Tag Archives: service control policies

Use scalable controls to help prevent access from unexpected networks

Post Syndicated from Sowjanya Rajavaram original https://aws.amazon.com/blogs/security/use-scalable-controls-to-help-prevent-access-from-unexpected-networks/

As your organization grows, the amount of data you own and the number of data sources to store and process your data across multiple Amazon Web Services (AWS) accounts increases. Enforcing consistent access controls that restrict access to known networks might become a key part in protecting your organization’s sensitive data.

Previously, AWS customers could rely on AWS Identity and Access Management (IAM) global condition keys such as aws:SourceVpc and aws:SourceVpce to restrict access to specific virtual private clouds (VPCs) or VPC endpoints. These condition keys work well for organizations with few accounts and for use cases limited to specific workloads. However, as the number of your VPCs grow, using these keys could introduce challenges in scaling the control across a large set of resources.

To address this challenge, AWS has introduced three new global condition keys for scalable access controls based on request origin: aws:VpceAccount, aws:VpceOrgPaths, and aws:VpceOrgID.

In this blog post, we demonstrate how these keys can help make sure that your AWS resources are accessible only from expected VPCs, so that you can scale your data perimeter implementation across your organization within AWS Organizations.

Background

Organizations often store data in AWS resources such as Amazon Simple Storage Service (Amazon S3) buckets. For example, you might use Amazon S3 as your data lake foundation with data scientists and analysts running their data processing and analytics workflows against data stored in a centralized S3 bucket.

To limit access to data stored in your S3 buckets to expected networks, you can use IAM policies associated with your identities and resources. You can define expected networks in a policy using specific IAM global condition keys based on your organization’s intended data access patterns and unique requirements. For example, use aws:SourceIp to specify your corporate IP CIDR ranges, and aws:SourceVpc or aws:SourceVpce to list VPC and VPC endpoint IDs you expect requests to come from. These condition keys help make sure that only workloads operating within your expected network boundaries can access sensitive data.

However, there are scenarios where you might want to allow access from multiple networks within your organization, as illustrated in Figure 1.

Figure 1: Applications and users accessing an S3 bucket from VPCs and public networks

Figure 1: Applications and users accessing an S3 bucket from VPCs and public networks

In such cases, using the aws:SourceVpc and aws:SourceVpce condition keys requires enumerating all expected VPC and VPC endpoint IDs and updating policies whenever new VPCs or VPC endpoints are added or deleted. This approach creates operational overhead and increases the risk of misconfigurations. The operational complexity grows as organizations scale their data processing capacity across multiple AWS Regions and accounts. While many organizations have developed automated mechanisms to detect changes in VPC configurations and update policies accordingly, auditing lengthy policies that enumerate VPCs within their organization remains challenging.

The new global condition keys provide a more scalable way to restrict access to expected networks:

  • aws:VpceAccount – Restricts the use of your identities and resources to networks that belong to a specific AWS account.
  • aws:VpceOrgPaths – Restricts the use of your identities and resources to networks that belong to a specific organizational unit (OU) in your organization.
  • aws:VpceOrgID – Restricts the use of your identities and resources to networks that belong to your organization.

The value of these keys in the request context is the ID of the account (for example, 111122223333), organization unit (OU) (for example, o-abcdef0123/r-acroot/ou-development/*), or organization (for example, o-abcdef0123) that owns the VPC endpoint the request is made through.

You can use the preceding keys in relevant IAM policies such as resource control policies (RCPs), service control policies (SCPs), session policies, permissions boundaries, identity-based policies, and resource-based policies.

Note that at the time of writing, not all services support these keys. See AWS global condition context keys for a list of supported services.

Implementation examples

Let’s look at how to restrict access to expected networks using the three new condition keys for common use cases. Each of the use cases demonstrates how the new condition keys help simplify controlling access to your resources in the sample scenario from Figure 1.

Use case 1: Allow access to your S3 buckets only from networks of data processing accounts

Data owners might want to strictly manage what data workflows can access their data sources and restrict cross-account access to specific data processing accounts and networks. They can use the aws:VpceAccount condition key to allow access based on the account that owns the VPC endpoint the request is made through. The following is an example S3 bucket policy.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "AllowDataProcessingAccounts",
      "Effect": "Allow",
      "Principal": {
        "AWS": [
          "arn:aws:iam::<Central-ETL-account-ID>:role/<ETLRoleName>",
          "arn:aws:iam::<Shared-analytics-account-ID>:role/<AnalyticsRoleName>",
          "arn:aws:iam::<ML-processing-account-ID>:role/<MLRoleName>"
        ]
      },
      "Action": [
        "s3:GetObject",
        "s3:ListBucket"
      ],
      "Resource": [
        "arn:aws:s3:::<Datalake-S3-bucket-name>",
        "arn:aws:s3:::<Datalake-S3-bucket-name>/*"
      ],
      "Condition": {
        "StringEquals": {
          "aws:VpceAccount": [
             "<Central-ETL-account-ID>",
             "<Shared-analytics-account-ID>",
             "<ML-processing-account-ID>"
          ]
        }
      }
    }
  ]
}

This policy allows specific principals listed in the Principal element to list and download objects from the data lake bucket but only if they make requests from networks in one of the specified AWS accounts (StringEquals and aws:VpceAccount). Using the aws:VpceAccount condition key in this policy alleviates the need to maintain a list of VPC IDs or VPC endpoint IDs for the data processing accounts, reduces the size of the policy document, and simplifies auditing.

