an AWS Lambda function to perform actions on the data loaded to Amazon S3.

Before the launch of IAM permissions boundaries, central admin teams, such as identity and access management or cloud security teams, were often responsible for creating new roles and policies. But using a centralized team to create and manage all IAM roles and policies creates a bottleneck that doesn’t scale, especially as your organization grows and your centralized team receives an increasing number of requests to create and manage new downstream roles and policies. Imagine having teams of developers deploying or migrating hundreds of applications to the cloud—a centralized team won’t have the necessary context to manually create the permissions for each application themselves.

Because the use case and required permissions can vary significantly between applications and workloads, customers asked for a way to empower their developers to safely create and manage IAM roles and policies, while having security guardrails in place to set maximum permissions. IAM permissions boundaries are designed to provide these guardrails so that even if your developers created the most permissive policy that you can imagine, such broad permissions wouldn’t be functional.

By setting up permissions boundaries, you allow your developers to focus on tasks that add value to your business, while simultaneously freeing your centralized security and IAM teams to work on other critical tasks, such as governance and support. In the following sections, you will learn more about permissions boundaries and how to use them.

Permissions boundaries

A permissions boundary is designed to restrict permissions on IAM principals, such as roles, such that permissions don’t exceed what was originally intended. The permissions boundary uses an AWS or customer managed policy to restrict access, and it’s similar to other IAM policies you’re familiar with because it has resource, action, and effect statements. A permissions boundary alone doesn’t grant access to anything. Rather, it enforces a boundary that can’t be exceeded, even if broader permissions are granted by some other policy attached to the role. Permissions boundaries are a preventative guardrail, rather than something that detects and corrects an issue. To grant permissions, you use resource-based policies (such as S3 bucket policies) or identity-based policies (such as managed or in-line permissions policies).

The predominant use case for permissions boundaries is to limit privileges available to IAM roles created by developers (referred to as delegated administrators in the IAM documentation) who have permissions to create and manage these roles. Consider the example of a developer who creates an IAM role that can access all Amazon S3 buckets and Amazon DynamoDB tables in their accounts. If there are sensitive S3 buckets in these accounts, then these overly broad permissions might present a risk.

To limit access, the central administrator can attach a condition to the developer’s identity policy that helps ensure that the developer can only create a role if the role has a permissions boundary policy attached to it. The permissions boundary, which AWS enforces during authorization, defines the maximum permissions that the IAM role is allowed. The developer can still create IAM roles with permissions that are limited to specific use cases (for example, allowing specific actions on non-sensitive Amazon S3 buckets and DynamoDB tables), but the attached permissions boundary prevents access to sensitive AWS resources even if the developer includes these elevated permissions in the role’s IAM policy. Figure 1 illustrates this use of permissions boundaries.

Figure 1: Implementing permissions boundaries

The central IAM team adds a condition to the developer’s IAM policy that allows the developer to create a role only if a permissions boundary is attached to the role.
The developer creates a role with accompanying permissions to allow access to an application’s Amazon S3 bucket and DynamoDB table. As part of this step, the developer also attaches a permissions boundary that defines the maximum permissions for the role.
Resource access is granted to the application’s resources.
Resource access is denied to the sensitive S3 bucket.

You can use the following policy sample for your developers to allow the creation of roles only if a permissions boundary is attached to them. Make sure to replace <YourAccount_ID> with an appropriate AWS account ID; and the <DevelopersPermissionsBoundary>, with your permissions boundary policy.

   "Effect": "Allow",
   "Action": "iam:CreateRole",
   "Condition": {
      "StringEquals": {
         "iam:PermissionsBoundary": "arn:aws:iam::<YourAccount_ID&gh;:policy/<DevelopersPermissionsBoundary>"
      }
   }

You can also deny deletion of a permissions boundary, as shown in the following policy sample.

   "Effect": "Deny",
   "Action": "iam:DeleteRolePermissionsBoundary"

You can further prevent detaching, modifying, or deleting the policy that is your permissions boundary, as shown in the following policy sample.

   "Effect": "Deny", 
   "Action": [
      "iam:CreatePolicyVersion",
      "iam:DeletePolicyVersion",
	"iam:DetachRolePolicy",
"iam:SetDefaultPolicyVersion"
   ],

Put together, you can use the following permissions policy for your developers to get started with permissions boundaries. This policy allows your developers to create downstream roles with an attached permissions boundary. The policy further denies permissions to detach, delete, or modify the attached permissions boundary policy. Remember, nothing is implicitly allowed in IAM, so you need to allow access permissions for any other actions that your developers require. To learn about allowing access permissions for various scenarios, see Example IAM identity-based policies in the documentation.

{
   "Version": "2012-10-17",
   "Statement": [
      {
         "Sid": "AllowRoleCreationWithAttachedPermissionsBoundary",
   "Effect": "Allow",
   "Action": "iam:CreateRole",
   "Resource": "*",
   "Condition": {
      "StringEquals": {
         "iam:PermissionsBoundary": "arn:aws:iam::<YourAccount_ID>:policy/<DevelopersPermissionsBoundary>"
      }
         }
      },
      {
   "Sid": "DenyPermissionsBoundaryDeletion",
   "Effect": "Deny",
   "Action": "iam:DeleteRolePermissionsBoundary",
   "Resource": "*",
   "Condition": {
      "StringEquals": {
         "iam:PermissionsBoundary": "arn:aws:iam::<YourAccount_ID>:policy/<DevelopersPermissionsBoundary>"
      }
   }
      },
      {
   "Sid": "DenyPolicyChange",
   "Effect": "Deny", 
   "Action": [
      "iam:CreatePolicyVersion",
      "iam:DeletePolicyVersion",
      "iam:DetachRolePolicy",
      "iam:SetDefaultPolicyVersion"
   ],
   "Resource":
"arn:aws:iam::<YourAccount_ID>:policy/<DevelopersPermissionsBoundary>"
      }
   ]
}

Permissions boundaries at scale

You can build on these concepts and apply permissions boundaries to different organizational structures and functional units. In the example shown in Figure 2, the developer can only create IAM roles if a permissions boundary associated to the business function is attached to the IAM roles. In the example, IAM roles in function A can only perform Amazon EC2 actions and Amazon DynamoDB actions, and they don’t have access to the Amazon S3 or Amazon Relational Database Service (Amazon RDS) resources of function B, which serve a different use case. In this way, you can make sure that roles created by your developers don’t exceed permissions outside of their business function requirements.

Figure 2: Implementing permissions boundaries in multiple organizational functions

Best practices

You might consider restricting your developers by directly applying permissions boundaries to them, but this presents the risk of you running out of policy space. Permissions boundaries use a managed IAM policy to restrict access, so permissions boundaries can only be up to 6,144 characters long. You can have up to 10 managed policies and 1 permissions boundary attached to an IAM role. Developers often need larger policy spaces because they perform so many functions. However, the individual roles that developers create—such as a role for an AWS service to access other AWS services, or a role for an application to interact with AWS resources—don’t need those same broad permissions. Therefore, it is generally a best practice to apply permissions boundaries to the IAM roles created by developers, rather than to the developers themselves.

There are better mechanisms to restrict developers, and we recommend that you use IAM identity policies and AWS Organizations service control policies (SCPs) to restrict access. In particular, the Organizations SCPs are a better solution here because they can restrict every principal in the account through one policy, rather than separately restricting individual principals, as permissions boundaries and IAM identity policies are confined to do.

You should also avoid replicating the developer policy space to a permissions boundary for a downstream IAM role. This, too, can cause you to run out of policy space. IAM roles that developers create have specific functions, and the permissions boundary can be tailored to common business functions to preserve policy space. Therefore, you can begin to group your permissions boundaries into categories that fit the scope of similar application functions or use cases (such as system automation and analytics), and allow your developers to choose from multiple options for permissions boundaries, as shown in the following policy sample.

"Condition": {
   "StringEquals": { 
      "iam:PermissionsBoundary": [
"arn:aws:iam::<YourAccount_ID>:policy/PermissionsBoundaryFunctionA",
"arn:aws:iam::<YourAccount_ID>:policy/PermissionsBoundaryFunctionB"
      ]
   }
}

Finally, it is important to understand the differences between the various IAM resources available. The following table lists these IAM resources, their primary use cases and managing entities, and when they apply. Even if your organization uses different titles to refer to the personas in the table, you should have separation of duties defined as part of your security strategy.

IAM resource	Purpose	Owner/maintainer	Applies to
Federated roles and policies	Grant permissions to federated users for experimentation in lower environments	Central team	People represented by users in the enterprise identity provider
IAM workload roles and policies	Grant permissions to resources used by applications, services	Developer	IAM roles representing specific tasks performed by applications
Permissions boundaries	Limit permissions available to workload roles and policies	Central team	Workload roles and policies created by developers
IAM users and policies	Allowed only by exception when there is no alternative that satisfies the use case	Central team plus senior leadership approval	Break-glass access; legacy workloads unable to use IAM roles

Conclusion

This blog post covered how you can use IAM permissions boundaries to allow your developers to create the roles that they need and to define the maximum permissions that can be given to the roles that they create. Remember, you can use AWS Organizations SCPs or deny statements in identity policies for scenarios where permissions boundaries are not appropriate. As your organization grows and you need to create and manage more roles, you can use permissions boundaries and follow AWS best practices to set security guard rails and decentralize role creation and management. Get started using permissions boundaries in IAM.

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How to use AWS KMS RSA keys for offline encryption

2022-06-01 Patrick Palmer

Post Syndicated from Patrick Palmer original https://aws.amazon.com/blogs/security/how-to-use-aws-kms-rsa-keys-for-offline-encryption/

This blog post discusses how you can use AWS Key Management Service (AWS KMS) RSA public keys on end clients or devices and encrypt data, then subsequently decrypt data by using private keys that are secured in AWS KMS.

Asymmetric cryptography is a cryptographic system that uses key pairs. Each pair consists of a public key, which can be seen or accessed by anyone, and a private key, which can be accessed only by authorized people. This system has a useful property, which is that anything encrypted with a public key can only be decrypted by the corresponding private key. A popular method for generating key pairs and encrypting data is the RSA algorithm and cryptosystem.

For RSA key pairs, calculating the private key from the public key is seen as computationally infeasible, and therefore RSA key pairs can be used for both authentication and encryption. The features of asymmetric encryption allow separated parties to share information across an untrusted domain, such as the internet, without having to pre-share any other secrets. However, this type of encryption poses an issue of keeping the private key secure, because the private key has the power to decrypt all messages that are transmitted by a large number of end users.

AWS KMS provides simple APIs that you can use to securely generate, store, and manage keys, including RSA key pairs inside hardware security modules (HSMs). Key pairs are generated within FIPS 140-2 validated HSMs that are managed by AWS. You can then use these private keys through APIs to do actions such as decrypt ciphertexts, meaning that plaintext private keys never leave the HSM, which provides assurances of privacy for the private key. Additional APIs allow a customer to retrieve a plaintext copy of the corresponding public key, which allows disconnected or offline uses of RSA public keys.

Limits of asymmetric cryptography

A key drawback to asymmetric cryptography is the fact that you cannot encrypt large pieces of data. When you have a 2048-bit RSA key pair and encrypt something by using the cipher RSAES_OASEP_SHA_256, the largest amount of data that you can encrypt is 190 bytes.

In contrast, symmetric encryption ciphers that use a chained or counter-mode operation don’t have this limit, and they make it possible for you to encrypt data in the tens-of-gigabytes. Symmetric encryption algorithms such as the Advanced Encryption Standard (AES) also benefit from faster data encryption speeds due to smaller key sizes and less complex operations that can be built into hardware.

By combining these two algorithms in a hybrid cryptosystem, you give end clients with a public key the ability to encrypt large pieces of information. A client generates a random 256-bit AES key, which should be from a secure source such as /dev/urandom or a dedicated embedded chip. The client then encrypts its large payload by using a mode of operation such as AES-GCM or AES-CBC by using that 256-bit AES key. Next, the client encrypts that 256-bit AES key by using the RSA public key (see step 5 in Figure 1). End clients then transmit only encrypted data across insecure channels, maintaining privacy of the payload data.

A challenge that customers often face is that they want to use AWS KMS for its security properties, but also want to access their KMS keys from devices that don’t have AWS credentials embedded within them. Without AWS credentials, a device can’t call AWS APIs. This blog post shows how you can use a hybrid cryptosystem where RSA public keys can be downloaded or embedded into devices to overcome this challenge.

Prerequisites and initial considerations

This walkthrough assumes that you have some understanding of RSA ciphers and symmetric encryption schemes such as AES. The walkthrough uses OpenSSL for demonstration of the encryption process, but similar libraries can be used on a client-side device.

The walkthrough also assumes that you have an AWS Identity and Access Management (IAM) user with permissions to the AWS KMS service, and the AWS Command Line Interface (AWS CLI) installed with the relevant credentials.

When you create a KMS key, you will also generate a key policy that defines access to it. The default key policy allows all users in your account with AWS KMS actions in their IAM policies to access the KMS key. The key policy for a given KMS key is the primary method for determining access.

Important: You will incur charges for the services used in this example. You can find the cost of each service on the corresponding service pricing page. For more information, see AWS KMS Pricing.

Architectural overview

This post contains procedures for completing the following operations, which are also shown in Figure 1:

Create an RSA key pair in AWS KMS.
Download or pre-install the AWS KMS public key to an end-client device.
Generate an AES 256-bit key on an end client.
Encrypt a large payload of data on the end client by using the AES 256-bit key.
Encrypt the AES 256-bit key with the AWS KMS public key.
Transfer the encrypted payload and key.
Decrypt the AES 256-bit key by using AWS KMS.
Decrypt the payload data by using the now-shared AES 256-bit key.

Figure 1: The steps for hybrid encryption

This diagram shows an end client device, an untrusted network such as a cellular network, and the AWS Cloud. An RSA key pair is generated in AWS KMS, and then the public key can either be embedded in the end client, or pulled by the end client through HTTP(S) or other remote means. In all circumstances, only the public key persists on the end client, which means that no secrets are stored on the device.

How you host the public key on your end clients depends on what network access they have. For example, an embedded Internet of Things (IoT) device for mining vehicles might never connect to the internet, but could communicate with a central system through a private 5G network. In this circumstance, you would host this public key within that network for retrieval. For other disconnected IoT devices that can connect to the internet, such as smart-home appliances, you might want to host the public key on a web server at a predefined URL or through an API.

Note: Whenever you vend public keys over an untrusted channel, such as when you vend the public key through an API, you should make sure that the key can be verified in some way to confirm that it hasn’t been tampered with. This is typically done by vending keys over an HTTPS connection, where the integrity of the keys is provided by the X.509 certificate that was used in the TLS connection. The X.509 certificate also verifies an association with the key-pair owner, typically by domain name.

Implement the solution

The following steps can be used as a proof-of-concept to guide you through implementing a hybrid-cryptosystem by using a KMS public key on an example device.

Create keys in AWS KMS

In the first step of this solution, you create an RSA asymmetric key pair in AWS KMS (step 1 in the architectural overview). With AWS KMS, you can create key pairs in a variety of dimensions according to your security requirements or standards. For more information, see Choosing a KMS key type in the AWS KMS documentation.

To create a key pair in AWS KMS, use the CreateKey API. For this example, you will create an RSA key pair with RSA_2048 for the CustomerMasterKeySpec parameter and ENCRYPT_DECRYPT for the KeyUsage parameter in the AWS CLI. This post uses 2048-bit keys, but note that AWS KMS allows larger key sizes. The CLI will return a KeyId value that uniquely identifies the KMS key in your account, which you should take note of.

To create a KMS key by using the CLI

Enter the following command in the AWS CLI.

aws kms create-key --key-spec RSA_2048 \
    --key-usage ENCRYPT_DECRYPT \
    --description "Example RSA Encryption Key Pair"

You can follow the Creating asymmetric KMS keys documentation to see how to use the AWS Management Console to create a KMS key pair with the same properties as shown here.

Note: When a KMS key is created, it will be logged by AWS CloudTrail, a service that monitors and records activity within your account. All API calls to the AWS KMS service are logged in CloudTrail, which you can use to audit access to KMS keys.

To allow your KMS key to be identified by a human-readable string rather than KeyId, you can assign an alias for the KMS key (replace the target-key-id value of <1234abcd-12ab-34cd-56ef-1234567890ab> with your KeyId). This makes it easier to use and manage.

To create a KMS key alias for your key by using the CLI

Enter the following command in the AWS CLI.

aws kms create-alias \
    --alias-name alias/example-rsa-key \
    --target-key-id <1234abcd-12ab-34cd-56ef-1234567890ab>

Download the public key from AWS KMS

A benefit of asymmetric encryption is that you can distribute a public key to a large, untrusted network, and the public key can only be used for encryption. Decryption of those messages can only be conducted by the corresponding private key. You can use the AWS KMS Encrypt API to encrypt data with a KMS key pair (specifically the public key). However, because the AWS APIs are authenticated by using a signature, you must have access to AWS credentials to use these APIs, which you might not want to do on untrusted devices. Additionally, in a private 5G network, you might not have the capability to call the AWS KMS API endpoints from the end clients. Instead, you can download the public key from a local source or embed that into the end client at the time of manufacture.

To retrieve a copy of the public key from your AWS KMS key pair, you can use the GetPublicKey API. The following example shows how to use this with the AWS CLI command get-public-key and reference the key alias you set earlier.

To view the public key for your KMS key pair by using the CLI

Enter the following command in the AWS CLI.

aws kms get-public-key --key-id alias/example-rsa-key

The return value from this API will contain several elements, including the PublicKey. The returned PublicKey value is the DER-encoded X.509, and because you’re using the AWS CLI, it is base64-encoded for readability purposes. By using the AWS CLI, you can query just the PublicKey return value, base64-decode it, and then save the key to a file on disk, as follows.

To use the AWS CLI to query only the public key, then base64 decode it and output it to a file

Enter the following command in the AWS CLI.

aws kms get-public-key \
--key-id alias/example-rsa-key \ 
--output text \ 
--query PublicKey | base64 -–decode > public_key.der

In this example, the local machine where you saved the public_key.der file will now represent the end-client device.

Note: If you call this API by using one of the AWS SDKs, such as boto3, then the PublicKey value is not base64-encoded.

Create an AES 256-bit symmetric key on the end client

Although the end client now has a copy of the public key from the associated KMS private key, the public key can’t be used for encrypting data that you plan on transmitting, due to the size limits on data that can be encrypted. Instead, you can use symmetric encryption. Typically, symmetric keys are smaller than asymmetric keys, the ciphers are faster when encrypting data, and the resulting ciphertext is similar in size to the original data.

To generate a symmetric key, you should use a source of random entropy. Some operating systems offer block access to hardware-based sources of random numbers, such as /dev/hwrng. To provide an example process in this blog post, you will use the OpenSSL rand utility, which uses a cryptographically secure pseudo random generator (CSPRNG) seeded by /dev/urandom. In production systems, you might have stronger sources of entropy to rely on, or compliance requirements for random number generation. In hardware-constrained environments, you should take extra care to make sure that sources of entropy are cryptographically secure. The following command uses OpenSSL to create an AES 256-bit (32 bytes) key and base64-encode it, then save it to disk in plaintext as key.b64.

Note: Anyone with access to this file system will have access to this key.

To use the OpenSSL rand command to create a symmetric key and output it to a file

Enter the following command.
```
openssl rand -base64 32 > key.b64
```

Encrypt the data to be sent from the end client

Now that you have two different key types on the end client, you can use a hybrid cryptosystem to encrypt a large text file. First, you will generate a sample file to encrypt on your system. By outputting some bytes from /dev/urandom, you can create this file to the size you want. The following command outputs 200 random bytes, base64-encodes the file, and writes that to disk in a file called encrypt.me.

To generate a sample file from random data, which will be encrypted later

Enter the following command.

head -c 200 /dev/urandom | base64 –-wrap=0 > encrypt.me

Next, you will encrypt the newly created file with the AES 256-bit key that you created earlier (which is base64-encoded). By using the OpenSSL command line, you will encrypt the file on disk and create a new file called encrypt.me.enc.