Use case 2: Restricting access to company networks for resources across multiple accounts

Central security teams often look for ways to enforce a set of standard access controls on resources across their entire organization. This is to meet compliance and security requirements, fulfill legal and contractual obligations, and to protect corporate data from unintended access. One such control could be used to limit access to only expected networks within the organization. In our sample scenario, this control helps prevent your data analysts and scientists from using their credentials to access data outside of your corporate environment.
The following RCP demonstrates how to enforce the network perimeter controls on S3 buckets:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "RestrictAccessToOrgVPCs",
      "Effect": "Deny",
      "Principal": "*",
      "Action": "s3:*",
      "Resource": "*",
      "Condition": {
        "NotIpAddressIfExists": {
          "aws:SourceIp": "<My-corporate-CIDR>"
        },
        "StringNotEqualsIfExists": {
          "aws:VpceOrgID": "<My-corporate-org-ID>",
          "aws:PrincipalTag/network-perimeter-exception": "true"
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false",
          "aws:ViaAWSService": "false"
        }
      }
    }
  ]
}

This policy denies access to S3 buckets and objects unless it is from expected networks defined as: your corporate IP CIDR range (NotIpAddressIfExists and aws:SourceIp), VPC endpoints in your organization (StringNotEqualsIfExists and aws:VpceOrgID), networks of AWS services that use their service principals or forward access sessions (FAS) to act on your behalf (BoolIfExists with aws:PrincipalIsAWSService and aws:ViaAWSService). It also allows access to networks of AWS services using specific service roles to access your resources (StringNotEqualsIfExists and aws:PrincipalTag/network-perimeter-exception set to true). Some organizations might need to edit this policy to allow third-party partner access. See Establishing a data perimeter on AWS: Allow access to company data only from expected networks for additional information on access patterns that need to be accounted for to meet the needs of your organization.

We used an RCP because it can be used to apply access controls centrally on resources across multiple accounts. Central security teams use RCPs to enforce security invariants on resources across their entire organization. For best practices in designing and deploying RCPs, see Effectively implementing resource control policies in a multi-account environment.

Remember to reference the list of services that support aws:VpceOrgID before using it in a policy such as an RCP. Enforcing it on an unsupported service might prevent your developers from using the service. If you need to restrict access to expected networks on a wider range of services, consider using the aws:SourceVpc and aws:SourceVpce condition keys. See the data perimeter policy examples repository that illustrate how to implement network perimeter controls for a wider range of services.

Use case 3: Restricting access based on intra-organization boundaries

Organizations often need to segment environments within their organization with varying data access requirements. For example, they might need to separate production from non-production environments or create boundaries between different business units, such as Finance, Marketing, and Sales; each operating in separate accounts. This might include making sure that resources within a specific OU can only be accessed from networks in the same OU. Central security teams can use aws:VpceOrgPaths to achieve this objective at scale.

The following is an example RCP that restricts access to your Amazon S3 and AWS Key Management Service (AWS KMS) resources so that they can only be accessed through VPC endpoints in a specific OU.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "RestrictAccessToOUVPCs",
      "Effect": "Deny",
      "Principal": "*",
      "Action": [
          "s3:*",
          "kms:*"
      ],
      "Resource": "*",
      "Condition": {
        "NotIpAddressIfExists": {
          "aws:SourceIp": "<My-corporate-CIDR>"
        },
        "ForAllValues:StringNotLikeIfExists": {
          "aws:VpceOrgPaths": "<My-corporate-org-path>"
        },
       "StringNotEqualsIfExists": {
          "aws:PrincipalTag/network-perimeter-exception": "true"
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false",
          "aws:ViaAWSService": "false"
        }
      }
    }
  ]
}

This policy is similar to the one we built for the previous use case but uses aws:VpceOrgPaths instead of aws:VpceOrgID to enforce a more granular boundary based on the requests’ network origin.

Best practices and considerations

When implementing the new condition keys, consider the following best practices.

Identify opportunities to adopt the new global condition keys by reviewing your security objectives and controls

If you currently restrict access to a wide range of resources using the aws:SourceVpc and aws:SourceVpce condition keys and want to avoid the need to enumerate VPC or VPC endpoint IDs in your policies, evaluate if you can migrate to aws:VpceAccount, aws:VpceOrgPaths, or aws:VpceOrgID. This migration decision depends on whether services you restrict access to are supported by the new condition keys. Similarly, if you plan to add network perimeter restrictions to your security baseline, first evaluate whether the new condition keys offer a more scalable solution for your target services. Only enforce the new keys on services that are currently supported. If you need to enforce the restriction on a service not yet supported, you should use aws:SourceVpc and aws:SourceVpce. Also, continue using aws:SourceVpc and aws:SourceVpce to achieve your least privilege objectives, for example if the network boundary you need to maintain for a subset of resources is scoped to specific VPCs or VPC endpoints.