Note: For demonstration purposes, this solution uses OpenSSL to complete the encryption process. However, the command line OpenSSL enc utility doesn’t allow the cipher aes-256-gcm. Galois Counter Mode (GCM) is recommended when encrypting and sending data, because it includes authentication, so that that the ciphertext can’t be tampered with in transit. Instead, for this demonstration, you will use aes-256-cbc, which is not authenticated.

To use the OpenSSL enc command to encrypt your sample file with a symmetric key

• Enter the following command.

openssl enc -aes-256-cbc \
-in encrypt.me -out encrypt.me.enc \
-pass file:./key.b64

Encrypt the AES 256-bit key

So that the data can be decrypted again, you will need to share the same AES 256-bit key with the recipient. To share that with only the person who can use the KMS private key that you created earlier, you can encrypt the symmetric key (key.b64) with the RSA public key that you retrieved earlier (public_key.der).

Again, you will use OpenSSL to see how this works and the required cipher options. When encrypting or decrypting with a KMS RSA key pair, you can use one of two encryption algorithms, either RSAES_OAEP_SHA_1 or RSAES_OAEP_SHA_256. These identify the cipher suites used in encryption that are currently supported by AWS KMS for encryption.

To use the OpenSSL pkeyutl command to encrypt your symmetric key with your local copy of your KMS public key

Enter the following command.

openssl pkeyutl \
	-in key.b64 -out key.b64.enc \
	-inkey public_key.der -keyform DER -pubin -encrypt \
	-pkeyopt rsa_padding_mode:oaep -pkeyopt rsa_oaep_md:sha256

This command creates a new file on disk called key.b64.enc. This file is the encrypted AES 256-bit key, which can now be transported securely across an insecure network, such as the internet. The last two options in the command define the padding mode used (OAEP) and the length of the message digest (SHA-256), which align with the options available to decrypt when you use the AWS KMS APIs.

Note: You should securely delete both the original payload file (encrypt.me) and the plaintext AES 256-bit key (key.b64) if you want to prevent anyone else from accessing these files. At this point, you will have three files on disk: public_key.der, encrypt.me.enc, and key.b64.enc. If you want to verify the decryption process later in this example, keep these files.

In production, you might never write any of these values to disk. Instead, you can keep all values in memory and only write the encrypted data (ciphertext) to disk, clearing memory after that process has completed.

You can now use the method of your choice to transfer the encrypted files across an unsecured network without compromising the privacy of those files. For smart-home appliance use cases, you can upload the encrypted files in Amazon Simple Storage Service (Amazon S3), a highly durable storage system that can be accessed from the internet, keeping in mind the preventative security practices that AWS recommends. Later, another service can pull these files from S3, and with the correct permissions for the KMS key, can decrypt the files by using the AWS KMS Decrypt API.

Decrypt the files

With access to the decrypt operation for the KMS key and the encrypted files, you can now retrieve the plaintext data file again. To do this, you will replicate the preceding steps, but in reverse. This involves decrypting the AWS 256-bit key by using the AWS KMS API, and then using that result to decrypt the encrypted data. You will need access to the AWS KMS API to complete these actions, because the private key exists in plaintext only within the AWS KMS HSMs.

To decrypt the files

The first step is to decrypt the AWS 256-bit key. You will need to use the AWS CLI to submit the key.b64.enc file to the AWS KMS API, and specify the algorithm you used to encrypt the file (RSAES_OAEP_SHA_256). Use the following command to retrieve the AES 256-bit key in plaintext. Again, you’re using the –query selector to output only the plaintext, and then decode the base64 value.
```
aws kms decrypt --key-id alias/example-rsa-key \ 
		--ciphertext-blob fileb://key.b64.enc \
		--encryption-algorithm RSAES_OAEP_SHA_256 --output text \
		--query 'Plaintext' | base64 --decode > decrypted_key.b64
```
The final step in decrypting the data is to reverse the CBC encryption process you used in OpenSSL. If another mode of symmetric encryption was used, such as AES-GCM, then you would need to decrypt by using that algorithm and the input AES 256-bit key. Use the following OpenSSL command to retrieve the original plaintext payload.
```
openssl enc -d -aes-256-cbc \
		-in encrypt.me.enc -out decrypted.file \
		-pass file:./decrypted_key.b64
```

Conclusion

In this post, you learned how to combine AWS KMS asymmetric key pairs with locally created symmetric keys to encrypt and share data that exceeds 190 bytes, without storing a secret on a client device. By taking advantage of the RSA cryptosystem for offline encryption, you can reduce the exposure of plaintext data or secrets to devices outside of your control, and without having to complete complex key exchanges. By using the steps in this solution, you can more securely share large amounts of data, such as update files or configuration settings. To learn more about the asymmetric keys feature of AWS KMS, refer to the AWS KMS Developer Guide. If you have questions about the asymmetric keys feature, interact with us through AWS re:Post.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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How to use regional SAML endpoints for failover

2022-05-31 Jonathan VanKim

Post Syndicated from Jonathan VanKim original https://aws.amazon.com/blogs/security/how-to-use-regional-saml-endpoints-for-failover/

Many Amazon Web Services (AWS) customers choose to use federation with SAML 2.0 in order to use their existing identity provider (IdP) and avoid managing multiple sources of identities. Some customers have previously configured federation by using AWS Identity and Access Management (IAM) with the endpoint signin.aws.amazon.com. Although this endpoint is highly available, it is hosted in a single AWS Region, us-east-1. This blog post provides recommendations that can improve resiliency for customers that use IAM federation, in the unlikely event of disrupted availability of one of the regional endpoints. We will show you how to use multiple SAML sign-in endpoints in your configuration and how to switch between these endpoints for failover.

How to configure federation with multi-Region SAML endpoints

AWS Sign-In allows users to log in into the AWS Management Console. With SAML 2.0 federation, your IdP portal generates a SAML assertion and redirects the client browser to an AWS sign-in endpoint, by default signin.aws.amazon.com/saml. To improve federation resiliency, we recommend that you configure your IdP and AWS federation to support multiple SAML sign-in endpoints, which requires configuration changes for both your IdP and AWS. If you have only one endpoint configured, you won’t be able to log in to AWS by using federation in the unlikely event that the endpoint becomes unavailable.

Let’s take a look at the Region code SAML sign-in endpoints in the AWS General Reference. The table in the documentation shows AWS regional endpoints globally. The format of the endpoint URL is as follows, where <region-code> is the AWS Region of the endpoint: https://<region-code>.signin.aws.amazon.com/saml

All regional endpoints have a region-code value in the DNS name, except for us-east-1. The endpoint for us-east-1 is signin.aws.amazon.com—this endpoint does not contain a Region code and is not a global endpoint. AWS documentation has been updated to reference SAML sign-in endpoints.

In the next two sections of this post, Configure your IdP and Configure IAM roles, I’ll walk through the steps that are required to configure additional resilience for your federation setup.

Important: You must do these steps before an unexpected unavailability of a SAML sign-in endpoint.

Configure your IdP

You will need to configure your IdP and specify which AWS SAML sign-in endpoint to connect to.

To configure your IdP

If you are setting up a new configuration for AWS federation, your IdP will generate a metadata XML configuration file. Keep track of this file, because you will need it when you configure the AWS portion later.
Register the AWS service provider (SP) with your IdP by using a regional SAML sign-in endpoint. If your IdP allows you to import the AWS metadata XML configuration file, you can find these files available for the public, GovCloud, and China Regions.
If you are manually setting the Assertion Consumer Service (ACS) URL, we recommend that you pick the endpoint in the same Region where you have AWS operations.
In SAML 2.0, RelayState is an optional parameter that identifies a specified destination URL that your users will access after signing in. When you set the ACS value, configure the corresponding RelayState to be in the same Region as the ACS. This keeps the Region configurations consistent for both ACS and RelayState. Following is the format of a Region-specific console URL.
https://<region-code>.console.aws.amazon.com/

For more information, refer to your IdP’s documentation on setting up the ACS and RelayState.

Configure IAM roles

Next, you will need to configure IAM roles’ trust policies for all federated human access roles with a list of all the regional AWS Sign-In endpoints that are necessary for federation resiliency. We recommend that your trust policy contains all Regions where you operate. If you operate in only one Region, you can get the same resiliency benefits by configuring an additional endpoint. For example, if you operate only in us-east-1, configure a second endpoint, such as us-west-2. Even if you have no workloads in that Region, you can switch your IdP to us-west-2 for failover. You can log in through AWS federation by using the us-west-2 SAML sign-in endpoint and access your us-east-1 AWS resources.

To configure IAM roles

Log in to the AWS Management Console with credentials to administer IAM. If this is your first time creating the identity provider trust in AWS, follow the steps in Creating IAM SAML identity providers to create the identity providers.

Next, create or update IAM roles for federated access. For each IAM role, update the trust policy that lists the regional SAML sign-in endpoints. Include at least two for increased resiliency.

The following example is a role trust policy that allows the role to be assumed by a SAML provider coming from any of the four US Regions.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Principal": {
                "Federated": "arn:aws:iam:::saml-provider/IdP"
            },
            "Action": "sts:AssumeRoleWithSAML",
            "Condition": {
                "StringEquals": {
                    "SAML:aud": [
                        "https://us-east-2.signin.aws.amazon.com/saml",
                        "https://us-west-1.signin.aws.amazon.com/saml",
                        "https://us-west-2.signin.aws.amazon.com/saml",
                        "https://signin.aws.amazon.com/saml"
                    ]
                }
            }
        }
    ]
}

When you use a regional SAML sign-in endpoint, the corresponding regional AWS Security Token Service (AWS STS) endpoint is also used when you assume an IAM role. If you are using service control policies (SCP) in AWS Organizations, check that there are no SCPs denying the regional AWS STS service. This will prevent the federated principal from being able to obtain an AWS STS token.

Switch regional SAML sign-in endpoints

In the event that the regional SAML sign-in endpoint your ACS is configured to use becomes unavailable, you can reconfigure your IdP to point to another regional SAML sign-in endpoint. After you’ve configured your IdP and IAM role trust policies as described in the previous two sections, you’re ready to change to a different regional SAML sign-in endpoint. The following high-level steps provide guidance on switching the regional SAML sign-in endpoint.

To switch regional SAML sign-in endpoints

Change the configuration in the IdP to point to a different endpoint by changing the value for the ACS.
Change the configuration for the RelayState value to match the Region of the ACS.
Log in with your federated identity. In the browser, you should see the new ACS URL when you are prompted to choose an IAM role.

Figure 1: New ACS URL

The steps to reconfigure the ACS and RelayState will be different for each IdP. Refer to the vendor’s IdP documentation for more information.

Conclusion

In this post, you learned how to configure multiple regional SAML sign-in endpoints as a best practice to further increase resiliency for federated access into your AWS environment. Check out the updates to the documentation for AWS Sign-In endpoints to help you choose the right configuration for your use case. Additionally, AWS has updated the metadata XML configuration for the public, GovCloud, and China AWS Regions to include all sign-in endpoints.

The simplest way to get started with SAML federation is to use AWS Single Sign-On (AWS SSO). AWS SSO helps manage your permissions across all of your AWS accounts in AWS Organizations.

If you have any questions, please post them in the Security Identity and Compliance re:Post topic or reach out to AWS Support.

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Spring 2022 SOC 2 Type I Privacy report now available

2022-05-25 Nimesh Ravasa

Post Syndicated from Nimesh Ravasa original https://aws.amazon.com/blogs/security/spring-2022-soc-2-type-i-privacy-report-now-available/

Your privacy considerations are at the core of our compliance work at Amazon Web Services (AWS), and we are focused on the protection of your content while using AWS services. Our Spring 2022 SOC 2 Type I Privacy report is now available, which provides customers with a third-party attestation of our system and the suitability of the design of our privacy controls. The SOC 2 Privacy Trust Service Criteria (TSC), developed by the American Institute of Certified Public Accountants (AICPA) establishes the criteria for evaluating controls that relate to how personal information is collected, used, retained, disclosed, and disposed of. For more information about our privacy commitments supporting our SOC 2 Type 1 report, see the AWS Customer Agreement.

The scope of the Spring 2022 SOC 2 Type I Privacy report includes information about how we handle the content that you upload to AWS, and how it is protected in all of the services and locations that are in scope for the latest AWS SOC reports. The SOC 2 Type I Privacy report is available to AWS customers through AWS Artifact in the AWS Management Console.

As always, we value your feedback and questions. Feel free to reach out to the compliance team through the Contact Us page. If you have feedback about this post, submit comments in the Comments section below.

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Spring 2022 SOC reports now available with 150 services in scope

2022-05-20 Emma Zhang

Post Syndicated from Emma Zhang original https://aws.amazon.com/blogs/security/spring-2022-soc-reports-now-available-with-150-services-in-scope/

At Amazon Web Services (AWS), we’re committed to providing our customers with continued assurance over the security, availability and confidentiality of the AWS control environment. We’re proud to deliver the Spring 2022 System and Organizational (SOC) 1, 2 and 3 reports, which cover October 1, 2021 to March 31, 2022, to support our AWS customers’ confidence in AWS services.

The Spring 2022 SOC reports now include the Asia Pacific (Jakarta) Region, newly added to scope. The associated infrastructure supporting our in-scope products and services is also updated to reflect new edge locations, AWS Wavelength zones, and AWS Local Zones.

The Spring 2022 SOC reports include an additional 9 new services in scope, for a total of 150 services. See the full list on our Services in Scope by Compliance Program page.

Here are the 9 new services in scope for the Spring 2022 SOC reports:

The Spring 2022 SOC reports are now available to AWS customers through AWS Artifact in the AWS Management Console, or you can see our publicly-accessible PDF of the SOC 3 Report.

AWS strives to bring services into scope of our compliance programs to help you meet your architectural and regulatory needs. If there are additional AWS services you would like to see added to the scope of our SOC reports or other compliance programs, reach out to your AWS representatives.

As always, we value your feedback and questions. Feel free to reach out to the team through the Contact Us page. If you have feedback about this post, submit comments in the Comments section below.

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AWS Security Profile: Ely Kahn, Principal Product Manager for AWS Security Hub

2022-05-18 Maddie Bacon

Post Syndicated from Maddie Bacon original https://aws.amazon.com/blogs/security/aws-security-profile-ely-kahn-principal-product-manager-for-aws-security-hub/

In the AWS Security Profile series, I interview some of the humans who work in Amazon Web Services Security and help keep our customers safe and secure. This interview is with Ely Kahn, principal product manager for AWS Security Hub. Security Hub is a cloud security posture management service that performs security best practice checks, aggregates alerts, and facilitates automated remediation.

How long have you been at AWS and what do you do in your current role?

I’ve been with AWS just over 4 years. I came to AWS through the acquisition of a company I co-founded called Sqrrl, which then became Amazon Detective. Shortly after the acquisition, I moved from the Sqrrl/Detective team and helped launch AWS Security Hub. In my current role, I’m the head of product for Security Hub, which means I lead our product roadmap and our product strategy, and I translate customer requirements into technical specifications.

How did you get started in the world of security?

My career started inside the U.S. federal government, first inside the Department of Homeland Security and, specifically, inside the Transportation Security Administration (TSA). At the time, the TSA had uncovered a vulnerability concerning boarding passes and the terrorist no-fly list. I was tasked with figuring out how to close that vulnerability, and I came up with a new way to embed a digital signature inside the barcode to help ensure the authenticity of the boarding pass. After that, people thought I was a cybersecurity expert, and I began working on a lot of cybersecurity strategy and policy at the Department of Homeland Security and then at the White House.

How do you explain your job to your non-tech friends?

I actually explain it the same way to technical and non-technical friends. I head up a service called Security Hub, which is designed to help you do a couple of different things. It helps you understand your security posture on AWS—what sort of risks you face and the most urgent security issues that you need to address across your AWS accounts. It also gives you the tools to improve your security posture and help you fix as many of those security issues as possible. We do that through three primary functions. First, we aggregate all of your security alerts into a standardized data format that’s available in one place. Second, we do our own automated security checks. We look at all the resources you’ve enabled on AWS and help check that those resources are configured in accordance with best practices that we define, and in alignment with various regulatory frameworks. Third, we help you auto-remediate and auto-respond to as many of those issues as possible.

What are you currently working on that you’re excited about?

Our number one priority with Security Hub is to expand coverage of the automated security checks that we provide. We have almost 200 automated security checks today covering several dozen AWS services. Over the next few years, we plan to expand this to more AWS services, which will add a large number of additional security checks. This is important because customers don’t want to have to write these security checks themselves. They want the one-click capability to turn on the checks—or controls, as we call them in Security Hub—and they should be automatically on in all of your accounts. They should only run if you’re using resources that are actually in-scope for those checks, and they should produce a security score to help you quickly understand the security posture of different accounts and of your organization as a whole.

What would you say is the coolest feature of Security Hub?

The coolest feature is probably the one that gets the least attention. It’s what we call our AWS Security Finding Format (ASFF). The ASFF is really just a data standard—it consists of over 1,000 JSON fields and objects, and it’s how you normalize all of your different security alerts. We’ve integrated 75 different services and partner products. The real advantage of Security Hub is that we automatically take all of those different alerts from all of those different integration partners and normalize them into this standardized data format, so that when you’re searching the findings you have a common set of fields to search against if you’re trying to do correlations. For example, you can imagine a situation where Amazon GuardDuty detects unusual activity in an Amazon Simple Storage Service (Amazon S3) bucket, one of our Security Hub checks detects that the bucket is open, and Amazon Macie determines that the bucket contains sensitive information. It’s much easier to do correlations for situations like this when the alerts from those different tools are in the same format. Similarly, building auto-response, auto-remediation workflows is much easier when all of your alerts are in the same format. One of our biggest customers at AWS called the ASFF the gold standard for how to normalize security alerts, which is something we’re super proud of.

As you mentioned, Security Hub integrates with a lot of other AWS services, like GuardDuty and Macie. How do you work with other service teams?

We work across AWS in a couple of different ways. We build out these integrations with other AWS services to either send or receive findings from those services. So, we receive findings from services like GuardDuty and Macie, and we send our findings to other services like AWS Trusted Advisor to give them the same view of security that we see in Security Hub. In general, we try to make it as simple and as low impact as possible because every service team is extremely busy. Wherever possible, we do the integration work and don’t put the onus of effort on the other service team.

The other way we work with other service teams is to formally define the best practices for that service. We have a security engineering team on Security Hub, and we partner with AWS Professional Services and their security consultants. Together, we have been working through the list of the most popular AWS services using a standard taxonomy of control categories to define security controls and best practices for that service. We then work with product managers and engineers on those service teams to review the controls we’re proposing, get their feedback, and then finally code them up as AWS Config rules before deploying them in Security Hub. We have a very well-honed process now to partner with the service teams to integrate with and define the security controls for each service.

Where do you suggest customers start with Security Hub if they are newer in their cloud journey?

The first step with Security Hub is just to turn it on across all of your accounts and AWS Regions. When you do, you’re likely going to see a lot of alerts. Don’t get overwhelmed with the number of alerts you see. Focus initially on the critical and high-severity alerts and work them as campaigns. Identify the owners for all open critical and high-severity alerts and start tracking burndown on a weekly basis. Coordinate with the leadership in your organization so you can identify which teams are keeping up with the alerts and which ones aren’t.

What’s your favorite Leadership Principle and why?

My favorite is one that I initially discounted: frugality. When I first joined AWS, what came to mind was Jeff Bezos using doors as desks. Although that’s certainly a component of frugality, I’ve found that for me, this principle means that we need to be frugal with each other’s time. There are so many competing demands on everyone’s time, and it’s extremely important in a place like AWS to be mindful of that. Make sure you’ve done your due diligence on something before you broadly ask the question or escalate.

What’s the thing you’re most proud of in your career?

There are two things. First is the acquisition of Sqrrl by AWS. I couldn’t have picked a better landing spot for Sqrrl and the team. I feel really lucky that I joined AWS through this acquisition. I’ve really learned a lot here in a short amount of time.

The other thing I’m especially proud of is to have been selected to do a stint through the White House National Security Council staff as the Department of Homeland Security representative to the Council. I sat in the cybersecurity directorate from 2009–2010 as part of that detail to the White House and got a chance to work in the West Wing and attend meetings in the Situation Room, which was just such a special experience.

If you had to pick an industry outside of security, what would you want to do?

This is pretty similar to security, but I got very close to going into the military. Out of high school, I was being recruited for lacrosse at the U.S. Air Force Academy. I had convinced myself that I wanted to go fly jets. I have the utmost respect for our military community, and I certainly could’ve seen myself taking that path.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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Choosing the right certificate revocation method in ACM Private CA

2022-05-16 Arthur Mnev

Post Syndicated from Arthur Mnev original https://aws.amazon.com/blogs/security/choosing-the-right-certificate-revocation-method-in-acm-private-ca/

AWS Certificate Manager Private Certificate Authority (ACM PCA) is a highly available, fully managed private certificate authority (CA) service that allows you to create CA hierarchies and issue X.509 certificates from the CAs you create in ACM PCA. You can then use these certificates for scenarios such as encrypting TLS communication channels, cryptographically signing code, authenticating users, and more. But what happens if you decide to change your TLS endpoint or update your code signing entity? How do you revoke a certificate so that others no longer accept it?

In this blog post, we will cover two fully managed certificate revocation status checking mechanisms provided by ACM PCA: the Online Certificate Status Protocol (OCSP) and certificate revocation lists (CRLs). OCSP and CRLs both enable you to manage how you can notify services and clients about ACM PCA–issued certificates that you revoke. We’ll explain how these standard mechanisms work, we’ll highlight appropriate deployment use cases, and we’ll identify the advantages and downsides of each. We won’t cover configuration topics directly, but will provide you with links to that information as we go.

Certificate revocation

An X.509 certificate is a static, cryptographically signed document that represents a user, an endpoint, an IoT device, or a similar end entity. Because certificates provide a mechanism to authenticate these end entities, they are valid for a fixed period of time that you specify in the expiration date attribute when you generate a certificate. The expiration attribute is important, because it validates and regulates an end entity’s identity, and provides a means to schedule the termination of a certificate’s validity. However, there are situations where a certificate might need to be revoked before its scheduled expiration. These scenarios can include a compromised private key, the end of agreement between signed and signing organizations, user or configuration error when issuing certificates, and more. Although you can use certificates in many ways, we will refer to the predominant use case of TLS-based client-server implementations for the remainder of this blog post.

Certificate revocation can be used to identify certificates that are no longer trusted, and CRLs and OCSP are the standard mechanisms used to publish the revocation information. In addition, the special use case of OCSP stapling provides a more efficient mechanism that is supported in TLS 1.2 and later versions.

ACM PCA gives you the flexibility to use either of these mechanisms, or both. More importantly, as an ACM PCA administrator, the mechanism you choose to use is reflected in the certificate, and you must know how you want to manage revocation before you create the certificate. Therefore, you need to understand how the mechanisms work, select your strategy based on its appropriateness to your needs, and then create and deploy your certificates. Let’s look at how each mechanism works, the use cases for each, and issues to be aware of when you select a revocation strategy.

Certificate revocation using CRLs

As the name suggests, a CRL contains a list of revoked certificates. A CRL is cryptographically signed and issued by a CA, and made available for download by clients (for example, web browsers for TLS) through a CRL distribution point (CDP) such as a web server or a Lightweight Directory Access Point (LDAP) endpoint.

A CRL contains the revocation date and the serial number of revoked certificates. It also includes extensions, which specify whether the CA administrator temporarily suspended or irreversibly revoked the certificate. The CRL is signed and timestamped by the CA and can be verified by using the public key of the CA and the cryptographic algorithm included in the certificate. Clients download the CRL by using the address provided in the CDP extension and trust a certificate by verifying the signature, expiration date, and revocation status in the CRL.

CRLs provide an easy way to verify certificate validity. They can be cached and reused, which makes them resilient to network disruptions, and are an excellent choice for a server that is getting requests from many clients for the same CA. All major web browsers, OpenSSL, and other major TLS implementations support the CRL method of validating certificates.

However, the size of CRLs can lead to inefficiency for clients that are validating server identities. An example is the scenario of browsing multiple websites and downloading a CRL for each site that is visited. CRLs can also grow large over time as you revoke more certificates. Consider the World Wide Web and the number of invalidations that take place daily, which makes CRLs an inefficient choice for small-memory devices (for example, mobile, IoT, and similar devices). In addition, CRLs are not suited for real-time use cases. CRLs are downloaded periodically, a value that can be hours, days, or weeks, and cached for memory management. Many default TLS implementations, such as Mozilla, Chrome, Windows OS, and similar, cache CRLs for 24 hours, leaving a window of up to a day where an endpoint might incorrectly trust a revoked certificate. Cached CRLs also open opportunities for non-trusted sites to establish secure connections until the server refreshes the list, leading to security risks such as data breaches and identity theft.

Implementing CRLs by using ACM PCA

ACM PCA supports CRLs and stores them in an Amazon Simple Storage Service (Amazon S3) bucket for high availability and durability. You can refer to this blog post for an overview of how to securely create and store your CRLs for ACM PCA. Figure 1 shows how CRLs are implemented by using ACM PCA.

Figure 1: Certificate validation with a CRL

The workflow in Figure 1 is as follows:

On certificate revocation, ACM PCA updates the Amazon S3 CRL bucket with a new CRL.

Note: An update to the CRL may take up to 30 minutes after a certificate is revoked.
The client requests a TLS connection and receives the server’s certificate.
The client retrieves the current CRL file from the Amazon S3 bucket and validates it.

The refresh interval is the period between when an administrator revokes a certificate and when all parties consider that certificate revoked. The length of the refresh interval can depend on how quickly new information is published and how long clients cache revocation information to improve performance.

When you revoke a certificate, ACM PCA publishes a new CRL. ACM PCA waits 5 minutes after a RevokeCertificate API call before publishing a new CRL. This process exists to accommodate multiple revocation requests in a short time frame. An update to the CRL can take up to 30 minutes to propagate. If the CRL update fails, ACM PCA makes further attempts every 15 minutes.

CRLs also have a validity period, which you define as part of the CRL configuration by using ExpirationInDays. ACM PCA uses the value in the ExpirationInDays parameter to calculate the nextUpdate field in the CRL (the day and time when ACM PCA will publish the next CRL). If there are no changes to the CRL, the CRL is refreshed at half the interval of the next update. Clients may cache CRLs while they are still valid, so not all clients will have the updated CRL with the newly revoked certificates until the previous published CRL has expired.

Certificate revocation using OCSP

OCSP removes the burden of downloading the CRL from the client. With OCSP, clients provide the serial number and obtain the certificate status for a single certificate from an OCSP Responder. The OCSP Responder can be the CA or an endpoint managed by the CA. The certificate that is returned to the client contains an authorityInfoAccess extension, which provides an accessMethod (for example, OCSP), and identifies the OCSP Responder by a URL (for example, http://example-responder:<port>) in the accessLocation. You can also specify the OCSP Responder location manually in the CA profile. The certificate status response that is returned by the OCSP Responder can be good, revoked, or unknown, and is signed by using a process similar to the CRL for protection against forgery.

OCSP status checks are conducted in real time and are a good choice for time-sensitive devices, as well as mobile and IoT devices with limited memory.

However, the certificate status needs to be checked against the OCSP Responder for every connection, therefore requiring an extra hop. This can overwhelm the responder endpoint that needs to be designed for high availability, low latency, and protection against network and system failures. We will cover how ACM PCA addresses these availability and latency concerns in the next section.

Another thing to be mindful of is that the OCSP protocol implements OCSP status checks over unencrypted HTTP that poses privacy risks. When a client requests a certificate status, the CA receives information regarding the endpoint that is being connected to (for example, domain, IP address, and related information), which can easily be intercepted by a middle party. We will address how OCSP stapling can be used to address these privacy concerns in the OCSP stapling section.

Implementing OCSP by using ACM PCA

ACM PCA provides a highly available, fully managed OCSP solution to notify endpoints that certificates have been revoked. The OCSP implementation uses AWS managed OCSP responders and a globally available Amazon CloudFront distribution that caches OCSP responses closer to you, so you don’t need to set up and operate any infrastructure by yourself. You can enable OCSP on new or existing CAs using the ACM PCA console, the API, the AWS Command Line Interface (AWS CLI), or through AWS CloudFormation. Figure 2 shows how OCSP is implemented on ACM PCA.

Note: OCSP Responders, and the CloudFront distribution that caches the OCSP response for client requests, are managed by AWS.

Figure 2: Certificate validation with OCSP

The workflow in Figure 2 is as follows:

On certificate revocation, the ACM PCA updates the OCSP Responder, which generates the OCSP response.
The client requests a TLS connection and receives the server’s certificate.
The client sends a query to the OCSP endpoint on CloudFront.

Note: If the response is still valid in the CloudFront cache, it will be served to the client from the cache.
If the response is invalid or missing in the CloudFront cache, the request is forwarded to the OCSP Responder.
The OCSP Responder sends the OCSP response to the CloudFront cache.
CloudFront caches the OCSP response and returns it to the client.

The ACM PCA OCSP Responder generates an OCSP response that gets cached by CloudFront for 60 minutes. When a certificate is revoked, ACM PCA updates the OCSP Responder to generate a new OCSP response. During the caching interval, clients continue to receive responses from the CloudFront cache. As with CRLs, clients may also cache OCSP responses, which means that not all clients will have the updated OCSP response for the newly revoked certificate until the previously published (client-cached) OCSP response has expired. Another thing to be mindful of is that while the response is cached, a compromised certificate can be used to spoof a client.

Certificate revocation using OCSP stapling

With both CRLs and OCSP, the client is responsible for validating the certificate status. OCSP stapling addresses the client validation overhead and privacy concerns that we mentioned earlier by having the server obtain status checks for certificates that the server holds, directly from the CA. These status checks are periodic (based on a user-defined value), and the responses are stored on the web server. During TLS connection establishment, the server staples the certificate status in the response that is sent to the client. This improves connection establishment speed by combining requests and reduces the number of requests that are sent to the OCSP endpoint. Because clients are no longer directly connecting to OCSP Responders or the CAs, the privacy risks that we mentioned earlier are also mitigated.

Implementing OCSP stapling by using ACM PCA

OCSP stapling is supported by ACM PCA. You simply use the OCSP Certificate Status Response passthrough to add the stapling extension in the TLS response that is sent from the server to the client. Figure 3 shows how OCSP stapling works with ACM PCA.

Figure 3: Certificate validation with OCSP stapling

The workflow in Figure 3 is as follows:

On certificate revocation, the ACM PCA updates the OCSP Responder, which generates the OCSP response.
The client requests a TLS connection and receives the server’s certificate.
In the case of server’s cache miss, the server will query the OCSP endpoint on CloudFront.

Note: If the response is still valid in the CloudFront cache, it will be returned to the server from the cache.
If the response is invalid or missing in the CloudFront cache, the request is forwarded to the OCSP Responder.
The OCSP Responder sends the OCSP response to the CloudFront cache.
CloudFront caches the OCSP response and returns it to the server, which also caches the response.
The server staples the certificate status in its TLS connection response (for TLS 1.2 and later versions).

OCSP stapling is supported with TLS 1.2 and later versions.

Selecting the correct path with OCSP and CRLs

All certificate revocation offerings from AWS run on a highly available, distributed, and performance-optimized infrastructure. We strongly recommend that you enable a certificate validation and revocation strategy in your environment that best reflects your use case. You can opt to use CRLs, OCSP, or both. Without a revocation and validation process in place, you risk unauthorized access. We recommend that you review your business requirements and evaluate the risk profile of access with an invalid certificate versus the availability requirements for your application.

In the following sections, we’ll provide some recommendations on when to select which certificate validation and revocation strategy. We’ll cover client-server TLS communication, and also provide recommendations for mutual TLS (mTLS) authentication scenarios.

Recommended scenarios for OCSP stapling and OCSP Must-Staple

If your organization requires support for TLS 1.2 and later versions, you should use OCSP stapling. If you want to reduce the application availability risk for a client that is configured to fail the TLS connection establishment when it is unable to validate the certificate, you should consider using the OCSP Must-Staple extension.

OCSP stapling

If your organization requires support for TLS 1.2 and later versions, you should use OCSP stapling. With OCSP stapling, you reduce your client’s load and connectivity requirements, which helps if your network connectivity is unpredictable. For example, if your application client is a mobile device, you should anticipate network failures, low bandwidth, limited processing capacity, and impatient users. In this scenario, you will likely benefit the most from a system that relies on OCSP stapling.

Although the majority of web browsers support OCSP stapling, not all servers support it. OCSP stapling is, therefore, typically implemented together with CRLs that provide an alternate validation mechanism or as a passthrough for when the OCSP response fails or is invalid.

OCSP Must-Staple

If you want to rely on OCSP alone and avoid implementing CRLs, you can use the OCSP Must-Staple certificate extension, which tells the connecting client to expect a stapled response. You can then use OCSP Must-Staple as a flag for your client to fail the connection if the client does not receive a valid OCSP response during connection establishment.

Recommended scenarios for CRLs, OCSP (without stapling), and combinational strategies

If your application needs to support legacy, now deprecated protocols such as TLS 1.0 or 1.1, or if your server doesn’t support OCSP stapling, you could use a CRL, OCSP, or both together. To determine which option is best, you should consider your sensitivity to CA availability, recently revoked certificates, the processing capacity of your application client, and network latency.

CRLs

If your application needs to be available independent of your CA connectivity, you should consider using a CRL. CRLs are much larger files that, from a practical standpoint, require much longer cache times to be of use, but they will be present and available for verification on your system regardless of the status of your network connection. In addition, the lookup time of a certificate within a CRL is local and therefore shorter than a network round trip to an OCSP Responder, because there are no network connection or DNS lookup times.

OCSP (without stapling)

If you are sensitive to the processing capacity of your application client, you should use OCSP. The size of an OCSP message is much smaller compared to a CRL, which allows you to configure shorter caching times that are better suited for your risk profile. To optimize your OCSP and OCSP stapling process, you should review your DNS configuration because it plays a significant role in the amount of time your application will take to receive a response.

For example, if you’re building an application that will be hosted on infrastructure that doesn’t support OCSP stapling, you will benefit from clients making an OCSP request and caching it for a short period. In this scenario, your application client will make a single OCSP request during its connection setup, cache the response, and reuse the certificate state for the duration of its application session.

Combining CRLs and OCSP

You can also choose to implement both CRLs and OCSP for your certificate revocation and validation needs. For example, if your application needs to support legacy TLS protocols while providing resiliency to network failures, you can implement both CRLs and OCSP. When you use CRLs and OCSP together, you verify certificates primarily by using OCSP; however, in case your client is unable to reach the OCSP endpoint, you can fail over to an alternative validation method (for example, CRL). This approach of combining CRLs and OCSP gives you all the benefits of OCSP mentioned earlier, while providing a backup mechanism for failure scenarios such as an unreachable OCSP Responder, invalid response from the OCSP Responder, and similar. However, while this approach adds resilience to your application, it will add management overhead because you will need to set up CRL-based and OCSP-based revocation separately. Also, remember that clients with reduced computing power or poor network connectivity might struggle as they attempt to download and process the CRL.

Recommendations for mTLS authentication scenarios

You should consider network latency and revocation propagation delays when optimizing your server infrastructure for mTLS authentication. In a typical scenario, server certificate changes are infrequent, so caching an OCSP response or CRL on your client and an OCSP-stapled response on a server will improve performance. For mTLS, you can revoke a client certificate at any time; therefore, cached responses could introduce the risk of invalid access. You should consider designing your system such that a copy of a CRL for client certificates is maintained on the server and refreshed based on your business needs. For example, you can use S3 ETags to determine whether an object has changed, and flush the server’s cache in response.

Conclusion

This blog post covered two certificate revocation methods, OCSP and CRLs, that are available on ACM PCA. Remember, when you deploy CA hierarchies for public key infrastructure (PKI), it’s important to define how to handle certificate revocation. The certificate revocation information must be included in the certificate when it is issued, so the choice to enable either CRL or OCSP, or both, has to happen before the certificate is issued. It’s also important to have highly available CRL and OCSP endpoints for certificate lifecycle management. ACM PCA provides a highly available, fully managed CA service that you can use to meet your certificate revocation and validation requirements. Get started using ACM PCA.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

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Getting started with AWS SSO delegated administration

2022-05-12 Chris Mercer

Post Syndicated from Chris Mercer original https://aws.amazon.com/blogs/security/getting-started-with-aws-sso-delegated-administration/

Recently, AWS launched the ability to delegate administration of AWS Single Sign-On (AWS SSO) in your AWS Organizations organization to a member account (an account other than the management account). This post will show you a practical approach to using this new feature. For the documentation for this feature, see Delegated administration in the AWS Single Sign-On User Guide.

With AWS Organizations, your enterprise organization can manage your accounts more securely and at scale. One of the benefits of Organizations is that it integrates with many other AWS services, so you can centrally manage accounts and how the services in those accounts can be used.

AWS SSO is where you can create, or connect, your workforce identities in AWS just once, and then manage access centrally across your AWS organization. You can create user identities directly in AWS SSO, or you can bring them from your Microsoft Active Directory or a standards-based identity provider, such as Okta Universal Directory or Azure AD. With AWS SSO, you get a unified administration experience to define, customize, and assign fine-grained access.

By default, the management account in an AWS organization has the power and authority to manage member accounts in the organization. Because of these additional permissions, it is important to exercise least privilege and tightly control access to the management account. AWS recommends that enterprises create one or more accounts specifically designated for security of the organization, with proper controls and access management policies in place. AWS provides a method in which many services can be administered for the organization from a member account; this is usually referred to as a delegated administrator account. These accounts can reside in a security organizational unit (OU), where administrators can enforce organizational policies. Figure 1 is an example of a recommended set of OUs in Organizations.

Figure 1: Recommended AWS Organizations OUs

Many AWS services support this delegated administrator model, including Amazon GuardDuty, AWS Security Hub, and Amazon Macie. For an up-to-date complete list, see AWS services that you can use with AWS Organizations. AWS SSO is now the most recent addition to the list of services in which you can delegate administration of your users, groups, and permissions, including third-party applications, to a member account of your organization.

How to configure a delegated administrator account

In this scenario, your enterprise AnyCompany has an organization consisting of a management account, an account for managing security, as well as a few member accounts. You have enabled AWS SSO in the organization, but you want to enable the security team to manage permissions for accounts and roles in the organization. AnyCompany doesn’t want you to give the security team access to the management account, and they also want to make sure the security team can’t delete the AWS SSO configuration or manage access to that account, so you decide to delegate the administration of AWS SSO to the security account.

Note: There are a few things to consider when making this change, which you should review before you enable delegated administration. These items are covered in the console during the process, and are described in the section Considerations when delegating AWS SSO administration in this post.

To delegate AWS SSO administration to a security account

In the AWS Organizations console, log in to the management account with a user or role that has permission to use organizations:RegisterDelegatedAdministrator, as well as AWS SSO management permissions.
In the AWS SSO console, navigate to the Region in which AWS SSO is enabled.
Choose Settings on the left navigation pane, and then choose the Management tab on the right side.
Under Delegated administrator, choose Register account, as shown in Figure 2.

Figure 2: The Register account button in AWS SSO
Consider the implications of designating a delegated administrator account (as described in the section Considerations when delegating AWS SSO administration). Select the account you want to be able to manage AWS SSO, and then choose Register account, as shown in Figure 3.

Figure 3: Choosing a delegated administrator account in AWS SSO

You should see a success message to indicate that the AWS SSO delegated administrator account is now setup.

To remove delegated AWS SSO administration from an account

In the AWS Organizations console, log in to the management account with a user or role that has permission to use organizations:DeregisterDelegatedAdministrator.
In the AWS SSO console, navigate to the Region in which AWS SSO is enabled.
Choose Settings on the left navigation pane, and then choose the Management tab on the right side.
Under Delegated administrator, select Deregister account, as shown in Figure 4.