Plan the implementation of the new condition keys

We recommend that you test access controls updates in a non-production environment and only promote them to production after validating their expected behavior. If you currently maintain an automation to enumerate VPC or VPC endpoint IDs in your policies and plan to migrate to the new keys, deactivate your automation only after you have completed policy updates across all environments. This approach helps make sure that your existing security posture remains intact while you progressively deploy the changes.

Monitor and validate the implementation

Use AWS CloudTrail to audit access patterns and regularly review and update your access controls as your organization structure evolves and security objectives change. For example, you might need to adjust access controls when accounts requiring access to your data lakes change, or when organizational boundaries need modification to accommodate new integrations between business units. You must establish processes to continuously evaluate the effectiveness of your controls in meeting both security and business objectives.

Conclusion

In this post, you learned how to use the new global condition keys—aws:VpceAccount, aws:VpceOrgPaths, and aws:VpceOrgID—to restrict access to expected networks at scale. By using these keys, you can:

  • Implement network perimeter controls that scale with your AWS organization.
  • Reduce the operational overhead of managing access to your data.
  • Simplify your IAM policies and reduce the risk of misconfigurations.
  • Scale your data lake implementation while maintaining security.

For more information, see:

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 IAM re:Post or contact AWS Support.


Sowjanya Rajavaram

Sowjanya Rajavaram

Sowjanya is a Sr Solution Architect who specializes in Identity and Security in AWS. Her entire career has been focused on helping customers of all sizes solve their identity and access management problems. She enjoys traveling and experiencing new cultures and food.

Tatyana Yatskevich

Tatyana Yatskevich

Tatyana is a Principal Solutions Architect in AWS Identity. She works with customers to help them build and operate in AWS in the most secure and efficient manner.

How to import existing AWS Organizations SCPs and RCPs to CloudFormation

Post Syndicated from Swara Gandhi original https://aws.amazon.com/blogs/security/how-to-import-existing-aws-organizations-scps-and-rcps-to-cloudformation/

Many AWS Organizations customers begin by creating and manually applying service control policies (SCPs) and resource control policies (RCPs) through the AWS Management Console or AWS Command Line Interface (AWS CLI) when they first set up their environments. However, as the organization grows and the number of policies increases, this manual approach can become cumbersome. It can result in limited visibility into all implemented SCPs and RCPs, the targets they’re attached to (such as accounts, organizational units (OUs), or nested OUs), and the ability to manage updates effectively. Without clear visibility and proper access controls, it becomes challenging to track who’s making changes and how they are being made.

Importing existing SCPs and RCPs into AWS CloudFormation can help streamline the management of your policies by enabling history tracking, policy validation through CloudFormation Hooks, and rollback capabilities. You can also sync stacks with source code stored in a Git repository with Git sync. With Git sync, you can use pull requests and version tracking to configure, deploy, and update your CloudFormation stacks from a centralized location. When you commit changes to the template or the deployment file, CloudFormation automatically updates the stack.

In this post, I provide a solution to import existing SCPs and RCPs into AWS CloudFormation templates using the CloudFormation infrastructure as code generator (IaC generator). By using the IaC generator, you can automate the management of your SCPs and RCPs at scale.

Important: Only existing policies are brought into CloudFormation; policies are not recreated.

Solution overview

The solution in this post includes a command line tool for discovering SCPs and RCPs in your organization and automating policy import into CloudFormation templates. The following figure shows the end-to-end flow:

Figure 1: Solution overview

Figure 1: Solution overview

The end-to-end flow shown in the preceding figure includes:

  1. Run the tool: The tool automates the following steps and can be run in the management account or delegated administrator account.
    1. Identify SCPs and RCPs in the organization: The tool begins by making API calls to the Organizations service to retrieve the policies in your environment. It then provides a count of the total number of SCPs and RCPs present.
    2. Identify AWS Control Tower SCPs and RCPs and policies without targets:
      1. AWS Control Tower SCPs and RCPs: The tool checks for SCPs and RCPs created by AWS Control Tower and lists them in the output for your review.
        • SCPs are identified by the aws-guardrails- prefix in their policy names.
        • RCPs are identified by the AWSControlTower-Controls- prefix in their policy names.
      2. Policies with no targets: The tool also identifies SCPs and RCPs that aren’t attached to an organizational unit (OU), account, or root and lists them. These policies might be redundant or need reassignment.
    3. CloudFormation IaC generator scan: At this stage, you will be prompted to confirm whether you want to import the policies to the CloudFormation templates using CloudFormation resource scan. If you select yes, the tool will initiate a CloudFormation resource scan using IaC generator to get details about the policies including policy name, targets, policy tags, and so on.
    4. Create template from scanned policy resources: The tool generates CloudFormation template with the policy resources. The template will include the policies without targets (if any).
  2. Review process: After the template is generated, it’s recommended that you preview the template using IaC generator from the CloudFormation console. We recommend viewing the template resource section to verify and adjust the generated templates as needed (step 11 of the solution deployment).
  3. Create CloudFormation stacks with the generated templates: After reviewing the templates, import them into CloudFormation stacks for deployment. It’s important to note that only existing policies are brought into CloudFormation—policies aren’t recreated. The templates reflect the current policies and policy attributes.

Consideration before implementing the solution

There are some considerations that you need to keep in mind before implementing the solution.

  • If you have enabled the AWS Organizations policy management delegation, you should run this solution from the delegated administrator account. Otherwise, you can run the solution using the management account.