Figure 4: The Deregister account button in AWS SSO
Consider the implications of removing a delegated administrator account (as described in the section Considerations when delegating AWS SSO administration), then enter the account name that is currently administering AWS SSO, and choose Deregister account, as shown in Figure 5.

Figure 5: Considerations of deregistering a delegated administrator in AWS SSO

Considerations when delegating AWS SSO administration

There are a few considerations you should keep in mind when you delegate AWS SSO administration. The first consideration is that the delegated administrator account will not be able to perform the following actions:

Delete the AWS SSO configuration.
Delegate (to other accounts) administration of AWS SSO.
Manage user or group access to the management account.
Manage permission sets that are provisioned (have a user or group assigned) in the organization management account.

For examples of those last two actions, consider the following scenarios:

In the first scenario, you are managing AWS SSO from the delegated administrator account. You would like to give your colleague Saanvi access to all the accounts in the organization, including the management account. This action would not be allowed, since the delegated administrator account cannot manage access to the management account. You would need to log in to the management account (with a user or role that has proper permissions) to provision that access.

In a second scenario, you would like to change the permissions Paulo has in the management account by modifying the policy attached to a ManagementAccountAdmin permission set, which Paulo currently has access to. In this scenario, you would also have to do this from inside the management account, since the delegated administrator account does not have permissions to modify the permission set, because it is provisioned to a user in the management account.

With those caveats in mind, users with proper access in the delegated administrator account will be able to control permissions and assignments for users and groups throughout the AWS organization. For more information about limiting that control, see Allow a user to administer AWS SSO for specific accounts in the AWS Single Sign-On User Guide.

Deregistering an AWS SSO delegated administrator account will not affect any permissions or assignments in AWS SSO, but it will remove the ability for users in the delegated account to manage AWS SSO from that account.

Additional considerations if you use Microsoft Active Directory

There are additional considerations for you to keep in mind if you use Microsoft Active Directory (AD) as an identity provider, specifically if you use AWS SSO configurable AD sync, and which AWS account the directory resides in. In order to use AWS SSO delegated administration when the identity source is set to Active Directory, AWS SSO configurable AD sync must be enabled for the directory. Your organization’s administrators must synchronize Active Directory users and groups you want to grant access to into an AWS SSO identity store. When you enable AWS SSO configurable AD sync, a new feature that launched in April, Active Directory administrators can choose which users and groups get synced into AWS SSO, similar to how other external identity providers work today when using the System for Cross-domain Identity Management (SCIM) v2.0 protocol. This way, AWS SSO knows about users and groups even before they are granted access to specific accounts or roles, and AWS SSO administrators don’t have to manually search for them.

Another thing to consider when delegating AWS SSO administration when using AD as an identity source is where your directory resides, that is which AWS account owns the directory. If you decide to change the AWS SSO identity source from any other source to Active Directory, or change it from Active Directory to any other source, then the directory must reside in (be owned by) the account that the change is being performed in. For example, if you are currently signed in to the management account, you can only change the identity source to or from directories that reside in (are owned by) the management account. For more information, see Manage your identity source in the AWS Single Sign-On User Guide.

Best practices for managing AWS SSO with delegated administration

AWS recommends the following best practices when using delegated administration for AWS SSO:

Maintain separate permission sets for use in the organization management account (versus the rest of the accounts). This way, permissions can be kept separate and managed from within the management account without causing confusion among the delegated administrators.
When granting access to the organization management account, grant the access to groups (and permission sets) specifically for access in that account. This helps enable the principal of least privilege for this important account, and helps ensure that AWS SSO delegated administrators are able to manage the rest of the organization as efficiently as possible (by reducing the number of users, groups, and permission sets that are off limits to them).
If you plan on using one of the AWS Directory Services for Microsoft Active Directory (AWS Managed Microsoft AD or AD Connector) as your AWS SSO identity source, locate the directory and the AWS SSO delegated administrator account in the same AWS account.

Conclusion

In this post, you learned about a helpful new feature of AWS SSO, the ability to delegate administration of your users and permissions to a member account of your organization. AWS recommends as a best practice that the management account of an AWS organization be secured by a least privilege access model, in which as few people as possible have access to the account. You can enable delegated administration for supported AWS services, including AWS SSO, as a useful tool to help your organization minimize access to the management account by moving that control into an AWS account designated specifically for security or identity services. We encourage you to consider AWS SSO delegated administration for administrating access in AWS. To learn more about the new feature, see Delegated administration in the AWS Single Sign-On User Guide.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on the AWS IAM forum or contact AWS Support.

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Establishing a data perimeter on AWS

2022-05-11 Ilya Epshteyn

Post Syndicated from Ilya Epshteyn original https://aws.amazon.com/blogs/security/establishing-a-data-perimeter-on-aws/

For your sensitive data on AWS, you should implement security controls, including identity and access management, infrastructure security, and data protection. Amazon Web Services (AWS) recommends that you set up multiple accounts as your workloads grow to isolate applications and data that have specific security requirements. AWS tools can help you establish a data perimeter between your multiple accounts, while blocking unintended access from outside of your organization. Data perimeters on AWS span many different features and capabilities. Based on your security requirements, you should decide which capabilities are appropriate for your organization. In this first blog post on data perimeters, I discuss which AWS Identity and Access Management (IAM) features and capabilities you can use to establish a data perimeter on AWS. Subsequent posts will provide implementation guidance and IAM policy examples for establishing your identity, resource, and network data perimeters.

A data perimeter is a set of preventive guardrails that help ensure that only your trusted identities are accessing trusted resources from expected networks. These terms are defined as follows:

Trusted identities – Principals (IAM roles or users) within your AWS accounts, or AWS services that are acting on your behalf
Trusted resources – Resources that are owned by your AWS accounts, or by AWS services that are acting on your behalf
Expected networks – Your on-premises data centers and virtual private clouds (VPCs), or networks of AWS services that are acting on your behalf

Data perimeter guardrails

You typically implement data perimeter guardrails as coarse-grained controls that apply across a broad set of AWS accounts and resources. When you implement a data perimeter, consider the following six primary control objectives.

Data perimeter	Control objective
Identity	Only trusted identities can access my resources.
Identity	Only trusted identities are allowed from my network.
Resource	My identities can access only trusted resources.
Resource	Only trusted resources can be accessed from my network.
Network	My identities can access resources only from expected networks.
Network	My resources can only be accessed from expected networks.

Note that the controls in the preceding table are coarse in nature and are meant to serve as always-on boundaries. You can think of data perimeters as creating a firm boundary around your data to prevent unintended access patterns. Although data perimeters can prevent broad unintended access, you still need to make fine-grained access control decisions. Establishing a data perimeter does not diminish the need to continuously fine-tune permissions by using tools such as IAM Access Analyzer as part of your journey to least privilege.

To implement the preceding control objectives on AWS, use three primary capabilities:

Service control policies (SCPs) – AWS Organizations policies that you can use to establish the maximum available permissions for your principals (IAM roles or users) within your organization. SCPs help you ensure that your accounts stay within your organization’s access control guidelines. In the context of data perimeters, you use SCPs so that your identities can access only trusted resources from expected networks.
Resource-based policies– Policies that are attached to resources. For example, you can attach resource-based policies to Amazon Simple Storage Service (Amazon S3) buckets, Amazon Simple Queue Service (Amazon SQS) queues, and AWS Key Management Service (AWS KMS) encryption keys. For a list of services that support resource-based policies, see AWS services that work with IAM. In the context of data perimeters, use resource-based policies so that your resources can be accessed only by trusted identities and from expected networks.
VPC endpoint policies – Policies that you attach to VPC endpoints to control which principals, actions, and resources can be accessed by using a VPC endpoint. In the context of data perimeters, use VPC endpoint policies to specify that your network can be used only by trusted identities to access only trusted resources. For a list of services that support VPC endpoints and VPC endpoint policies, see AWS services that integrate with AWS PrivateLink.

Let’s expand the previous table to include the corresponding policies you would use to implement the controls for each of the control objectives.

Data perimeter	Control objective	Implemented by using
Identity	Only trusted identities can access my resources.	Resource-based policies
Identity	Only trusted identities are allowed from my network.	VPC endpoint policies
Resource	My identities can access only trusted resources.	SCPs
Resource	Only trusted resources can be accessed from my network.	VPC endpoint policies
Network	My identities can access resources only from expected networks.	SCPs
Network	My resources can only be accessed from expected networks.	Resource-based policies

As you can see in the preceding table, the correct policy for each control objective depends on which resource you are trying to secure. Resource-based policies, which are applied to resources such as Amazon S3 buckets, can be used to filter access based on the calling principal and the network from which they are making a call. VPC endpoint policies are used to inspect the principal that is making the API call and the resource they are trying to access. And SCPs are used to restrict your identities from accessing resources outside your control or from outside your network. Note that SCPs apply only to your principals within your AWS organization, whereas resource policies can be used to limit access to all principals.

The last components are the specific IAM controls or condition keys that enforce the control objective. For effective data perimeter controls, use the following primary IAM condition keys, including the new resource owner condition keys:

aws:PrincipalOrgID – Use this condition key to restrict access to trusted identities, your principals (roles or users) that belong to your organization. In the context of a data perimeter, you will use this condition key with your resource-based policies and VPC endpoint policies.
aws:ResourceOrgID – Use this condition key to restrict access to resources that belong to your AWS organization. To establish a data perimeter, you will use this condition key within SCPs and VPC endpoint policies.
aws:SourceIp, aws:SourceVpc, aws:SourceVpce – Use these condition keys to restrict access to expected network locations, such as your corporate network or your VPCs. In the context of a data perimeter, you will use these keys within identity and resource-based policies.

We can now complete the table that we’ve been developing throughout this post.

Data perimeter	Control objective	Implemented by using	Primary IAM capability
Identity	Only trusted identities can access my resources.	Resource-based policies	aws:PrincipalOrgID aws:PrincipalIsAWSService
Identity	Only trusted identities are allowed from my network.	VPC endpoint policies	aws:PrincipalOrgID
Resource	My identities can access only trusted resources.	SCPs	aws:ResourceOrgID
Resource	Only trusted resources can be accessed from my network.	VPC endpoint policies	aws:ResourceOrgID
Network	My identities can access resources only from expected networks.	SCPs	aws:SourceIp aws:SourceVpc aws:SourceVpce aws:ViaAWSService
Network	My resources can only be accessed from expected networks.	Resource-based policies	aws:SourceIp aws:SourceVpc aws:SourceVpce aws:ViaAWSService aws:PrincipalIsAWSService

For the identity data perimeter, the primary condition key is aws:PrincipalOrgID, which you can use in resource-based policies and VPC endpoint policies so that only your identities are allowed access. Use aws:PrincipalIsAWSService to allow AWS services to access your resources by using their own identities—for example, AWS CloudTrail can use this access to write data to your bucket.

For the resource data perimeter, the primary condition key is aws:ResourceOrgID, which you can use in an SCP policy or VPC endpoint policy to allow your identities and network to access only the resources that belong to your AWS organization.

Last, for the network perimeter, use the aws:SourceIp, aws:SourceVpc, and aws:SourceVpce condition keys in SCPs and resource-based policies to make sure that your identities and resources are accessed only from your trusted network. Use the aws:PrincipalIsAWSService and aws:ViaAWSService condition keys to allow AWS services to access your resources from outside your network locations. For example, CloudTrail can use this access to write data to one of your S3 buckets, or Amazon Athena can query data in your S3 buckets. For more information about using these keys as part of your data perimeter strategy, see the blog post IAM makes it easier for you to manage permissions for AWS services accessing your resources.

Conclusion

In this blog post, you learned the foundational elements that are needed to implement an identity, resource, and network data perimeter on AWS, including the primary IAM capabilities that are used to implement each of the control objectives. Stay tuned to the follow-up posts in this series, which will provide prescriptive guidance on establishing your identity, resource, and network data perimeters.

Following are additional resources that will help you further explore the data perimeter topic, including a whitepaper and a hands-on-workshop. We have also curated several blog posts related to the key IAM capabilities discussed in this post.

If you have any questions, comments, or concerns, contact AWS Support or start a new thread on the IAM forum. If you have feedback about this post, submit comments in the Comments section below.

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How to let builders create IAM resources while improving security and agility for your organization

2022-05-07 Jeb Benson

Post Syndicated from Jeb Benson original https://aws.amazon.com/blogs/security/how-to-let-builders-create-iam-resources-while-improving-security-and-agility-for-your-organization/

Many organizations restrict permissions to create and manage AWS Identity and Access Management (IAM) resources to a group of privileged users or a central team. This post explains how you can safely grant these permissions to builders – the people who are developing, testing, launching, and managing cloud infrastructure – to speed up your development, increase your agility, and improve your application security. In addition, you will use an example application stack to see how IAM permissions boundaries can help establish a secure, yet agile work environment for builders.

An example application stack

Defining and creating IAM resources within the application stack allows your builders to craft policies and roles that grant least privilege to application resources. When builders are entitled to create IAM resources, it is straightforward for them to scope policies by referencing the application resources directly in the IAM policies in the same template.

To illustrate this point you will build a simple “hello world” serverless application. The application includes an AWS Step Functions state machine that, once executed, will invoke an AWS Lambda function. You will use this example application along with some IAM policies and IAM roles to illustrate how you can use permissions boundaries to safely grant IAM privileges to builders.

In this example AWS CloudFormation template, the Resource element in MyStateMachineExecutionRole, which is specified as the role for MyStateMachine, includes a reference to the Amazon Resource Name (ARN) of MyLambdaFunction. This is a great example of the principle of least privilege as MyStateMachine will only have permissions to invoke MyLambdaFunction. Making this association is straightforward because the IAM, Step Functions, and Lambda resources are defined together in the same template.

Example application template

AWSTemplateFormatVersion: 2010-09-09
Description: builder-application

Resources:

MyLambdaFunctionExecutionRole:
	Type: AWS::IAM::Role
    Properties:
		AssumeRolePolicyDocument:
			Version: 2012-10-17
			Statement:
				- Effect: Allow
				Principal:
				Service:
					- lambda.amazonaws.com
				Action: sts:AssumeRole
		Policies:
			- PolicyName: MyLambdaFunctionBasicExecutionPolicy
			PolicyDocument:
				Version: 2012-10-17
				Statement:
					- Effect: Allow
					Action:
						- logs:CreateLogGroup
						- logs:CreateLogStream
						- logs:PutLogEvents
					Resource: !Sub arn:${AWS::Partition}:logs:${AWS::Region}:${AWS::AccountId}:log-group:*


MyLambdaFunction:
  	Type: AWS::Lambda::Function
	Properties:
		Runtime: python3.8
		Role: !GetAtt MyLambdaFunctionExecutionRole.Arn
		Handler: index.handler
		Code:
			ZipFile: |
				def handler(event, context):
					return("Hello Builder!")
		Timeout: 30

MyStateMachineExecutionRole:
	Type: AWS::IAM::Role
	Properties:
		AssumeRolePolicyDocument:
			Version: 2012-10-17
			Statement:
				- Effect: Allow
				Principal:
				Service:
					- states.amazonaws.com
				Action: sts:AssumeRole
		Policies:
			- PolicyName: StateMachineExecutionPolicy
			PolicyDocument:
				Version: 2012-10-17
				Statement:
					- Effect: Allow
					Action:
						- lambda:InvokeFunction
					Resource: !GetAtt MyLambdaFunction.Arn
      
MyStateMachine:
	Type: AWS::StepFunctions::StateMachine
	Properties:
		DefinitionString: !Sub |
          {
            "StartAt": "State1",
            "States": {
              "State1": {
                "Type": "Task",
                "Resource": "${MyLambdaFunction.Arn}",
                "End": true
              }
            }
          }
		RoleArn: !GetAtt MyStateMachineExecutionRole.Arn

MyLambdaFunctionPermission:
	Type: AWS::Lambda::Permission
	Properties:
	  Action: lambda:InvokeFunction
	  FunctionName: !Ref MyLambdaFunction
	  Principal: states.amazonaws.com
	  SourceArn: !Ref MyStateMachine

In an organization that uses a centralized approach to IAM management, a builder would not be able to deploy this example application because the roles the builders are granted prohibit IAM actions related to creating and managing roles and policies. This creates three key challenges for the organization:

Builders often rely on a security or cloud team to create IAM resources. This approach adds an additional burden to that team which slows down development while builders wait for the roles and policies to be created, and encourages the team to grant overly-broad permissions so that they don’t have to be involved in the precise details of changes on a daily basis.
IAM resources must be created before the rest of the stack, which makes it much more difficult to create least-privilege policies and roles.
The code for IAM and application infrastructure is maintained separately, which requires extra coordination when creating and updating workloads.

Removing these challenges can simplify your cloud development, lower the amount of overhead and coordination required across your organization, and improve your security posture. Further, reducing the burden on your security team can free up time for them to focus on enforcing additional data perimeters and implementing best practices from the security pillar of the AWS Well-Architected Framework.

Use permissions boundaries on application roles created by builders

So how can your organization shift to a decentralized approach to IAM management and allow builders to safely create application IAM policies and roles, as well as prevent builders from being able to escalate their own privileges? This is a scenario where permissions boundaries should be used.

Permissions boundaries allow an IAM policy to be attached to an IAM role to enforce limits on the permissions that role can be granted. The permissions boundary itself does not grant any permissions – it’s just a guardrail that defines the maximum entitlements. You can create a builder policy that requires a specified permissions boundary be attached to any application roles that a builder creates, effectively setting the maximum permissions on any role that a builder can generate. The permissions for any application roles created will be the intersection of the application policies and the permissions boundary associated with the application role. Said another way, a permission granted in the application policy must also be granted in the permissions boundary, or else it will be implicitly denied according to the policy evaluation logic.

The set of permissions required for builder roles (assumed by actual people or CI/CD pipelines) to deploy infrastructure and develop applications are different than those required for application roles (assumed by workloads/applications) to execute within applications and workflows. If you think of permissions in terms of control plane actions involved in creating, deleting, and modifying resources, versus data plane actions needed to execute the daily business of those resources, builder and application roles typically operate more on the control plane and data plane, respectively. While permissions policies attached to application roles should be tightly scoped to include only those actions needed to perform a specific task, policies for permissions boundaries should be highly reusable and include a broad set of permissions across a suite of services that a variety of applications might need. In addition, it is a best practice to not share roles between humans and services. To summarize, policies for builder and application roles should be designed with the following criteria in mind:

Policy	Role	Permissions	Scope	Reusability	User
builder	builder	control plane	broad	high	human
application	application	data plane	specific	low	service
application-boundary	application	data plane	broad	high	application role

Following the steps in this section, you will create:

A builder policy that grants builders permissions for services needed to deploy and manage applications, and to create and manage IAM policies and roles for those applications.
An application-boundary policy that defines the extent of the permissions any application role created by a builder can have.
A builder role with the builder policy attached as the permissions policy, the application-boundary policy attached as a permissions boundary, and a trust policy that allows anyone in the account to assume the builder role.

Create the builder IAM resources

In this first procedure, you will use CloudFormation to create the builder and application-boundary IAM policies, and the builder IAM role.

To launch the builder IAM stack

Open a Linux terminal with the AWS Command Line Interface (CLI) installed and AWS credentials configured for a user or role that has permissions to create IAM resources.

Launch the builder IAM stack by using the following command:

aws cloudformation create-stack \
--stack-name builder-iam \
--template-url https://awsiammedia.s3.amazonaws.com/public/sample/993-grant-IAM-permissions-for-builders+/builder-iam.json \
--capabilities CAPABILITY_NAMED_IAM

The builder policy you created uses paths to organize IAM policies and roles into isolated “spaces” that can be specified as resource constraints. It also requires roles to have a permissions boundary attached. This approach helps manage role delegation and prevents builders from escalating their privileges or modifying roles that may be used by other teams.

Note that paths can only be added to IAM resources using the AWS CLI or APIs – not via the console. If this is an issue, another option is to specify that policies and roles start with a specific phrase, for example “application-roles-*”. Just be sure to use different phrases for the builder, application, and permissions boundaries resources to maintain isolation and prevent builders from being able to escalate their privileges.

The builder policy also includes some basic control plane permissions, while the application-boundary policy you created includes permissions used across a suite of services that a typical serverless application might need. However, both policies are only meant to demonstrate the concepts in this blog post. In practice, you will need to create policies that more accurately reflect the permissions needed by builder and application roles in your organization. See the example-permissions-boundaries repository on the AWS Samples GitHub site for more ideas.

Use the builder role to launch an application stack

In this section you will assume the builder role and verify that you can launch the application stack, including the application roles, but only if the required permissions boundary and path are specified.

To test launching a stack that creates application roles

Assume the builder role by using the following set of commands (copy and paste into the terminal as a single block). This step uses the jq program, which is available in most operating system package repositories.
```
export AWS_DEFAULT_OUTPUT="json"; \
role=builder; \
aws_role=$(aws iam get-role --role-name $role); \
role_arn=$(echo $aws_role|jq '.Role.Arn'|tr -d '"'); \
aws_credentials=$(aws sts assume-role --role-arn $role_arn --role-session-name builder-test); \
export AWS_ACCESS_KEY_ID=$(echo $aws_credentials|jq '.Credentials.AccessKeyId'|tr -d '"'); \
export AWS_SECRET_ACCESS_KEY=$(echo $aws_credentials|jq '.Credentials.SecretAccessKey'|tr -d '"'); \
export AWS_SESSION_TOKEN=$(echo $aws_credentials|jq '.Credentials.SessionToken'|tr -d '"')
```
You will use this role for all of the following procedures up until the “Clean up” section. If, during the course of this exercise, you get an error that “The security token included in the request is expired”, create a new terminal and repeat this step to get a fresh set of credentials.

The trust policy for the builder role allows any principal in the account to assume it. You can use a combination of the Principal and Condition attributes to further reduce its scope. Normally builder roles are assumed directly via federation or AWS SSO.
Check that the you have now assumed the builder role by using the following command:
```
aws sts get-caller-identity
```

Launch the example application stack by using the following command:

aws cloudformation create-stack \
--stack-name builder-application \
--template-url https://awsiammedia.s3.amazonaws.com/public/sample/993-grant-IAM-permissions-for-builders+/builder-application-1.yml \
--capabilities CAPABILITY_NAMED_IAM

If things are set up correctly, the stack will fail. To confirm, check the StackStatus by using the following command – it should show ROLLBACK_IN_PROGRESS or ROLLBACK_COMPLETE.
```
aws cloudformation describe-stacks \
--stack-name builder-application | jq '.Stacks[].StackStatus'
```
The stack failed to create because the builder role you assumed does not have permissions to create the two application roles without specifying the /application_roles/ path and attaching a permissions boundary with /permissions_boundaries/ in the path. To see the details, use the following command:
```
aws cloudformation describe-stack-events \
--stack-name builder-application | jq '.StackEvents[] | select(.ResourceStatus=="CREATE_FAILED") | .ResourceStatusReason'
```
If the original stack did not create successfully, you will not be able to update it, so you will need to delete it instead by using the following command:
```
aws cloudformation delete-stack \
--stack-name builder-application
```

Launch a new stack with an updated template that includes the required path and permissions boundary by using the following command:

aws cloudformation create-stack \
--stack-name builder-application \
--template-url https://awsiammedia.s3.amazonaws.com/public/sample/993-grant-IAM-permissions-for-builders+/builder-application-2.yml \
--capabilities CAPABILITY_NAMED_IAM

After a few minutes, confirm the stack was successfully created by using the following command and verifying StackStatus is CREATE_COMPLETE:
```
aws cloudformation describe-stacks \
--stack-name builder-application | jq '.Stacks[].StackStatus'
```

To verify the application is working

Start an execution of the state machine and verify the application is working by using the following commands. Run them one at a time to allow the execution to finish.

state_machine_arn=$(aws cloudformation describe-stack-resources --stack-name builder-application | jq '.StackResources[] | select (.LogicalResourceId=="MyStateMachine") | .PhysicalResourceId' | tr -d '"')

execution_arn=$(aws stepfunctions start-execution --state-machine-arn $state_machine_arn | jq '.executionArn' | tr -d '"')

aws stepfunctions describe-execution --execution-arn $execution_arn | jq '.output'

If the output is “\”Hello Builder!\””, then the application is working.

Test that a builder can’t escalate their privileges

In this section, you will test scenarios where a builder attempts, intentionally or not, to escalate their privileges by first modifying the policies attached to the builder role and then extending the permissions of an application role beyond the permissions boundary.

To test updating a builder policy attached to the builder role

Create an environment variable for your AWS account number, which will be used in several of the steps below, using the following command:
```
export AWS_ACCOUNT=$(aws sts get-caller-identity | jq '.Account' | tr -d '"')
```

Retrieve the builder policy and save it to a file by using the following command:

aws iam get-policy-version \
--policy-arn arn:aws:iam::$AWS_ACCOUNT:policy/builder_policies/builder \
--version-id v1 | jq '.PolicyVersion.Document' > builder-policy.json

Add the following JSON block to the “Statement” array in the builder-policy.json file and save the changes.
```
{
	"Sid": "SneakyBuilder",
	"Effect": "Allow",
	"Action": "*",
	"Resource": "*"
}
```
Try to update the builder policy and set it as the default version by using the following command:
```
aws iam create-policy-version \
--policy-arn arn:aws:iam::$AWS_ACCOUNT:policy/builder_policies/builder \
--policy-document file://builder-policy.json \
--set-as-default
```
You should get an AccessDenied error because the builder role can only modify policies in the /application_policies/ space.

To test adding an application policy to the builder role

Save a copy of builder-policy.json as a new file called sneaky-policy.json using the following command:
```
cp builder-policy.json sneaky-policy.json
```
Create the new policy using the following command:
```
aws iam create-policy \
--policy-name sneaky-policy \
--path /application_policies/ \
--policy-document file://sneaky-policy.json
```
You should not get an error in this step because you are creating a new policy that complies with the resource constraint for the statement that includes the iam:CreatePolicy permission in the builder policy. But, it’s just a policy for now – it can’t have any effect unless attached to a role.
Now try to attach this new policy to the builder role by using the following command:
```
aws iam attach-role-policy \
--role-name builder \
--policy-arn arn:aws:iam::$AWS_ACCOUNT:policy/application_policies/sneaky-policy
```
You should get an error because you’re attempting to attach a policy to a role that’s not in the /application-roles/ space, in this case the builder role.

To test modifying an application role with actions outside the permissions boundary

In this procedure, you will attempt to escalate the privileges of the MyLambdaFunctionExecutionRole by adding an action (s3:CreateBucket) that is outside of the permissions boundary attached to the role and then attempting to execute that action when MyLambdaFunction is invoked.

Update the builder-application stack by using the following command:

aws cloudformation update-stack \
--stack-name builder-application \
--template-url https://awsiammedia.s3.amazonaws.com/public/sample/993-grant-IAM-permissions-for-builders+/builder-application-3.yml \
--capabilities CAPABILITY_NAMED_IAM

After a few minutes, confirm the stack was successfully updated by using the following command and verifying StackStatus is UPDATE_COMPLETE:
```
aws cloudformation describe-stacks \
--stack-name builder-application | jq '.Stacks[].StackStatus'
```
Start an execution of the state machine and verify the result by using the following commands. Run them one at a time to allow the execution to finish.
```
state_machine_arn=$(aws cloudformation describe-stack-resources --stack-name builder-application | jq '.StackResources[] | select (.LogicalResourceId=="MyStateMachine") | .PhysicalResourceId' | tr -d '"')

execution_arn=$(aws stepfunctions start-execution --state-machine-arn $state_machine_arn | jq '.executionArn' | tr -d '"')

aws stepfunctions describe-execution --execution-arn $execution_arn | jq '.status'
```
The status should be FAILED. Remember – the effective permissions for any application roles will be the intersection of the attached permissions policies and the permissions boundary. Thus, this execution failed because even though you were able to modify the inline policy of the Lambda function to add s3:CreateBucket, since that action is not allowed in the application-boundary policy attached to the Lambda as a permissions boundary, the request to create an S3 bucket was denied.

Get the name of the latest log stream by using the following commands:

lambda_function_name=$(aws cloudformation describe-stack-resources --stack-name builder-application | jq '.StackResources[] | select (.LogicalResourceId=="MyLambdaFunction") | .PhysicalResourceId' | tr -d '"')

aws logs describe-log-streams \
--log-group-name /aws/lambda/$lambda_function_name \
--order-by LastEventTime \
--descending | jq -r '.logStreams[0].logStreamName'

To verify the actual error was due to a lack of permissions, get the event message by using the following command, replacing <value> with the value of the log stream copied in the step above. If using a bash terminal, you will need to escape any dollar signs in <value> with a backslash character:
```
aws logs get-log-events \
--log-group-name /aws/lambda/$lambda_function_name \
--log-stream-name <value> | jq '.events[] | select (.message | contains("[ERROR]"))'
```
The error should read [ERROR] ClientError: An error occurred (AccessDenied) when calling the CreateBucket operation: Access Denied, which confirms that the permissions boundary prevented you from escalating your privileges as a builder via an application role.

You have now verified that you can safely allow builders to create IAM policies and roles!

Clean up

After you have finished testing, clean up the resources created in this example. Because the builder role does not have permissions to delete builder policies and roles, you will need to assume a different role that can manage IAM resources to complete step 3 below. If you create a new terminal session, make sure the AWS_ACCOUNT environment variable is set.

To clean up

Delete the builder-application stack by using the following command:
```
aws cloudformation delete-stack --stack-name builder-application
```

Delete the sneaky-policy by using the following command:

aws iam delete-policy \
--policy-arn arn:aws:iam::$AWS_ACCOUNT:policy/application_policies/sneaky-policy

Delete the builder-iam stack by using the following command:
```
aws cloudformation delete-stack --stack-name builder-iam
```

Service control policies

Permissions boundaries are applied to individual IAM users or roles within an account. If your organization has multiple accounts, you must create and maintain these boundaries in each account for each individual user or role. But what if you’d like to apply a subset of these rules or others across some or all of your accounts? In this case, you could use service control policies (SCPs), which are a feature of AWS Organizations, to provide central control over the maximum available permissions for multiple accounts in your organization. By organizing accounts into organizational units (OUs), which are groups of accounts that serve an application or service, you can apply service control policies (SCPs) to create targeted governance boundaries for your OUs. To learn more about creating SCPs, see Get more out of service control policies in a multi-account environment in the AWS Security Blog.

Additional tools

Creating and managing tightly scoped policies and roles is an ongoing process that requires a lot of thought and attention to detail. AWS IAM enables fine-grained access control to AWS services, and permissions boundaries are an advanced feature. There is no substitute for actual testing like you performed in the “Test that a builder can’t escalate their privileges” section above, however you can also use the IAM Policy Simulator as a tool to test policies and determine whether or not specific actions are allowed for a given user, group, or role. Additional tools you can use to create, audit, and update IAM policies include:

Access Advisor – to review when services and actions were last accessed.
Access Analyzer – to help identify resources in your organization and accounts that are shared with an external identity, validate IAM policies against policy grammar and best practices, and generate IAM policies based on access activity in your AWS CloudTrail logs.
AWS Cloud Development Kit (CDK) – has built-in convenience methods to help you follow best practices, including the ability to generate least-privilege policies for cloud applications with a single line of code.
Open Source tools like cfn-nag and cdk-nag – to inspect CloudFormation templates and CDK applications for patterns that may indicate insecure infrastructure, for example IAM policies that are too permissive.

Conclusion

In this post, you learned how to put policies and guardrails in place that will allow your organization to grant IAM permissions to builders. These changes will enable your builders to develop and deploy cloud infrastructure and applications more rapidly, and will help strengthen your organization’s security culture by extending the responsibility to a broader group. To learn more about creating, testing, and refining IAM policies and permissions boundaries, see Creating IAM policies, Testing IAM policies, and Refining permissions using access information in the IAM User Guide, and IAM policy types: How and when to use them in the AWS Security Blog.

How to use new Amazon GuardDuty EKS Protection findings

2022-05-06 Marshall Jones

Post Syndicated from Marshall Jones original https://aws.amazon.com/blogs/security/how-to-use-new-amazon-guardduty-eks-protection-findings/

If you run container workloads that use Amazon Elastic Kubernetes Service (Amazon EKS), Amazon GuardDuty now has added support that will help you better protect these workloads from potential threats. Amazon GuardDuty EKS Protection can help detect threats related to user and application activity that is captured in Kubernetes audit logs. Newly-added Kubernetes threat detections include Amazon EKS clusters that are accessed by known malicious actors or from Tor nodes, API operations performed by anonymous users that might indicate a misconfiguration, and misconfigurations that can result in unauthorized access to Amazon EKS clusters. By using machine learning (ML) models, GuardDuty can identify patterns consistent with privilege-escalation techniques, such as a suspicious launch of a container with root-level access to the underlying Amazon Elastic Compute Cloud (Amazon EC2) host. In this post, we give you an overview of the new GuardDuty EKS Protection feature; show you examples of new finding details; and help you understand, operationalize, and respond to these new findings.

Amazon GuardDuty is an automated threat detection service that continuously monitors for suspicious activity and potentially unauthorized behavior to help protect your AWS accounts, Amazon EC2 workloads, data stored in Amazon Simple Storage Service (S3), and now Amazon EKS workloads.

If you are already a GuardDuty customer, you can enable GuardDuty EKS Protection and efficiently navigate the console to begin to use this feature. Your delegated administrator accounts can enable this for existing member accounts and determine if new AWS accounts in an organization will be automatically enrolled. If you are new to GuardDuty, the EKS Protection feature is included as part of the service’s 30-day trial period. As part of the 30-day trial period, you can take full advantage of this new feature and gain insight into your Amazon EKS workloads.

Overview of GuardDuty EKS Protection

GuardDuty EKS Protection enables GuardDuty to detect suspicious activities and potential compromises of your EKS clusters by analyzing Kubernetes audit logs. Kubernetes audit logs provide a security relevant, chronological set of records documenting the sequence of events from individual users, administrators, or system components that have affected your cluster. Audit logs can help answer questions such as: What happened? When did it happen? Who initiated it? GuardDuty EKS Protection analyzes Kubernetes audit logs from your Amazon EKS clusters, both new and existing, without the need to configure EKS control plane logging in your environment. GuardDuty collects these Kubernetes audit logs in addition to AWS CloudTrail, Amazon Virtual Private Cloud (Amazon VPC) flow logs, DNS queries, and Amazon S3 data events. GuardDuty EKS Protection performs analysis and looks for suspicious activity without the need for agents or adding resource constraints to your environment.

To detect threats using Kubernetes audit logs, GuardDuty uses a combination of machine learning, anomaly detection, and integrated threat intelligence to identify and prioritize potential threats. These findings primarily align to five root causes including compromised container images, configuration issues, Kubernetes user compromise, pod compromise, and node compromise. An example of a configuration issue is granting unnecessary privileges to the anonymous user by misconfiguring role-based access control (RBAC), which may inadvertently allow anonymous and unauthenticated calls to the Kubernetes API. A Kubernetes user compromise example could be a bad actor using stolen credentials to deploy containers with insecure settings, to use for a variety of activities from command and control to crypto-mining.

After a threat is detected, GuardDuty generates a security finding that includes container details such as the pod ID, container image ID, and tags associated with the Amazon EKS cluster. These finding details assist you with understanding the root cause which you can use to identify basic steps to remediate findings specific to EKS clusters. For example, your response to a finding or group of findings associated with a compromised Kubernetes user might begin with revoking access. For more information, see Remediating Kubernetes security issues discovered by GuardDuty in the Amazon GuardDuty User Guide.

Understanding new GuardDuty EKS Protection findings

As adversaries continue to become more sophisticated, it becomes even more important for you to align to a common framework to understand the tactics, techniques, and procedures (TTPs) behind an individual event. GuardDuty aligns findings using the MITRE ATT&CK framework, which is a globally-accessible knowledge base of adversary tactics and techniques based on real-world observations. GuardDuty findings have a specific finding format that helps you understand details of each finding. If you examine the ThreatPurpose portion in the GuardDuty EKS Protection finding types, you see there are finding types associated with various MITRE ATT&CK tactics, including CredentialAccess, DefenseEvasion, Discovery, Impact, Persistence, and PrivilegeEscalation. This can help you identify and understand the type of activity associated with a finding.

For example, look at two different finding types that seem similar: Impact:Kubernetes/SuccessfulAnonymousAccess and Discovery:Kubernetes/SuccessfulAnonymousAccess. You can see the difference is the ThreatPurpose at the beginning. They are both involved with successful anonymous access, and the difference is the intent of the activity associated with each finding. GuardDuty has determined based on the API or request URI invoked, that in this example, the activity seen on one finding aligns with the Impact tactic whereas the other finding aligns with the Discovery tactic

With GuardDuty EKS Protection, you now have an additional mechanism to gain insight into your EKS clusters across your accounts to look for suspicious activity. You can be alerted to Kubernetes-specific suspicious activity including: allowing administrator access to the default service account, exposing a Kubernetes dashboard, and launching a container with sensitive host paths. With this new feature, GuardDuty is also able to extend support for finding types that you might already be familiar with that also apply to Amazon EKS workloads. These finding types include calls to a Kubernetes cluster API from a Tor node, or calls to a Kubernetes cluster from a known malicious IP address, which can indicate that there are interactions with your Kubernetes clusters from sources that are commonly associated with malicious actors.

Responding to GuardDuty EKS Protection findings

This section gives an overview of three new GuardDuty EKS Protection findings, how to prevent them, and how to investigate and respond if they happen in your environment. The patterns shown can also act as a guide for how to prevent, investigate, and respond to other GuardDuty EKS Protection findings.

Discovery:Kubernetes/SuccessfulAnonymousAccess

Finding documentation: Discovery:Kubernetes/SuccessfulAnonymousAccess

Severity: Medium

Overview: This finding (as shown in Figure 1) informs you that an API operation was successfully invoked by the system:anonymous user. API calls made by system:anonymous are unauthenticated. The observed API is commonly associated with the discovery stage of an attack when an adversary is gathering information on your Kubernetes cluster. This activity indicates that anonymous or unauthenticated access is permitted on the API action reported in the finding, and may be permitted on other actions. These API calls are possible because of a misconfiguration of the system:anonymous user or system:unauthenticated group.

Preventative measures: AWS recommends that you disable unnecessary anonymous authentication. For instructions, see Review and revoke unnecessary anonymous access in the Amazon EKS Best Practices Guides. It is important to note that Kubernetes versions older than 1.14 granted system:discovery and system:basic-user roles to system:anonymous user by default, and these permissions remain in place after updating unless you explicitly change them.

How to remediate: To respond to this finding, it is important to first identify the details of the activity, for example what cluster is involved? Who is the owner of this cluster? This information will assist you with the remediation steps that follow, to review and revoke unnecessary permissions, and also help you determine a root cause.

Figure 1: GuardDuty Console showing Discovery:Kubernetes/SuccessfulAnonymousAccess finding type

Remediation step 1: Examine permissions

The first step is to examine the permissions that have been granted to the system:anonymous user, and determine what permissions are needed. To accomplish this, you need to first understand what permissions the system:anonymous user has. You can use an rbac-lookup tool to list the Kubernetes roles and cluster roles bound to users, service accounts, and groups. An alternative method can be found at this GitHub page.

./rbac-lookup | grep -P 'system:(anonymous)|(unauthenticated)'
system:anonymous               cluster-wide        ClusterRole/system:discovery
system:unauthenticated         cluster-wide        ClusterRole/system:discovery
system:unauthenticated         cluster-wide        ClusterRole/system:public-info-viewer

Remediation step 2: Disassociate groups

Next, you disassociate the system:unauthenticated group from system:discovery and system:basic-user ClusterRoles, which you do by editing the ClusterRoleBinding. Make sure to not remove system:unauthenticated from the system:public-info-viewer cluster role binding, because that will prevent the Network Load Balancer from performing health checks against the API server. For more information, see Network Load Balancer in the AWS Load Balancer Controller Guide and Identity and Access Management in Amazon EKS Best Practices Guide.