    Note: Delegating management of organizations policies to a delegated administrator member account is recommended best practice.

  • AWS Control Tower SCPs and RCPs (with or without targets) won’t be imported to the CloudFormation templates because they should be managed using AWS Control Tower. Changes made to AWS Control Tower resources outside of AWS Control Tower can cause drift and affect AWS Control Tower functionality in unpredictable ways.
  • FullAWSAccess SCP and RCPFullAWSAccess RCP are AWS managed policies that won’t be imported to CloudFormation because CloudFormation stacks do not allow importing AWS managed resources.
  • You might see multiple CloudFormation templates created if you exceed the CloudFormation template size quotas. To help ensure smooth creation, the tool is designed to automatically split the content into multiple templates if necessary, allowing you to stay within the quotas while still accommodating the imported content.
  • Note that the generated templates have the following attributes set by default.
    • Deletion policy: Set to Retain. This enables persisting the policies even when their related stack is deleted.
    • Update Replace policy: Set to Delete. This enables deletion of the physical ID associated with the policy when the policy is updated.

Solution deployment

Now that you understand the solution and know the considerations to keep in mind, you’re ready to deploy the solution.

  1. Clone the solution repository.
    git clone https://github.com/aws-samples/sample-tool-for-importing-existing-AWS-SCPs-and-RCPs
    

  2. Navigate to the directory of the cloned repository.
    cd sample-tool-for-importing-existing-AWS-SCPs-and-RCPs/
    

  3. Install the solution (Python 3.10+ is supported)
    pip install .
    

  4. If you want to use a particular AWS Identity and Access Management (IAM) principal to run this tool, create a profile in ~./aws/config using an IAM principal from your AWS Organizations management account. If you have delegated policy management to a member account, make sure that you use the IAM principal from the delegated administrator account

    Note: The IAM principal will need to have the following permissions to be able to successfully run the tool.

    {
        "Version": "2012-10-17",
        "Statement": [
            {
                "Sid": "VisualEditor0",
                "Effect": "Allow",
                "Action": [
                    "organizations:Describe*",
                    "organizations:List*",
                    "cloudformation:Describe*",
                    "cloudformation:Detect*",
                    "cloudformation:Estimate*",
                    "cloudformation:Get*",
                    "cloudformation:List*",
                    "cloudformation:CreateGeneratedTemplate",
                    "cloudformation:StartResourceScan",
                    "cloudformation:UpdateGeneratedTemplate",
                    "cloudformation:CreateStack",
                    "cloudformation:DeleteStack",
                    "cloudformation:UpdateStack",
                    "cloudformation:DeleteGeneratedTemplate"
                ],
                "Resource": "*"
            }
        ]
    }
    

  5. You can run the tool specifying a profile name as a command line argument. Use the following command, replacing <profile_name> with the name of the profile you created in step 4. If you do not specify a profile, the default profile from the file ~./aws/config will be used.
    policy-importer --profile <profile_name>
    

  6. After the preceding command is executed, you will see an output displaying the total number of SCPs and RCPs found in the organization. The output will also list AWS Control Tower managed policies as INFO, in addition to policies without targets as a WARNING. At this point, you can enter Yes to proceed with scanning to import the policies, or enter No if you want to exit.

    Note: If policies without targets are detected, we recommend stopping at this point. Either delete the policies without targets or assign appropriate targets to them. You can then rerun the tool from step 5. If you proceed without addressing the policies without targets, be aware that these policies will also be included in the CloudFormation template.

    Figure 2: Terminal view with policies identified in the organization

    Figure 2: Terminal view with policies identified in the organization

  7. If you enter Yes, the CloudFormation IaC resource scan will begin immediately. You will see the resource scan ID Amazon Resource Name (ARN) displayed.

    Note: A scan can take up to 10 minutes for every 1,000 resources.

    Figure 3: Terminal view with AWS CloudFormation resource scan details

    Figure 3: Terminal view with AWS CloudFormation resource scan details

  8. You can also review the scan progress from the IaC generator page of the CloudFormation console as shown in the following figure. To get to the IaC generator page, go to the CloudFormation console and choose IaC generator from the navigation pane.
    Figure 4: View the scan summary in the CloudFormation console to track progress

    Figure 4: View the scan summary in the CloudFormation console to track progress

  9. Upon completion of the scan, the template generation process will be initiated.
    Figure 5: Terminal view showing CloudFormation template being created

    Figure 5: Terminal view showing CloudFormation template being created

  10. After the template creation is finished, sign in to the AWS CloudFormation IaC console. Choose the Templates tab to review the generated templates and verify that they align with your requirements.
    Figure 6: View CloudFormation templates in the console

    Figure 6: View CloudFormation templates in the console

  11. You can review the policies added to a template by selecting a template name.
    Figure 7: Review policies included in the template

    Figure 7: Review policies included in the template

  12. When satisfied, you can proceed to import the templates into CloudFormation stacks for deployment by selecting Import to stack.
    Figure 8: Import a template into the CloudFormation stack

    Figure 8: Import a template into the CloudFormation stack

  13. Follow the prompts to create a stack.
    Figure 9: AWS CloudFormation stack example

    Figure 9: AWS CloudFormation stack example

  14. The tool automatically creates a folder named Policies in your current directory and downloads the generated templates.