To disassociate the appropriate groups

Run the command kubectl edit clusterrolebindings system:discovery. This command will open the current definition of system:discovery ClusterRoleBinding in your editor as shown in the sample .yaml configuration file:

# Please edit the object below. Lines beginning with a '#' will be ignored,
# and an empty file will abort the edit. If an error occurs while saving this # file will be reopened with the relevant failures.
#
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  annotations:
    rbac.authorization.kubernetes.io/autoupdate: "true"
  creationTimestamp: "2021-06-17T20:50:49Z"
  labels:
    kubernetes.io/bootstrapping: rbac-defaults
  name: system:discovery
  resourceVersion: "24502985"
  selfLink: /apis/rbac.authorization.k8s.io/v1/clusterrolebindings/system%3Adiscovery
  uid: b7936268-5043-431a-a0e1-171a423abeb6
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: system:discovery
subjects:
- apiGroup: rbac.authorization.k8s.io
  kind: Group
  name: system:authenticated
- apiGroup: rbac.authorization.k8s.io
  kind: Group
  name: system:unauthenticated

Delete the entry for system:unauthenticated group, which is highlighted in bold in the subjects section.
Repeat the same steps for system:basic-user ClusterRoleBinding.

If there is no reason that the system:anonymous user should be used in your environment, AWS recommends that you set up automatic response and remediation steps 1-3. For more information about the system:anonymous user, see Identity and Access Management in Amazon EKS Best Practices Guide.

PrivilegeEscalation:Kubernetes/PrivilegedContainer

Finding documentation: PrivilegeEscalation:Kubernetes/PrivilegedContainer

Severity: Medium

Overview: This finding (as shown in Figure 2) informs you that a privileged container was launched on your Kubernetes cluster using an image that has never before been used to launch privileged containers in your cluster. A privileged container has root level access on the host. Adversaries commonly launch privileged containers to perform privilege escalation to gain access and compromise the underlying host.

Preventative measures: Create and enforce policy-as-code (PAC) or Pod Security Standards (PSS) that require that pods be created as non-privileged. For more information, see Pod Security in the in Amazon EKS Best Practices Guide.

How to remediate: To respond to this finding, it is important to first identify the details of the activity and begin to answer questions that will help determine what happened. For example, what pod or workload was launched? Who was the user that launched this pod or workload? What cluster is involved?

Figure 2: GuardDuty Console showing PrivilegeEscalation:Kubernetes/PrivilegedContainer finding type

If this privileged container launch is unexpected, the credentials of the user identity used to launch the container may be compromised. You should then focus on remediating and reviewing access to your cluster, and remediating the user. To do this, follow the procedure in the Remediating a compromised Kubernetes user section of this post. Next, you should identify compromised pods using the procedure in the Identifying and remediating compromised pods section of this post.

If you know what specific circumstances a privileged container can be deployed in your environment, for example only in a specific namespace, it is likely you can automatically remediate any GuardDuty EKS Protection finding associated with a privileged container in any other namespace. For more information about automated response activities, see Incident response and forensics in the Amazon EKS Best Practices Guide.

Persistence:Kubernetes/ContainerWithSensitiveMount

Finding documentation: Persistence:Kubernetes/ContainerWithSensitiveMount

Severity: Medium

Overview: This finding (as shown in Figure 3) informs you that a container was launched with a configuration that included a sensitive host path with write access in the volumeMounts section. This makes the sensitive host path accessible and writable from inside the container. This technique is commonly used by adversaries to gain access to the host’s filesystem.

Preventative Measures: Create and enforce policy-as-code (PAC) or Pod Security Standards (PSS) that use the allowedHostPaths control to only allow required host paths for use in volumes and preferably with read-only access. For more information, see Pod Security in the Amazon EKS Best Practices Guide.

Figure 3: GuardDuty Console showing Persistence:Kubernetes/ContainerWithSensitiveMount finding type

If the container launched is unexpected, the credentials of the user identity used to launch the container may be compromised. You should then focus on remediating and reviewing access to your cluster and remediating the user. To do this, follow the procedure in the next section, Remediating a compromised Kubernetes user.

If you can determine what containers should and should not be launched with writable hostPath mounts, then you can create automatic response and remediation for this use case. For example, you might want to revoke temporary security credentials assigned to the pod or worker node. For more information about revoking temporary security credentials and other response and remediation actions, see Incident response and forensics in the Amazon EKS Best Practices Guide.

Remediating a compromised Kubernetes user

If the compromised user has privileges to read secrets of one or more namespaces, rotate all of the affected secrets. For more information about the different types of secrets, see Secrets in the Kubernetes documentation. If the user has write privileges, AWS recommends auditing all changes made by the user in question. You can accomplish this by querying audit logs, if you have enabled EKS control plane logging on your EKS cluster. If you do not currently have logging enabled, follow the instructions for Enabling and disabling control plane logs in the Amazon EKS User Guide. Amazon EKS stores these control plane logs in Amazon CloudWatch Logs in your account. You can use CloudWatch Logs Insights to list all the mutating changes that the compromised user has made.

Remediation step 1: Identify the user

All actions performed on a Kubernetes cluster has an associated identity. GuardDuty EKS Protection findings report details of the Kubernetes user identity that the malicious actor may have compromised. You can find details of the user identity in the GuardDuty console under the Kubernetes user details section in the finding details, or in the finding JSON under the resources.eksClusterDetails.kubernetesDetails.kubernetesUserDetails section. These user details include username, UID, and groups that the user belongs to.

Remediation step 2: Identify changes

Identify the changes made by the attacker associated with the compromised user identity by using the code example below to query CloudWatch Logs Insights, replacing the placeholders with your values.

fields @timestamp, @message
| filter user.username == <username> 
| filter verb == "create" or verb == "update" or verb == "patch"
| filter responseStatus.code >= 200 and responseStatus.code <= 300
| filter @timestamp >= <approximate start time of the attack in epoch milliseconds>

For example:

fields @timestamp, @message
| filter user.username == "kubernetes-admin" 
| filter verb == "create" or verb == "update" or verb == "patch"
| filter responseStatus.code >= 200 and responseStatus.code <= 300
| filter @timestamp >= 1628279482312

An EKS cluster can have multiple types of user identities, for example the kubernetes-admin user, aws-auth ConfigMap defined user, and so on. You will need to take actions appropriate for the user type to properly revoke its access. For more information, see Remediating compromised Kubernetes users in the Amazon GuardDuty User Guide.
(Optional) If the compromised user identity had extensive privileges and you determine that the attacker made extensive changes to the cluster, you should consider isolating the pod, followed by creating a new clean cluster and redeploying your applications to the new cluster. For instructions to isolate and redeploy EKS pods, see Isolate the Pod by creating a Network Policy that denies all ingress and egress traffic to the pod in the Amazon EKS Best Practices Guide.

Identifying and remediating compromised pods

If a GuardDuty EKS Protection finding is caused by activity related to a specific pod, the value of the finding JSON resource.kubernetesDetails.kubernetesWorkloadDetails.type field is pod. The finding includes the name of the pod and namespace in the resource.kubernetesDetails.kubernetesWorkloadDetails.name and resource.kubernetesDetails.kubernetesWorkloadDetails.namespace fields, which uniquely identify the pod.

In other cases, such as when a service account or a Kubernetes workload name is in the resource.kubernetesDetails.kubernetesUserDetails, you can follow the instructions in the Sample incident response plan to identify compromised pods using different pieces of information available in the GuardDuty EKS Protection findings.

After you have identified compromised pods, to remediate, use the instructions to isolate the pods, rotate the credentials, and gather data for forensic analysis in Isolate the Pod by creating a Network Policy that denies all ingress and egress traffic to the pod in the Amazon EKS Best Practices Guide.

Conclusion

In this post, you learned the details of the new Amazon GuardDuty EKS Protection feature, and Kubernetes audit logs, and you saw examples for how to understand, operationalize, and respond to these new findings. You can enable this feature through the GuardDuty Console or APIs to start monitoring your Amazon EKS clusters today. If you have created Amazon EventBridge Rules to send findings from GuardDuty to a target, then ensure that your rules are configured to deliver these newly added findings.

AWS is committed to continually improving GuardDuty, to make it more efficient for you to operate securely in AWS. At AWS, customer feedback drives change, so we encourage you to continue providing feedback. If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on AWS re:Post or contact AWS Support.

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How to protect HMACs inside AWS KMS

2022-04-20 Jeremy Stieglitz

Post Syndicated from Jeremy Stieglitz original https://aws.amazon.com/blogs/security/how-to-protect-hmacs-inside-aws-kms/

Today AWS Key Management Service (AWS KMS) is introducing new APIs to generate and verify hash-based message authentication codes (HMACs) using the Federal Information Processing Standard (FIPS) 140-2 validated hardware security modules (HSMs) in AWS KMS. HMACs are a powerful cryptographic building block that incorporate secret key material in a hash function to create a unique, keyed message authentication code.

In this post, you will learn the basics of the HMAC algorithm as a cryptographic building block, including how HMACs are used. In the second part of this post, you will see a few real-world use cases that show an application builder’s perspective on using the AWS KMS HMAC APIs.

HMACs provide a fast way to tokenize or sign data such as web API requests, credit cards, bank routing information, or personally identifiable information (PII).They are commonly used in several internet standards and communication protocols such as JSON Web Tokens (JWT), and are even an important security component for how you sign AWS API requests.

HMAC as a cryptographic building block

You can consider an HMAC, sometimes referred to as a keyed hash, to be a combination function that fuses the following elements:

A standard hash function such as SHA-256 to produce a message authentication code (MAC).
A secret key that binds this MAC to that key’s unique value.

Combining these two elements creates a unique, authenticated version of the digest of a message. Because the HMAC construction allows interchangeable hash functions as well as different secret key sizes, one of the benefits of HMACs is the easy replaceability of the underlying hash function (in case faster or more secure hash functions are required), as well as the ability to add more security by lengthening the size of the secret key used in the HMAC over time. The AWS KMS HMAC API is launching with support for SHA-224, SHA-256, SHA-384, and SHA-512 algorithms to provide a good balance of key sizes and performance trade-offs in the implementation. For more information about HMAC algorithms supported by AWS KMS, see HMAC keys in AWS KMS in the AWS KMS Developer Guide.

HMACs offer two distinct benefits:

Message integrity: As with all hash functions, the output of an HMAC will result in precisely one unique digest of the message’s content. If there is any change to the data object (for example you modify the purchase price in a contract by just one digit: from “$350,000” to “$950,000”), then the verification of the original digest will fail.
Message authenticity: What distinguishes HMAC from other hash methods is the use of a secret key to provide message authenticity. Only message hashes that were created with the specific secret key material will produce the same HMAC output. This dependence on secret key material ensures that no third party can substitute their own message content and create a valid HMAC without the intended verifier detecting the change.

HMAC in the real world

HMACs have widespread applications and industry adoption because they are fast, high performance, and simple to use. HMACs are particularly popular in the JSON Web Token (JWT) open standard as a means of securing web applications, and have replaced older technologies such as cookies and sessions. In fact, Amazon implements a custom authentication scheme, Signature Version 4 (SigV4), to sign AWS API requests based on a keyed-HMAC. To authenticate a request, you first concatenate selected elements of the request to form a string. You then use your AWS secret key material to calculate the HMAC of that string. Informally, this process is called signing the request, and the output of the HMAC algorithm is informally known as the signature, because it simulates the security properties of a real signature in that it represents your identity and your intent.

Advantages of using HMACs in AWS KMS

AWS KMS HMAC APIs provide several advantages over implementing HMACs in application software because the key material for the HMACs is generated in AWS KMS hardware security modules (HSMs) that are certified under the FIPS 140-2 program and never leave AWS KMS unencrypted. In addition, the HMAC keys in AWS KMS can be managed with the same access control mechanisms and auditing features that AWS KMS provides on all AWS KMS keys. These security controls ensure that any HMAC created in AWS KMS can only ever be verified in AWS KMS using the same KMS key. Lastly, the HMAC keys and the HMAC algorithms that AWS KMS uses conform to industry standards defined in RFC 2104 HMAC: Keyed-Hashing for Message Authentication.

Use HMAC keys in AWS KMS to create JSON Web Tokens

The JSON Web Token (JWT) open standard is a common use of HMAC. The standard defines a portable and secure means to communicate a set of statements, known as claims, between parties. HMAC is useful for applications that need an authorization mechanism, in which claims are validated to determine whether an identity has permission to perform some action. Such an application can only work if a validator can trust the integrity of claims in a JWT. Signing JWTs with an HMAC is one way to assert their integrity. Verifiers with access to an HMAC key can cryptographically assert that the claims and signature of a JWT were produced by an issuer using the same key.

This section will walk you through an example of how you can use HMAC keys from AWS KMS to sign JWTs. The example uses the AWS SDK for Python (Boto3) and implements simple JWT encoding and decoding operations. This example shows the ease with which you can integrate HMAC keys in AWS KMS into your JWT application, even if your application is in another language or uses a more formal JWT library.

Create an HMAC key in AWS KMS

Begin by creating an HMAC key in AWS KMS. You can use the AWS KMS console or call the CreateKey API action. The following example shows creation of a 256-bit HMAC key:

import boto3

kms = boto3.client('kms')

# Use CreateKey API to create a 256-bit key for HMAC
key_id = kms.create_key(
	KeySpec='HMAC_256',
	KeyUsage='GENERATE_VERIFY_MAC'
)['KeyMetadata']['KeyId']

Use the HMAC key to encode a signed JWT

Next, you use the HMAC key to encode a signed JWT. There are three components to a JWT token: the set of claims, header, and signature. The claims are the very application-specific statements to be authenticated. The header describes how the JWT is signed. Lastly, the MAC (signature) is the output of applying the header’s described operation to the message (the combination of the claims and header). All these are packed into a URL-safe string according to the JWT standard.

The following example uses the previously created HMAC key in AWS KMS within the construction of a JWT. The example’s claims simply consist of a small claim and an issuance timestamp. The header contains key ID of the HMAC key and the name of the HMAC algorithm used. Note that HS256 is the JWT convention used to represent HMAC with SHA-256 digest. You can generate the MAC using the new GenerateMac API action in AWS KMS.

import base64
import json
import time

def base64_url_encode(data):
	return base64.b64encode(data, b'-_').rstrip(b'=')

# Payload contains simple claim and an issuance timestamp
payload = json.dumps({
	"does_kms_support_hmac": "yes",
	"iat": int(time.time())
}).encode("utf8")

# Header describes the algorithm and AWS KMS key ID to be used for signing
header = json.dumps({
	"typ": "JWT",
	"alg": "HS256",
	"kid": key_id #This key_id is from the “Create an HMAC key in AWS KMS” #example. The “Verify the signed JWT” example will later #assert that the input header has the same value of the #key_id 
}).encode("utf8")

# Message to sign is of form <header_b64>.<payload_b64>
message = base64_url_encode(header) + b'.' + base64_url_encode(payload)

# Generate MAC using GenerateMac API of AWS KMS
MAC = kms.generate_mac(
	KeyId=key_id, #This key_id is from the “Create an HMAC key in AWS KMS” 
				 #example
	MacAlgorithm='HMAC_SHA_256',
	Message=message
)['Mac']

# Form JWT token of form <header_b64>.<payload_b64>.<mac_b64>
jwt_token = message + b'.' + base64_url_encode(mac)

Verify the signed JWT

Now that you have a signed JWT, you can verify it using the same KMS HMAC key. The example below uses the new VerifyMac API action to validate the MAC (signature) of the JWT. If the MAC is invalid, AWS KMS returns an error response and the AWS SDK throws an exception. If the MAC is valid, the request succeeds and the application can continue to do further processing on the token and its claims.

def base64_url_decode(data):
	return base64.b64decode(data + b'=' * (4 - len(data) % 4), b'-_')

# Parse out encoded header, payload, and MAC from the token
message, mac_b64 = jwt_token.rsplit(b'.', 1)
header_b64, payload_b64 = message.rsplit(b'.', 1)

# Decode header and verify its contents match expectations
header_map = json.loads(base64_url_decode(header_b64).decode("utf8"))
assert header_map == {
	"typ": "JWT",
	"alg": "HS256",
	"kid": key_id #This key_id is from the “Create an HMAC key in AWS KMS” 
				 #example
}

# Verify the MAC using VerifyMac API of AWS KMS. # If the verification fails, this will throw an error.
kms.verify_mac(
	KeyId=key_id, #This key_id is from the “Create an HMAC key in AWS KMS” 
				 #example
	MacAlgorithm='HMAC_SHA_256',
	Message=message,
	Mac=base64_url_decode(mac_b64)
)

# Decode payload for use application-specific validation/processing
payload_map = json.loads(base64_url_decode(payload_b64).decode("utf8"))

Create separate roles to control who has access to generate HMACs and who has access to validate HMACs

It’s often helpful to have separate JWT creators and validators so that you can distinguish between the roles that are allowed to create tokens and the roles that are allowed to verify tokens. HMAC signatures performed outside of AWS-KMS don’t work well for this because you can’t isolate creators and verifiers if they both must have a copy of the same key. However, this is not an issue for HMAC keys in AWS KMS. You can use key policies to separate out who has permission to ask AWS KMS to generate HMACs and who has permission to ask AWS KMS to validate. Each party uses their own unique access keys to access the HMAC key in AWS KMS. Only HSMs in AWS KMS will ever have access to the actual key material. See the following example key policy statements that separate out GenerateMac and VerifyMac permissions:

{
	"Id": "example-jwt-policy",
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "Allow use of the key for creating JWTs",
			"Effect": "Allow",
			"Principal": {
				"AWS": "arn:aws:iam::111122223333:role/JwtProducer"
			},
			"Action": [
				"kms:GenerateMac"
			],
			"Resource": "*"
		},
		{
			"Sid": "Allow use of the key for validating JWTs",
			"Effect": "Allow",
			"Principal": {
				"AWS": "arn:aws:iam::111122223333:role/JwtConsumer"
			},
			"Action": [
				"kms:VerifyMac"
			],
			"Resource": "*"
		}
	]
}

Conclusion

In this post, you learned about the new HMAC APIs in AWS KMS (GenerateMac and VerifyMac). These APIs complement existing AWS KMS cryptographic operations: symmetric key encryption, asymmetric key encryption and signing, and data key creation and key enveloping. You can use HMACs for JWTs, tokenization, URL and API signing, as a key derivation function (KDF), as well as in new designs that we haven’t even thought of yet. To learn more about HMAC functionality and design, see HMAC keys in AWS KMS in the AWS KMS Developer Guide.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on the KMS re:Post or contact AWS Support.
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How to integrate AWS STS SourceIdentity with your identity provider

2022-04-11 Keith Joelner

Post Syndicated from Keith Joelner original https://aws.amazon.com/blogs/security/how-to-integrate-aws-sts-sourceidentity-with-your-identity-provider/

You can use third-party identity providers (IdPs) such as Okta, Ping, or OneLogin to federate with the AWS Identity and Access Management (IAM) service using SAML 2.0, allowing your workforce to configure services by providing authorization access to the AWS Management Console or Command Line Interface (CLI). When you federate to AWS, you assume a role through the AWS Security Token Service (AWS STS), which through the AssumeRole API returns a set of temporary security credentials you then use to access AWS resources. The use of temporary credentials can make it challenging for administrators to trace which identity was responsible for actions performed.

To address this, with AWS STS you set a unique attribute called SourceIdentity, which allows you to easily see which identity is responsible for a given action.

This post will show you how to set up the AWS STS SourceIdentity attribute when using Okta, Ping, or OneLogin as your IdP. Your IdP administrator can configure a corporate directory attribute, such as an email address, to be passed as the SourceIdentity value within the SAML assertion. This value is stored as the SourceIdentity element in AWS CloudTrail, along with the activity performed by the assumed role. This post will also show you how to set up a sample policy for setting the SourceIdentity when switching roles. Finally, as an administrator reviewing CloudTrail activity, you can use the source identity information to determine who performed which actions. We will walk you through CloudTrail logs from two accounts to demonstrate the continuance of the source identity attribute, showing you how the SourceIdentity will appear in both accounts’ logs.