    Note: If you encounter errors, check the recommended solutions for common issues.

As shown in the following figure, there are two recommended next steps.

Figure 10: Solution overview including recommended next steps

Figure 10: Solution overview including recommended next steps

After the existing policies are imported into a CloudFormation stack, we recommend storing your CloudFormation templates in a private Git repository. You can use the Policies folder that was automatically created by the tool in the current local directory with the generated templates downloaded and set up a continuous integration and delivery (CI/CD) pipeline to efficiently manage the imported policies.

By using a Git repository, you can use version control features like pull requests, branch management, and history tracking. This approach allows your team to efficiently review, update, and deploy policies with better collaboration and control. You can also create a CI/CD pipeline to automate the deployment of changes to your CloudFormation stacks, helping to ensure that updates are consistent and reliable.

We also recommend incorporating CloudFormation Hooks in your environment. CloudFormation Hooks can help validate policies (and other resources) against best practices, to help ensure that they adhere to the correct syntax, follow security best practices, and minimize potential vulnerabilities.

Related resources:

Conclusion

Importing existing AWS Organizations service control policies (SCPs) and resource control policies (RCPs) into CloudFormation provides an efficient and scalable approach to managing and automating your AWS governance. After they’ve been imported, you can manage and update policies directly in CloudFormation, to help ensure consistency and version control across your organization. The tool also creates a Policies folder in your current directory, storing downloaded templates for use as a central repository and integration with a CI/CD pipeline.

By using CloudFormation Hooks, you can further improve your policy management by validating SCPs and RCPs against best practices and policy grammar. This approach centralizes your policy updates, making governance more automated and efficient while reducing the risk of misconfiguration.

Swara Gandhi

Swara Gandhi

Swara is a Senior Solutions Architect on the AWS Identity Solutions team. She works on building secure and scalable end-to-end identity solutions. She is passionate about everything identity, security, and cloud.

Establishing a data perimeter on AWS: Analyze your account activity to evaluate impact and refine controls

Post Syndicated from Achraf Moussadek-Kabdani original https://aws.amazon.com/blogs/security/establishing-a-data-perimeter-on-aws-analyze-your-account-activity-to-evaluate-impact-and-refine-controls/

A data perimeter on Amazon Web Services (AWS) is a set of preventive controls you can use to help establish a boundary around your data in AWS Organizations. This boundary helps ensure that your data can be accessed only by trusted identities from within networks you expect and that the data cannot be transferred outside of your organization to untrusted resources. Review the previous posts in the Establishing a data perimeter on AWS series for information about the security objectives and foundational elements needed to define and enforce each perimeter type.

In this blog post, we discuss how to use AWS logging and analytics capabilities to help accelerate the implementation and effectively operate data perimeter controls at scale.

You start your data perimeter journey by identifying access patterns that you want to prevent and defining what trusted identities, trusted resources, and expected networks mean to your organization. After you define your trust boundaries based on your business and security requirements, you can use policy examples provided in the data perimeter GitHub repository to design the authorization controls for enforcing these boundaries. Before you enforce the controls in your organization, we recommend that you assess the potential impacts on your existing workloads. Performing the assessment helps you to identify unknown data access patterns missed during the initial design phase, investigate, and refine your controls to help ensure business continuity as you deploy them.

Finally, you should continuously monitor your controls to verify that they operate as expected and consistently align with your requirements as your business grows and relationships with your trusted partners change.

Figure 1 illustrates common phases of a data perimeter journey.

Figure 1: Data perimeter implementation journey

Figure 1: Data perimeter implementation journey

The usual phases of the data perimeter journey are:

  1. Examine your security objectives
  2. Set your boundaries
  3. Design data perimeter controls
  4. Anticipate potential impacts
  5. Implement data perimeter controls
  6. Monitor data perimeter controls
  7. Continuous improvement

In this post, we focus on phase 4: Anticipate potential impacts. We demonstrate how to analyze activity observed in your AWS environment to evaluate impact and refine your data perimeter controls. We also demonstrate how you can automate the analysis by using the data perimeter helper open source tool.

You can use the same techniques to support phase 6: Monitor data perimeter controls, where you will continuously monitor data access patterns in your organization and potentially troubleshoot permissions issues caused by overly restrictive or overly permissive policies as new data access paths are introduced.

Setting prerequisites for impact analysis

In this section, we describe AWS logging and analytics capabilities that you can use to analyze impact of data perimeter controls on your environment. We also provide instructions for configuring them.

While you might have some capabilities covered by other AWS tools (for example, AWS Security Lake) or external tools, the proposed approach remains applicable. For instance, if your logs are stored in an external security data lake or your configuration state recording is performed by an external cloud security posture management (CSPM) tool, you can extract and adapt the logic from this post to suit your context. The flexibility of this approach allows you to use the existing tools and processes in your environment while benefiting from the insights provided.

Pricing

Some of the required capabilities can generate additional costs in your environment.

AWS CloudTrail charges based on the number of events delivered to Amazon Simple Storage Service (Amazon S3). Note that the first copy of management events is free. To help control costs, you can use advanced event selectors to select only events that matter to your context. For more details, see CloudTrail pricing.

AWS Config charges based on the number of configuration items delivered, the AWS Config aggregator and advanced queries are included in AWS Config pricing. To help control costs, you can select which resource types AWS Config records or change the recording frequency. For more details, see AWS Config pricing.

Amazon Athena charges based on the number of terabytes of data scanned in Amazon S3. To help control costs, use the proposed optimized tables with partitioning and reduce the time frame of your queries. For more details, see Athena pricing.

AWS Identity and Access Management Access Analyzer doesn’t charge additional costs for external access findings. For more details, see IAM Access Analyzer pricing.

Create a CloudTrail trail to record access activity

The primary capability that you will use is a CloudTrail trail. CloudTrail records AWS API calls and events from your AWS accounts that contain the following information relevant to data perimeter objectives:

  • API calls performed by your identities or on your resources (record fields: eventSource, eventName)
  • Identity that performed API calls (record field: userIdentity)
  • Network origin of API calls (record fields: sourceIPAddress, vpcEndpointId)
  • Resources API calls are performed on (record fields: resources, requestParameters)

See the CloudTrail record contents page for the description of all available fields.

Data perimeter controls are meant to be applied across a broad set of accounts and resources, therefore, we recommend using a CloudTrail organization trail that collects logs across the AWS accounts in your organization. If you don’t have an organization trail configured, follow these steps or use one of the data perimeter helper templates for deploying prerequisites. If you use AWS services that support CloudTrail data events and want to analyze the associated API calls, enable the relevant data events.

Though CloudTrail provides you information about parameters of an API request, it doesn’t reflect values of AWS Identity and Access Management (IAM) condition keys present in the request. Thus, you still need to analyze the logs to help refine your data perimeter controls.

Create an Athena table to analyze CloudTrail logs

To ease and accelerate logs analysis, use Athena to query and extract relevant data from the log files stored by CloudTrail in an S3 bucket.

To create an Athena table

  1. Open the Athena console. If this is your first time visiting the Athena console in your current AWS Region, choose Edit settings to set up a query result location in Amazon S3.
  2. Next, navigate to the Query editor and create a SQL table by entering the following DDL statement into the Athena console query editor. Make sure to replace s3://<BUCKET_NAME_WITH_PREFIX>/AWSLogs/<ORGANIZATION_ID>/ to point to the S3 bucket location that contains your CloudTrail log data and <REGIONS> with the list of AWS regions where you want to analyze API calls. For example, to analyze API calls made in the AWS Regions Paris (eu-west-3) and North Virginia (us-east-1), use eu-west-3,us-east-1. We recommend that you include us-east-1 to retrieve API calls performed on global resources such as IAM roles.
    CREATE EXTERNAL TABLE IF NOT EXISTS cloudtrail_logs (
        eventVersion STRING,
        userIdentity STRUCT<
            type: STRING,
            principalId: STRING,
            arn: STRING,
            accountId: STRING,
            invokedBy: STRING,
            accessKeyId: STRING,
            userName: STRING,
            sessionContext: STRUCT<
                attributes: STRUCT<
                    mfaAuthenticated: STRING,
                    creationDate: STRING>,
                sessionIssuer: STRUCT<
                    type: STRING,
                    principalId: STRING,
                    arn: STRING,
                    accountId: STRING,
                    userName: STRING>,
                ec2RoleDelivery: STRING,
                webIdFederationData: MAP<STRING,STRING>>>,
        eventTime STRING,
        eventSource STRING,
        eventName STRING,
        awsRegion STRING,
        sourceIpAddress STRING,
        userAgent STRING,
        errorCode STRING,
        errorMessage STRING,
        requestParameters STRING,
        responseElements STRING,
        additionalEventData STRING,
        requestId STRING,
        eventId STRING,
        readOnly STRING,
        resources ARRAY<STRUCT<
            arn: STRING,
            accountId: STRING,
            type: STRING>>,
        eventType STRING,
        apiVersion STRING,
        recipientAccountId STRING,
        serviceEventDetails STRING,
        sharedEventID STRING,
        vpcEndpointId STRING,
        tlsDetails STRUCT<
            tlsVersion:string,
            cipherSuite:string,
            clientProvidedHostHeader:string
        >
    )
    PARTITIONED BY (
    `p_account` string,
    `p_region` string,
    `p_date` string
    )
    ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'
    STORED AS INPUTFORMAT 'com.amazon.emr.cloudtrail.CloudTrailInputFormat'
    OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
    LOCATION 's3://<BUCKET_NAME_WITH_PREFIX>/AWSLogs/<ORGANIZATION_ID>/'
    TBLPROPERTIES (
        'projection.enabled'='true',
        'projection.p_date.type'='date',
        'projection.p_date.format'='yyyy/MM/dd', 
        'projection.p_date.interval'='1', 
        'projection.p_date.interval.unit'='DAYS', 
        'projection.p_date.range'='2022/01/01,NOW', 
        'projection.p_region.type'='enum',
        'projection.p_region.values'='<REGIONS>',
        'projection.p_account.type'='injected',
    'storage.location.template'='s3://<BUCKET_NAME_WITH_PREFIX>/AWSLogs/<ORGANIZATION_ID>/${p_account}/CloudTrail/${p_region}/${p_date}'
    )

  3. Finally, run the Athena query and confirm that the cloudtrail_logs table is created and appears under the list of Tables.