For more information about the SAML authentication flow in AWS services, see AWS Identity and Access Management Using SAML. For more information about using SourceIdentity, see How to relate IAM role activity to corporate identity.

Configure the SourceIdentity attribute with Okta integration

You will do this portion of the configuration within the Okta administrative console. This procedure assumes that you have a previously configured AWS and Okta integration. If not, you can configure your integration by following the instructions in the Okta AWS Multi-Account Configuration Guide. You will use the Okta to SAML integration and configure an optional attribute to map as the SourceIdentity.

To set up Okta with SourceIdentity

Log in to the Okta admin console.
Navigate to Applications–AWS.
In the top navigation bar, select the Sign On tab, as shown in Figure 1.

Figure 1 – Navigate to attributes in SAML settings on the Okta applications page
Under Sign on methods, select SAML 2.0, and choose the arrow next to Attributes (Optional) to expand, as shown in Figure 2.

Figure 2 – Add new attribute SourceIdentity and map it to Okta provided attribute of your choice
Add the optional attribute definition for SourceIdentity using the following parameters:
- For Name, enter:
  https://aws.amazon.com/SAML/Attributes/SourceIdentity
- For Name format, choose URI Reference.
- For Value, enter user.login.
Note: The Name format options are the following:
Unspecified – can be any format defined by the Okta profile and must be interpreted by your application.
URI Reference – the name is provided as a Uniform Resource Identifier string.
Basic – a simple string; the default if no other format is specified.

The examples shown in Figure 1 and Figure 2 show how to map an email address to the SourceIdentity attribute by using an on-premises Active Directory sync. The SourceIdentity can be mapped to other attributes from your Active Directory.

Configure the SourceIdentity attribute with PingOne integration

You do this portion of the configuration in the Ping Identity administrative console. This procedure assumes that you have a previously configured AWS and Ping integration. If not, you can set up the PingFederate AWS Connector by following the Ping Identity instructions Configuring an SSO connection to Amazon Web Services.

You’re using the Ping to SAML integration and configuring an optional attribute to map as the source identity.

Configuring PingOne as an IdP involves setting up an identity repository (in this case, the PingOne Directory), creating a user group, and adding users to the individual groups.

To configure PingOne as an IdP for AWS

Navigate to https://admin.pingone.com/ and log in using your administrator credentials.
Choose the My Applications tab, as shown in Figure 3.

Figure 3. PingOne My Applications tab
On the Amazon Web Services line, choose on the arrow on the right side to show application details to edit and add a new attribute for the source identity.
Choose Continue to Next Step to open the Attribute Mapping section, as shown in Figure 4.

Figure 4. Attribute mappings
In the Attribute Mapping section line 1, for SAML_SUBJECT, choose Advanced.
On the Advanced Attribute Options page, for Name ID Format to send to SP select urn:oasis:names:tc:SAML:2.0:nameid-format:persistent. For IDP Attribute Name or Literal Value, select SAML_SUBJECT, as shown in Figure 4.

Figure 5. Advanced Attribute Options for SAML_SUBJECT
In the Attribute Mapping section line 2 as shown in Figure 4, for the application attribute https://aws.amazon.com/SAML/Attributes/Role, select Advanced.
On the Advanced Attribute Options page, for Name Format, select urn:oasis:names:tc:SAML:2.0:attrname-format:uri, as shown in Figure 6.

Figure 6. Advanced Attribute Options for https://aws.amazon.com/SAML/Attributes/Role
In the Attribute Mapping section line 2 as shown in Figure 4, select As Literal.
For IDP Attribute Name or Literal Value, format the role and provider ARNs (which are not yet created on the AWS side) in the following format. Be sure to replace the placeholders with your own values. Make a note of the role name and SAML provider name, as you will be using these exact names to create an IAM role and an IAM provider on the AWS side.
arn:aws:iam::<AWS_ACCOUNT_ID>:role/<IAM_ROLE_NAME>,arn:aws:iam:: ::<AWS_ACCOUNT_ID>:saml-provider/<SAML_PROVIDER_NAME>
In the Attribute Mapping section line 3 as shown in Figure 4, for the application attribute https://aws.amazon.com/SAML/Attributes/RoleSessionName, enter Email (Work).
In the Attribute Mapping section as shown in Figure 4, to create line 5, choose Add a new attribute in the lower left.
In the newly added Attribute Mapping section line 5 as shown in Figure 4, add the SourceIdentity.
- For Application Attribute, enter:
  https://aws.amazon.com/SAML/Attributes/SourceIdentity
- For Identity Bridge Attribute or Literal Value, enter:
  SAML_SUBJECT
Choose Continue to Next Step in the lower right.
For Group Access, add your existing PingOne Directory Group to this application.
Review your setup configuration, as shown in Figure 7, and choose Finish.

Figure 7. Review mappings

Configure the SourceIdentity attribute with OneLogin integration

For the OneLogin SAML integration with AWS, you use the Amazon Web Services Multi Account application and configure an optional attribute to map as the SourceIdentity. You do this portion of the configuration in the OneLogin administrative console.

This procedure assumes that you already have a previously configured AWS and OneLogin integration. For information about how to configure the OneLogin application for AWS authentication and authorization, see the OneLogin KB article Configure SAML for Amazon Web Services (AWS) with Multiple Accounts and Roles.

After the OneLogin Multi Account application and AWS are correctly configured for SAML login, you can further customize the application to pass the SourceIdentity parameter upon login.

To change OneLogin configuration to add SourceIdentity attribute

In the OneLogin administrative console, in the Amazon Web Services Multi Account application, on the app administration page, navigate to Parameters, as shown in Figure 8.

Figure 8. OneLogin AWS Multi Account Application Configuration Parameters
To add a parameter, choose the + (plus) icon to the right of Value.
As shown in Figure 9, for Field Name enter https://aws.amazon.com/SAML/Attributes/SourceIdentity, select Include in SAML assertion, then choose Save.

Figure 9. OneLogin AWS Multi Account Application add new field
In the Edit Field page, select the default value you want to use for SourceIdentity. For the example in this blog post, for Value, select Email, then choose Save, as shown in Figure 10.

Figure 10. OneLogin AWS Multi Account Application map new field to email

After you’ve completed this procedure, review the final mapping details, as shown in Figure 11, to confirm that you see the additional parameter that will be passed into AWS through the SAML assertion.

Figure 11. OneLogin AWS Multi Account Application final mapping details

Configuring AWS IAM role trust policy

Now that the IdP configuration is complete, you can enable your AWS accounts to use SourceIdentity by modifying the IAM role trust policy.

For the workforce identity or application to be able to define their source identity when they assume IAM roles, you must first grant them permission for the sts:SetSourceIdentity action, as illustrated in the sample policy document below. This will permit the workforce identity or application to set the SourceIdentity themselves without any need for manual intervention.

To modify an AWS IAM role trust policy

Log in to the AWS Management Console for your account as a user with privileges to configure an IdP, typically an administrator.
Navigate to the AWS IAM service.
For trusted identity, choose SAML 2.0 federation.
From the SAML Provider drop down menu, select the IAM provider you created previously.
Modify the role trust policy and add the SetSourceIdentity action.

Sample policy document

This is a sample policy document attached to a role you assume when you log in to Account1 from the Okta dashboard. Edit your Account1/Role1 trust policy document and add sts:AssumeRoleWithSAML and sts:setSourceIdentity to the Action section.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Federated": "arn:aws:iam::<AccountId>:saml-provider/<IdP>"
      },
      "Action": [
        "sts:AssumeRoleWithSAML",
        "sts:SetSourceIdentity"
      ],
      "Condition": {
        "StringEquals": {
          "SAML:aud": "https://signin.aws.amazon.com/saml"
        }
      }
    }
  ]
}

Notes: The SetSourceIdentity action has to be allowed in the trust policy for assumeRole to work when the IdP is set up to pass SourceIdentity in the assertion. Future version of the sign-in URL may contain a Region code. When this occurs, you will need to modify the URL appropriately.

Policy statement

The following are examples of how the line “Federated”: “arn:aws:iam::<AccountId>:saml-provider/<IdP>” should look, based on the different IdPs specified in this post:

“Federated”: “arn:aws:iam::12345678990:saml-provider/Okta”
“Federated”: “arn:aws:iam::12345678990:saml-provider/PingOne”
“Federated”: “arn:aws:iam::12345678990:saml-provider/OneLogin”

Modify Account2/Role2 policy statement

The following is a sample access control policy document in Account2 for Role2 that allows you to switchRole from Account1. Edit the control policy and add sts:AssumeRole and sts:SetSourceIdentity in the Action section.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::<AccountID>:root"
      },
      "Action": [
        "sts:AssumeRole",
        "sts:SetSourceIdentity"
      ] 
    }
  ]
}

Trace the SourceIdentity attribute in AWS CloudTrail

Use the following procedure for each IdP to illustrate passing a corporate directory attribute mapped as the SourceIdentity.

To trace the SourceIdentity attribute in AWS CloudTrail

Use an IdP to log in to an account Account1 (111122223333) using a role named Role1.
Create a new Amazon Simple Storage Service (Amazon S3) bucket in Account1.
Validate that the CloudTrail log entries for Account1 contain the Active Directory mapped SourceIdentity.
Use the Switch Role feature to switch to a second account Account2 (444455556666), using a role named Role2.
Create a new Amazon S3 bucket in Account2.

To summarize what you’ve done so far, you have:

Configured your corporate directory to pass a unique attribute to AWS as the source identity.
Configured a role that will persist the SourceIdentity attribute in AWS STS, which an employee will use to federate into your account.
Configured an Amazon S3 bucket that user will access.

Now you’ll observe in CloudTrail the SourceIdentity attribute that will be associated with every IAM action.

To see the SourceIdentity attribute in CloudTrail

From the your preferred IdP dashboard, select the AWS tile to log into the AWS console. The example in Figure 12 shows the Okta dashboard.

Figure 12. Login to AWS from IdP dashboard
Choose the AWS icon, which will take you to the AWS Management Console. Notice how the user has assumed the role you created earlier.
To test the SourceIdentity action, you will create a new Amazon S3 bucket.
Amazon S3 bucket names are globally unique, and the namespace is shared by all AWS accounts, so you will need to create a unique bucket name in your account. For this example, we used a bucket named DOC-EXAMPLE-BUCKET1 to validate CloudTrail log entries containing the SourceIdentity attribute.
Log into an account Account1 (111122223333) using a role named Role1.
Next, create a new Amazon S3 bucket in Account1, and validate that the Account1 CloudTrail logs entries contain the SourceIdentity attribute.
Create an Amazon S3 bucket called DOC-EXAMPLE-BUCKET1, as shown in Figure 13.

Figure 13. Create S3 bucket
In the AWS Management Console go to CloudTrail and check the log entry for bucket creation event, as shown in Figure 14.

Figure 14 – Bucket creating entry in CloudTrail

Sample CloudTrail entry showing SourceIdentity entry

The following example shows the new sourceIdentity entry added to the JSON message for the CreateBucket event above.

{"eventVersion":"1.08",
"userIdentity":{
    "type":"AssumedRole",
    "principalId":"AROA42BPHP3V5TTJH32PZ:sourceidentitytest",
    "arn":"arn:aws:sts::111122223333:assumed-role/idsol-org-admin/sourceidentitytest",
    "accountId":"111122223333",
    "accessKeyId":"ASIA42BPHP3V2QJBW7WJ",
    "sessionContext":{
        "sessionIssuer":{
            "type":"Role",
            "principalId":"AROA42BPHP3V5TTJH32PZ",
            "arn":"arn:aws:iam::111122223333:role/idsol-org-admin",
            "accountId":"111122223333","userName":"idsol-org-admin"
        },
        "webIdFederationData":{},
        "attributes":{
            "mfaAuthenticated":"false",
            "creationDate":"2021-05-05T16:29:19Z"
        },
        "sourceIdentity":"<[email protected]>"
    }
},
"eventTime":"2021-05-05T16:33:25Z",
"eventSource":"s3.amazonaws.com",
"eventName":"CreateBucket",
"awsRegion":"us-east-1",
"sourceIPAddress":"203.0.113.0"

Switch to Account2 (444455556666) using assume role, and switch to Account2/assumeRoleSourceIdentity.
Create a new Amazon S3 bucket in Account2 and validate that the Account2 CloudTrail log entries contain the SourceIdentity attribute, as shown in Figure 15.

Figure 15 – Switch role to assumeRoleSourceIdentity
Create a new Amazon S3 bucket in account2 called DOC-EXAMPLE-BUCKET2, as shown in Figure 16.

Figure 16 – Create DOC-EXAMPLE-BUCKET2 bucket while logged into account2 using assumeRoleSourceIdentity
Check the CloudTrail logs for account2 (444455556666) to see if the original SourceIdentity is logged, as shown in Figure 17.

Figure 17 – CloudTrail log entry for the above action

CloudTrail entry showing original SourceIdentity after assuming a role

{
    "eventVersion": "1.08",
    "userIdentity": {
        "type": "AssumedRole",
        "principalId": "AROAVC5CY2KJCIXJLPMQE:sourceidentitytest",
        "arn": "arn:aws:sts::444455556666:assumed-role/s3assumeRoleSourceIdentity/sourceidentitytest",
        "accountId": "444455556666",
        "accessKeyId": "ASIAVC5CY2KJIAO7CGA6",
        "sessionContext": {
            "sessionIssuer": {
                "type": "Role",
                "principalId": "AROAVC5CY2KJCIXJLPMQE",
                "arn": "arn:aws:iam::444455556666:role/s3assumeRoleSourceIdentity",
                "accountId": "444455556666",
                "userName": "s3assumeRoleSourceIdentity"
            },
            "webIdFederationData": {},
            "attributes": {
                "mfaAuthenticated": "false",
                "creationDate": "2021-05-05T16:47:41Z"
            },
            "sourceIdentity": "<[email protected]>"
        }
    },
    "eventTime": "2021-05-05T16:48:53Z",
    "eventSource": "s3.amazonaws.com",
    "eventName": "CreateBucket",
    "awsRegion": "us-east-1",
    "sourceIPAddress": "203.0.113.0",

You logged into Account1/Role1 and switched to Account2/Role2. All the user activities performed in AWS using the Assume Role were also logged with the original user’s sourceIdentity attribute. This makes it simple to trace user activity in CloudTrail.

Conclusion

Now that you have configured your SourceIdentity, you have made it easier for the security team of your organization to use CloudTrail logs to investigate and identify the originating identity of a user. In this post, you learned how to configure the AWS STS SourceIdentity attribute for three different popular IdPs, as well as how to configure each IdP using SAML and their optional attributes. We also provided sample control policy documents outlining how to configure the SourceIdentity for each provider. Additionally, we provide a sample policy for setting the SourceIdentity when switching roles. Lastly, the post walks through how the source identity will show in CloudTrail logs, and provides logs from two accounts to demonstrate the continuance of the source identity attribute. You can now test this capability yourself in your own environment, validate activity in your CloudTrail logs, and determine which user performed a specific action while using the assumeRole functionality.

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ISO/IEC 27001 certificates now available in French and Spanish

2022-03-23 Rodrigo Fiuza

Post Syndicated from Rodrigo Fiuza original https://aws.amazon.com/blogs/security/iso-iec-27001-certificates-now-available-in-french-and-spanish/

French version
Spanish version

We continue to listen to our customers, regulators, and stakeholders to understand their needs regarding audit, assurance, certification, and attestation programs at Amazon Web Services (AWS). We are pleased to announce that ISO/IEC 27001 certificates for AWS are now available in French and Spanish on AWS Artifact. These translated reports will help drive greater engagement and alignment with customer and regulatory requirements across Latin America, Canada, and EMEA.

Current translated (French and Spanish) ISO/IEC 27001 certificates are available through AWS Artifact. Future ISO certificates will be published on an annual basis in accordance with the audit period.

We value your feedback and questions—feel free to reach out to our team or give feedback about this post through our Contact Us page.

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Les certificats ISO/IEC 27001 sont désormais disponibles en français et en espagnol

Nous restons à l’écoute de nos clients, des régulateurs et des parties prenantes pour comprendre leurs besoins en matière de programmes d’audit, d’assurance, de certification et d’attestation chez Amazon Web Services (AWS). Nous avons le plaisir d’annoncer que les certificats ISO/IEC 27001 d’AWS sont désormais disponibles en français et en espagnol sur AWS Artifact. Ces rapports traduits permettront de renforcer l’engagement et l’alignement sur les exigences des clients et des réglementations en Amérique latine, au Canada et en EMEA.

Les certificats ISO/IEC 27001 actuellement traduits (français et espagnol) sont disponibles via AWS Artifact. Les futurs certificats ISO seront publiés sur une base annuelle en fonction de la période d’audit.

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Los certificados ISO/IEC 27001 ahora están disponibles en francés y español

Seguimos escuchando a nuestros clientes y reguladores y entendemos sus necesidades con respecto a los programas de garantías en Amazon Web Services (AWS) y nos complace anunciar que los certificados ISO/IEC 27001 ya están disponibles en francés y español. Estos certificados traducidos ayudarán a impulsar los requisitos regulatorios y de los clientes locales en las regiones de LATAM, Canadá y EMEA.

Los certificados ISO/IEC 27001 traducidos actualmente (Francés y Español) están disponibles en AWS Artifact. Los futuros certificados ISO se publicarán anualmente según el período de auditoría.

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Scaling cross-account AWS KMS–encrypted Amazon S3 bucket access using ABAC

2022-02-23 Jorg Huser

Post Syndicated from Jorg Huser original https://aws.amazon.com/blogs/security/scaling-cross-account-aws-kms-encrypted-amazon-s3-bucket-access-using-abac/

This blog post shows you how to share encrypted Amazon Simple Storage Service (Amazon S3) buckets across accounts on a multi-tenant data lake. Our objective is to show scalability over a larger volume of accounts that can access the data lake, in a scenario where there is one central account to share from. Most use cases involve multiple groups or customers that need to access data across multiple accounts, which makes data lake solutions inherently multi-tenant. Therefore, it becomes very important to associate data assets and set policies to manage these assets in a consistent way. The use of AWS Key Management Service (AWS KMS) simplifies seamless integration with AWS services and offers improved data protection to ultimately enable data lake services (for example, Amazon EMR, AWS Glue, or Amazon Redshift).

To further enable access at scale, you can use AWS Identity and Access Management (IAM) to restrict access to all IAM principals in your organization in AWS Organizations through the aws:PrincipalOrgID condition key. When used in a role trust policy, this key enables you to restrict access to IAM principals in your organization when assuming the role to gain access to resources in your account. This is more scalable than adding every role or account that needs access in the trust policy’s Principal element, and automatically includes future accounts that you may add to your organization.

A data lake that is built on AWS uses Amazon S3 as its primary storage location; Amazon S3 provides an optimal foundation for a data lake because of its virtually unlimited scalability and high durability. AWS Lake Formation can be used as your authorization engine to manage or enforce permissions to your data lake with integrated services such as Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum. For AWS services that integrate with Lake Formation and honor Lake Formation permissions, see the Lake Formation Developer Guide.

This post focuses on services that are not integrated with Lake Formation or where Lake Formation is not enabled on the account; in these cases, direct access for S3 buckets is required for defining and enforcing access control policies. You will learn how to use attribute-based access control (ABAC) as an authorization strategy that defines fine-grained permissions based on attributes, where fewer IAM roles are required to be provisioned, which helps scale your authorization needs. By using ABAC in conjunction with S3 bucket policies, you can authorize users to read objects based on one or more tags that are applied to S3 objects and to the IAM role session of your users based on key-value pair attributes, named session tags. ABAC reduces the number of policies, because session tags are easier to manage and establish a differentiation in job policies. The session tags will be passed when you assume an IAM role or federate a user (through your identity provider) in AWS Security Token Service (AWS STS). This enables administrators to configure a SAML-based identity provider (IdP) to send specific employee attributes as tags in AWS. As a result, you can simplify the creation of fine-grained permissions for employees to get access only to the AWS resources with matching tags.