Create an AWS Config aggregator to enrich query results

To further reduce manual steps for retrieval of relevant data about your environment, use the AWS Config aggregator and advanced queries to enrich CloudTrail logs with the configuration state of your resources.

To have a view into the resource configurations across the accounts in your organization, we recommend using the AWS Config organization aggregator. You can use an existing aggregator or create a new one. You can also use one of the data perimeter helper templates for deploying prerequisites.

Create an IAM Access Analyzer external access analyzer

To identify resources in your organization that are shared with an external entity, use the IAM Access Analyzer external access analyzer with your organization as the zone of trust.

You can use an existing external access analyzer or create a new one.

Install the data perimeter helper tool

Finally, you will use the data perimeter helper, an open-source tool with a set of purpose-built data perimeter queries, to automate the logs analysis process.

Clone the data perimeter helper repository and follow instructions in the Getting Started section.

Analyze account activity and refine your data perimeter controls

In this section, we provide step-by-step instructions for using the AWS services and tools you configured to effectively implement common data perimeter controls. We first demonstrate how to use the configured CloudTrail trail, Athena table, and AWS Config aggregator directly. We then show you how to accelerate the analysis with the data perimeter helper.

Example 1: Review API calls to untrusted S3 buckets and refine your resource perimeter policy

One of the security objectives targeted by companies is ensuring that their identities can only put or get data to and from S3 buckets belonging to their organization to manage the risk of unintended data disclosure or access to unapproved data. You can help achieve this security objective by implementing a resource perimeter on your identities using a service control policy (SCP). Start crafting your policy by referring to the resource_perimeter_policy template provided in the data perimeter policy examples repository:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceResourcePerimeterAWSResourcesS3",
      "Effect": "Deny",
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": "*",
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<my-org-id>",
          "aws:PrincipalTag/resource-perimeter-exception": "true"
        },
        "ForAllValues:StringNotEquals": {
          "aws:CalledVia": [
            "dataexchange.amazonaws.com",
            "servicecatalog.amazonaws.com"
          ]
        }
      }
    }
  ]
}

Replace the value of the aws:ResourceOrgID condition key with your organization identifier. See the GitHub repository README file for information on other elements of the policy.

As a security engineer, you can anticipate potential impacts by reviewing account activity and CloudTrail logs. You can perform this analysis manually or use the data perimeter helper tool to streamline the process.

First, let’s explore the manual approach to understand each step in detail.

Perform impact analysis without tooling

To assess the effects of the preceding policy before deployment, review your CloudTrail logs to understand on which S3 buckets API calls are performed. The targeted Amazon S3 API calls are recorded as CloudTrail data events, so make sure you enable the S3 data event for this example. CloudTrail logs provide request parameters from which you can extract the bucket names.

Below is an example Athena query to list the targeted S3 API calls made by principals in the selected account within the last 7 days. The 7-day timeframe is set to verify that the query runs quickly, but you can adjust the timeframe later to suit your specific requirements and obtain more realistic results. Replace <ACCOUNT_ID> with the AWS account ID you want to analyze the activity of.

SELECT
  useridentity.sessioncontext.sessionissuer.arn AS principal_arn,
  useridentity.type AS principal_type,
  eventname,
  JSON_EXTRACT_SCALAR(requestparameters, '$.bucketName') AS bucketname,
  resources,
  COUNT(*) AS nb_reqs
FROM "cloudtrail_logs"
WHERE
  p_account = '<ACCOUNT_ID>'
  AND p_date BETWEEN DATE_FORMAT(CURRENT_DATE - INTERVAL '7' day, '%Y/%m/%d') AND DATE_FORMAT(CURRENT_DATE, '%Y/%m/%d')
  AND eventsource = 's3.amazonaws.com'
  -- Get only requests performed by principals in the selected account
  AND useridentity.accountid = '<ACCOUNT_ID>'
  -- Keep only the targeted API calls
  AND eventname IN ('GetObject', 'PutObject', 'PutObjectAcl')
  -- Remove API calls made by AWS service principals - `useridentity.principalid` field in CloudTrail log equals `AWSService`.
  AND useridentity.principalid != 'AWSService'
  -- Remove API calls made by service-linked roles in the selected account
    AND COALESCE(NOT regexp_like(useridentity.sessioncontext.sessionissuer.arn, '(:role/aws-service-role/)'), True)
  -- Remove calls with errors
  AND errorcode IS NULL
GROUP BY
  useridentity.sessioncontext.sessionissuer.arn,
  useridentity.type,
  eventname,
  JSON_EXTRACT_SCALAR(requestparameters, '$.bucketName'),
  resources

As shown in Figure 2, this query provides you with a list of the S3 bucket names that are being accessed by principals in the selected account, while removing calls made by service-linked roles (SLRs) because they aren’t governed by SCPs. In this example, the IAM roles AppMigrator and PartnerSync performed API calls on S3 buckets named app-logs-111111111111, raw-data-111111111111, expected-partner-999999999999, and app-migration-888888888888.

Figure 2: Sample of the Athena query results

Figure 2: Sample of the Athena query results

The CloudTrail record field resources provides information on the list of resources accessed in an event. The field is optional and can notably contain the resource Amazon Resource Names (ARNs) and the account ID of the resource owner. You can use this record field to detect resources owned by accounts not in your organization. However, because this record field is optional, to scale your approach you can also use the AWS Config aggregator data to list resources currently deployed in your organization.