For simplicity, in this solution you will be using an AWS Command Line Interface (AWS CLI) request for temporary security credentials when generating a session. You will apply the global aws:PrincipalOrgID condition key in your resource-based policies to restrict access to accounts in your AWS organization. This key will restrict access even though the Principal element uses the wildcard character * which applies to all AWS principals in the Principal element. We will suggest additional controls where feasible.

Cross-account access

From a high-level overview perspective, the following items are a starting point when enabling cross-account access. In order to grant cross-account access to AWS KMS-encrypted S3 objects in Account A to a user in Account B, you must have the following permissions in place (objective #1):

The bucket policy in Account A must grant access to Account B.
The AWS KMS key policy in Account A must grant access to the user in Account B.
The AWS Identity and Access Management (IAM) policy in Account B must grant the user access to both the bucket and key in Account A.

By establishing these permissions, you will learn how to maintain entitlements (objective #2) at the bucket or object level, explore cross-account bucket sharing at scale, and overcome limitations such as inline policy size or bucket policy file size (you can learn more details in the Policies overview section). As an extension, you:

Enable granular permissions.
Grant access to groups of resources by tags.

Configuration options can be challenging for cross-account access, especially when the objective is to scale across a large number of accounts to a multi-tenant data lake. This post offers to orchestrate the various configurations options in such a way that both objectives #1 and #2 are met and challenges are addressed. Note that although not all AWS services support tag-based authorization today, we are seeing an increase in support for ABAC.

Solution overview

Our objective is to overcome challenges and design backwards with scalability in mind. The following table depicts the challenges, and outlines recommendations for a better design.

Challenge	Recommendation detail
Use employee attributes from your corporate directory	You can configure your SAML-based or web identity provider to pass session tags to AWS. When your employees federate into AWS, their attributes are applied to their resulting principal in AWS. You can then use ABAC to allow or deny permissions based on those attributes.
Enable granular permissions	ABAC requires fewer policies, because differentiation in job policies is given through session tags, which are easier to manage. Permissions are granted automatically based on attributes.
Grant access to resources by tags	When you use ABAC, you can allow actions on all resources, but only if the resource tag matches the principal’s tag and/or the organization’s tag. It’s best practice to grant least privilege.
Not all services support tag-based authorization	Check for service updates and design around the limitations.
Scale with innovation	ABAC permissions scale with innovation, because it’s not necessary for the administrator to update existing policies to allow access to new resources.

Architecture overview

Figure 1: High-level architecture

The high-level architecture in Figure 1 is designed to show you the advantages of scaling ABAC across accounts and to reflect on a common model that applies to most large organizations.

Solution walkthrough

Here is a brief introduction to the basic components that make up the solution:

Identity provider (IdP) – Can be either on-premises or in the cloud. Your administrators configure your SAML-based IdP to allow workforce users federated access to AWS resources using credentials from your corporate directory (backed by Active Directory). Now you can configure your IdP to pass in user attributes as session tags in federated AWS sessions. These tags can also be transitive, persisting even across subsequent role assumptions.
Central governance account – Helps to establish the access control policies. It takes in the user’s attributes from the IdP and grants permission to access resources. The X-Acct Control Manager is a collection of IAM roles with trust boundaries that grants access to the SAML role by role re-assumption, also known as role chaining. The governance account manages access to the SAML role and trust relationship by using OpenID Connect (OIDC) to allow users to assume roles and pass session tags. This account’s primary purpose is to manage permissions for secure data access. This account can also consume data from the lake if necessary.
Multiple accounts to connect to a multi-tenant data lake – Mirrors a large organization with a multitude of accounts that would like cross-account read access. Each account uses a pre-pave data manager role (one that has been previously established) that can tag or untag any IAM roles in the account, with the cross-account trust allowing users to assume a role to a specific central account. Any role besides the data manager should be prevented from tagging or untagging IAM principals to help prevent unauthorized changes.
Member Analytics organizational unit (OU) – Is where the EMR analytics clusters are connecting to the data in the consumptions layer to visualize by using business intelligence (BI) tools such as Tableau. Access to the shared buckets is granted through bucket and identity policies. Multiple accounts may also have access to buckets within their own accounts. Since this is a consumer account, this account is only joining the lake to consume data from the lake and will not be contributing any data to the data lake.
Central Data Lake OU – Is the account that owns the data stored on Amazon S3. The objects are encrypted, which will require the IAM role to have permissions to the specified AWS KMS key in the key policy. AWS KMS supports the use of the aws:ResourceTag/tag-key global condition context key within identity policies, which lets you control access to AWS KMS keys based on the tags on the key.

Prerequisites

For using SAML session tags for ABAC, you need to have the following:

Access to a SAML-based IdP where you can create test users with specific attributes.
- For simplicity, you will be using an AWS CLI request for temporary security credentials when generating a session.
- You’ll be passing session tags using AssumeRoleWithSAML.
- For SAML-based authentication with Active Directory Federation Services (AD FS) session tags, see Use attribute-based access control with AD FS to simplify IAM permissions management.
AWS accounts where users can sign in. There are five accounts for interaction defined with accommodating policies and permission, as outlined in Figure 1. The numerals listed here refer to the labels on the figure:
- IdP account – IAM user with administrative permission (1)
- Central governance account – Admin/Writer ABAC policy (2)
- Sample accounts to connect to multi-tenant data lake – Reader ABAC policy (3)
- Member Analytics OU account – Assume roles in shared bucket (4)
- Central Data Lake OU account – Pave (that is create) or update virtual private cloud (VPC) condition and principals/PrincipalOrgId in a shared bucket (5)
AWS resources, such as Amazon S3, AWS KMS, or Amazon EMR.
Any third-party software or hardware, such as BI tools.

Our objective is to design an AWS perimeter where access is allowed only if necessary and sufficient conditions are met for getting inside the AWS perimeter. See the following table, and the blog post Establishing a data perimeter on AWS for more information.

Boundary	Perimeter objective	AWS services used
Identity	Only My Resources Only My Networks	Identity-based policies and SCPs
Resource	Only My IAM Principals Only My Networks	Resource-based policies
Network	Only My IAM Principals Only My Resources	VPC endpoint (VPCE) policies

There are multiple design options, as described in the whitepaper Building A Data Perimeter on AWS, but this post will focus on option A, which is a logical AND (∧) conjunction of principal organization, resource, and network:

(Only My aws:PrincipalOrgID) ∧ (Only My Resource) ∧ (Only My Network)
(Only My IAM Principals) ∧ (Only My Resource) ∧ (Only My Network)
(Only My aws:PrincipalOrgID) ∧ (Only My IAM Principals) ∧ (Only My Resource) ∧ (Only My Network)

Policies overview

In order to properly design and consider control points as well as scalability limitations, the following table shows an overview of the policies applied in this post. It outlines the design limitations and briefly discusses the proposed solutions, which are described in more detail in the Establish an ABAC policy section.

Policy type	Sample policies	Limitations to overcome	Solutions outlined in this blog
IAM user policy	AllowIamUserAssumeRole AllowPassSessionTagsAndTransitive IAMPolicyWithResourceTagForKMS	Inline JSON policy document is limited to (2048 bytes). For using KMS keys, accounts are limited to specific AWS Regions.	Enable session tags, which expire and require credentials. It is a best practice to grant least privilege permissions with AWS Identity and Access Management (IAM) policies.
S3 bucket policy	Principals-only-from-given-Org Access-to-specific-VPCE-only KMS-Decrypt-with-specific-key DenyUntaggedData	The bucket policy has a 20 KB maximum file size. Data exfiltration or non-trusted writing to buckets can be restricted by a combination of policies and conditions.	Use aws:PrincipalOrgID to simplify specifying the Principal element in a resource-based policy. No manual updating of account IDs required, if they belong to the intended organization.
~ VPCE policy	DenyNonApprovedIPAddresses VPCEndpointsNonAdmin DenyNonSSLConnections DenyIncorrectEncryptionKey DenyUnEncryptedObjectUploads	aws:PrincipalOrgID opens up broadly to accounts with single control—requiring additional controls. Make sure that principals aren’t inadvertently allowed or denied access.	Restrict access to VPC with endpoint policies and deny statements.
KMS key policy	Allow-use-of-the-KMS-key-for-organization	Listing all AWS account IDs in an organization. Maximum key policy document size is 32 KB, which applies to KMS key. Changing a tag or alias might allow or deny permission to a KMS key.	Specify the organization ID in the condition element, instead of listing all the AWS account IDs. AWS owned keys do not count against these quotas, so use these where possible. Assure visibility of API operations

By using a combination of these policies and conditions, you can work to mitigate accidental or intentional exfiltration of data, IAM credentials, and VPC endpoints. You can also alleviate writing to a bucket that is owned by a non-trusted account by using even more restrictive policies for write operations. For example, use the s3:ResourceAccount condition key to filter access to trusted S3 buckets that belong only to specific AWS accounts.

Today, the scalability of cross-account bucket sharing is limited by the current allowed S3 bucket policy size (20 KB) and KMS key policy size (32 KB). Cross-account sharing also may increase risk, unless the appropriate guardrails are in place. The aws:PrincipalOrgID condition helps by allowing sharing of resources such as buckets only to accounts and principals within your organization. If ABAC is also used for enforcement, tags used for authorization also need to be governed across all participating accounts; this includes protecting them from modification and also helps ensure only authorized principals can use ABAC when gaining access.

Figure 2 demonstrates a sample scenario for the roles from a specific organization in AWS Organizations, including multiple application accounts (Consumer Account 1, Consumer Account 2) with defined tags accessing an S3 bucket that is owned by Central Data Lake Account.

Figure 2: Sample scenario

Establish an ABAC policy

AWS has published additional blog posts and documentation for various services and features that are helpful supplements to this post. For more information, see the following resources:

ABAC for AWS KMS in the AWS KMS Developer Guide
Limit access to Amazon S3 buckets owned by specific AWS accounts blog post
Managing access permissions for your AWS organization in the AWS Organizations User Guide
Allowing users in other accounts to use a KMS key in the AWS KMS Developer Guide
How to scale your authorization needs by using attribute-based access control with S3 blog post
Overview of Lake Formation tag-based access control in the AWS Lake Formation Developer Guide
IAM policies for tag-based access to clusters and EMR notebooks in the Amazon EMR Management Guide

To establish the ABAC policy

Federate the user with permissions to assume roles with the same tags. By way of tagging the users, they automatically get access to assume the correct role, if they work only on one project and team.

Create the customer managed policy to attach to the federated user that uses ABAC to allow role assumption.

The federated user can assume a role only when the user and role tags are matching. More detailed instructions for defining permissions to access AWS resources based on tags are available in Create the ABAC policy in the IAM tutorial: Define permissions to access AWS resources based on tags.

Policy sample to allow the user to assume the role

The AllowUserAssumeRole statement in the following sample policy allows the federated user to assume the role test-session-tags with the attached policy. When that federated user assumes the role, they must pass the required session tags. For more information about federation, see Identity providers and federation in the AWS Identity and Access Management User Guide.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowUserAssumeRole",
            "Effect": "Allow",
            "Action": "sts:AssumeRole",
            "Resource": "arn:aws:iam::123456789123:role/test-session-tags",
            "Condition": {
                "StringEquals": {
                    "iam:ResourceTag/access-project": "${aws:PrincipalTag/access-project}",
                    "iam:ResourceTag/cost-center": "${aws:PrincipalTag/cost-center}",
                    "iam:ResourceTag/access-team":"${aws:PrincipalTag/access-team}"
                },
                "ForAllValues:StringEquals": {
                 "aws:TagKeys": [
                     "access-project",
                     "access-team",
                     "cost-center"
                 ]
             },
             "StringEqualsIfExists": {
                 "aws:RequestTag/access-project": "${aws:PrincipalTag/access-project}",
                 "aws:RequestTag/access-team": "${aws:PrincipalTag/access-team}",
                 "aws:RequestTag/cost-center": "${aws:PrincipalTag/cost-center}"
             }

			
                } }
        
    ]
}

Create an IAM policy to attach to the role

The IAM policy defines permissions to access cross-account encrypted S3 bucket and allows access to the role created in step #2

{
    "Version": "2012-10-17",
    "Statement": [
        	{
            		"Sid": "ListBucketObjects",
            		"Effect": "Allow",
            		"Action": [
                	"s3:ListBucket"
            		],
            		"Resource": [
                		"arn:aws:s3::: sharedbucket"
            		]
        	},
        	{
            		"Sid": "GetBucketObjects",
            		"Effect": "Allow",
            		"Action": [
                		"s3:GetObject"
            		],
            		"Resource": [
                		"arn:aws:s3::: sharedbucket",
                		"arn:aws:s3::: sharedbucket/*"
            		]
        }
    ]
}

Allow cross-account access to an AWS KMS key. This is a key policy to allow principals to call specific operations on KMS keys.
Using ABAC with AWS KMS provides a flexible way to authorize access without editing policies or managing grants. Additionally, the aws:PrincipalOrgID global condition key can be used to restrict access to all accounts in your organization. This is more scalable than having to list all the account IDs in an organization within a policy. You accomplish this by specifying the organization ID in the condition element with the condition key aws:PrincipalOrgID. For detailed instructions about changing the key policy by using the AWS Management Console, see Changing a key policy in the AWS KMS Developer Guide.

You should use these features with care so that principals aren’t inadvertently allowed or denied access.

Policy sample to allow a role in another account to use a KMS key

To grant another account access to a KMS key, update its key policy to grant access to the external account or role. For instructions, see Allowing users in other accounts to use a KMS key in the AWS KMS Developer Guide.
```
        {
            "Sid": "KeyPolicyForKMS",
            "Effect": "Allow",
            "Principal":”*”,
            "Action": [
                "kms:GenerateDataKeyWithoutPlaintext",
                "kms:Decrypt"
            ],
            "Resource": "arn:aws:kms:ap-southeast-1:111122223333:key/*",
            "Condition": {
                "StringEquals": {
				"aws:PrincipalOrgID": "o-teh8ggy8o9" ,
                    "aws:PrincipalTag/access-project": "CDO5951"
                }
            }
        }
```
The accounts are limited to roles that have an access-project=CDO5951 tag. You might attach this policy to roles in the example Alpha project.

Note: when using ABAC to grant access to an external account, you need to ensure that the tags used for ABAC are protected from modification across your organization.

Configure the S3 bucket policy.

For cross-account permissions to other AWS accounts or users in another account, you must use a bucket policy. Bucket policy is limited to a size of 20KB. For more information, see Access policy guidelines.

The idea of the S3 bucket policy is based on data classification, where the S3 bucket policy is used with deny statements that apply if the user doesn’t have the appropriate tags applied. You don’t need to explicitly deny all actions in the bucket policy, because a user must be authorized in both their identity policy and the S3 bucket policy in a cross-account scenario.

Policy sample for the S3 bucket

You can use the Amazon S3 console to add a new bucket policy or edit an existing bucket policy. For detailed instructions to create or edit a bucket policy, see Adding a bucket policy using the Amazon S3 console in the Amazon S3 User Guide. The following sample policy restricts access only to principals from organizations as listed in the policy and a specific VPC endpoint. It is important to test that all the AWS services involved in a solution can access this S3 bucket. For more information, see Resource-based policy examples in the whitepaper Building A Data Perimeter on AWS.

{
    "Version": "2012-10-17",
    "Statement": [
		{
		"Sid": "Principals-only-from-given-Org-List",
		"Effect": "Allow",
		"Principal": "*",
		"Action": "s3:ListBucket",
		"Resource": "arn:aws:s3:::sharedbucket",
		"Condition": {
			"StringLike": {
				"aws:PrincipalTag/CostCenter": "CDO",
				"aws:PrincipalTag/access-project": "CDO5951"
			},
			"StringEquals": {
				"aws:PrincipalTag/Department": "Engineering",
				"aws:PrincipalOrgID": “o-teh8ggy8o9”
				}}
		},
		{
		"Sid": "Principals-only-from-given-Org-Write",
		"Effect": "Allow",
		"Principal": "*",
		"Action": [ "s3:GetObject", "s3:PutObject"],
		"Resource": [
"arn:aws:s3:::sharedbucket", "arn:aws:s3:::sharedbucket/*"],
		"Condition": {
			"StringLike": {
				"aws:PrincipalTag/CostCenter": "CDO",
				"aws:PrincipalTag/access-project": "CDO5951"
			},
			"StringEquals": {
				"aws:PrincipalTag/Department": "Engineering",
				"aws:PrincipalOrgID": "o-teh8ggy8o9"
			}}}, 
{
            "Sid": "Access-to-specific-VPCE-only",
            "Effect": "Deny",
            "Principal": "*",
            "Action": "s3:*",
            "Resource": ["arn:aws:s3:::sharedbucket", "arn:aws:s3:::sharedbucket/*"],
                   "Condition": {
                        "StringNotEquals": {
                            "aws:sourceVpce": "vpce-xxxxxxxx" }
                    }
                },
     {
                    "Sid": "DenyPrincipalsNotonlyfromGivenOrg",
                    "Principal": "*",
                    "Effect": "Deny",
                    "Action": [ "s3:GetObject", "s3:GetObjectVersion" ],
                    "Resource": "arn:aws:s3:::sharedbucket/*",
                    "Condition": {
                        "StringNotEquals": {
                            "aws:PrincipalOrgID": “o-teh8ggy8o9”
                        }
}}			
        ]
}

For an additional layer of protection, you can configure the S3 bucket policy.
You can use S3 bucket policies to control access to buckets from specific VPC endpoints, or specific VPCs.

In addition, the S3 bucket policy should be scoped down to explicitly deny the following:
- Non-approved IP addresses
- Incorrect encryption keys
- Non-SSL connections
- Un-encrypted object uploads
Policy sample for VPCE-bucket policy enhancements

The setup of VPC endpoints is described in the Amazon VPC User Guide.

To create an interface endpoint, you must specify the VPC in which to create the interface endpoint, and the service to which to establish the connection.

You can download this sample policy.
Configure the SAML IdP (if you have one) or post in commands manually.
Typically, you configure your SAML IdP to pass in the project, cost-center, and department attributes as session tags. For more information, see Passing session tags using AssumeRoleWithSAML.

The following assume-role AWS CLI command helps you perform and test this request.
```
aws sts assume-role \
--role-arn arn:aws:iam::123456789123:role/test-session-tags \
--role-session-name my-session \
--duration-seconds 43200 \
--policy file://readpolicy.json \
--tags Key=access-project,Value=CDO5951 Key=access-team, Value=Analytics Key=cost-center, Value=CDO \ 
       Key=Department,Value=Engineering \
--transitive-tag-keys Project Department \
--external-id Example987 \
--source-identity=ExampleUser
```
This example request assumes the test-session-tags role for the specified duration with the included session policy, session tags, external ID, and source identity. The resulting session is named my-session.

Cleanup

To avoid unwanted charges to your AWS account, follow the instructions to delete the AWS resources that you created during this walkthrough.

Conclusion

This post explains how to share encrypted S3 buckets across accounts at scale by granting access across a large number of accounts to a multi-tenant data lake. The approach does not use Lake Formation, which may have advantages for use-cases requiring fine-grained access control. Instead, this solution uses a central governance account combining role-chaining with session tags to produce data for the lake. Permissions are granted through these tags. For read-only consumption of data by multiple accounts, cross-account read-only access is granted through Amazon EMR analytics clusters that access the data, visualizing them though BI tools. Access to the shared buckets is restricted through bucket and identity policies. Through the use of multiple AWS services and IAM features such as KMS key policies, IAM policies, S3 bucket policies, and VPCE policies, this solution enables controls that help secure access to the data, while enabling the users to use ABAC for access.

This approach is focused on scalability; you can generalize and repurpose the steps for different requirements and projects. As a result, this scalable solution for services not integrated with AWS Lake Formation can be customized with AWS KMS by way of combining with ABAC to authorize access without editing policies or managing grants. For services that honor Lake Formation permissions, you can use the Lake Formation Developer Guide to more easily set up integrated services to encrypt and decrypt data.

In summary, the design provided here is feasible for large projects, with appropriate controls to allow scalability potentially across more than 1,000 accounts.

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