To know if the S3 buckets belong to your organization or not, you can run the following AWS Config advanced query. This query lists the S3 buckets inventoried in your AWS Config organization aggregator.

SELECT
  accountId,
  awsRegion,
  resourceId
WHERE
  resourceType = 'AWS::S3::Bucket'

As shown in Figure 3, buckets expected-partner-999999999999 and app-migration-888888888888 aren’t inventoried and therefore don’t belong to this organization.

Figure 3: Sample of the AWS Config advanced query results

Figure 3: Sample of the AWS Config advanced query results

By combining the results of the Athena query and the AWS Config advanced query, you can now pinpoint S3 API calls made by principals in the selected account on S3 buckets that are not part of your AWS organization.

If you do nothing, your starting resource perimeter policy would block access to these buckets. Therefore, you should investigate with your development teams why your principals performed those API calls and refine your policy if there is a legitimate reason, such as integration with a trusted third party. If you determine, for example, that your principals have a legitimate reason to access the bucket expected-partner-999999999999, you can discover the account ID (<third-party-account-a>) that owns the bucket by reviewing the record field resources in your CloudTrail logs or investigating with your developers and edit the policy as follows:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceResourcePerimeterAWSResourcesS3",
      "Effect": "Deny",
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": "*",
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<my-org-id>",
          "aws:ResourceAccount": "<third-party-account-a>",
          "aws:PrincipalTag/resource-perimeter-exception": "true"
        },
        "ForAllValues:StringNotEquals": {
          "aws:CalledVia": [
            "dataexchange.amazonaws.com",
            "servicecatalog.amazonaws.com"
          ]
        }
      }
    }
  ]
}

Now your resource perimeter policy helps ensure that access to resources that belong to your trusted third-party partner aren’t blocked by default.

Automate impact analysis with the data perimeter helper

Data perimeter helper provides queries that perform and combine the results of Athena and AWS Config aggregator queries on your behalf to accelerate policy impact analysis.

For this example, we use the s3_scp_resource_perimeter query to analyze S3 API calls made by principals in a selected account on S3 buckets not owned by your organization or inventoried in your AWS Config aggregator.

You can first add the bucket names of your trusted third-party partners that are already known in the data perimeter helper configuration file (resource_perimeter_trusted_bucket parameter). You then run the data perimeter helper query using the following command. Replace <ACCOUNT_ID> with the AWS account ID you want to analyze the activity of.

data_perimeter_helper --list-account <ACCOUNT_ID> --list-query s3_scp_resource_perimeter

Data perimeter helper performs these actions:

  • Runs an Athena query to list S3 API calls made by principals in the selected account, filtering out:
    • S3 API calls made at the account level (for example, s3:ListAllMyBuckets)
    • S3 API calls made on buckets that your organization owns
    • S3 API calls made on buckets listed as trusted in the data perimeter helper configuration file (resource_perimeter_trusted_bucket parameter)
    • API calls made by service principals and SLRs because SCPs don’t apply to them
    • API calls with errors
  • Gets the list of S3 buckets in your organization using an AWS Config advanced query.
  • Removes from the Athena query’s results API calls performed on S3 buckets inventoried in your AWS Config aggregator. This is done as a second clean-up layer in case the optional CloudTrail record field resources isn’t populated.

Data perimeter helper exports the results in the selected format (HTML, Excel, or JSON) so that you can investigate API calls that don’t align with your initial resource perimeter policy. Figure 4 shows a sample of results in HTML:

Figure 4: Sample of the s3_scp_resource_perimeter query results

Figure 4: Sample of the s3_scp_resource_perimeter query results

The preceding data perimeter helper query results indicate that the IAM role PartnerSync performed API calls on S3 buckets that aren’t part of the organization, giving you a head start in your investigation efforts. Following the investigation, you can document a trusted partner bucket in the data perimeter helper configuration file to filter out the associated API calls from subsequent queries:

111111111111:
  network_perimeter_expected_public_cidr: [
  ]
  network_perimeter_trusted_principal: [
  ]
  network_perimeter_expected_vpc: [
  ]
  network_perimeter_expected_vpc_endpoint: [
  ]
  identity_perimeter_trusted_account: [
  ]
  identity_perimeter_trusted_principal: [
  ]
  resource_perimeter_trusted_bucket: [
    expected-partner-999999999999
  ]

With a single command line, you have identified for your selected account the S3 API calls crossing your resource perimeter boundaries. You can now refine and implement your controls while lowering the risk of potential impacts. If you want to scale your approach to other accounts, you just need to run the same query against them.

Example 2: Review granted access and API calls by untrusted identities on your S3 buckets and refine your identity perimeter policy

Another security objective pursued by companies is ensuring that their S3 buckets can be accessed only by principals belonging to their organization to manage the risk of unintended access to company data. You can help achieve this security objective by implementing an identity perimeter on your buckets. You can start by crafting your identity perimeter policy using policy samples provided in the data perimeter policy examples repository.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceIdentityPerimeter",
      "Effect": "Deny",
      "Principal": "*",
      "Action": "s3:*",
      "Resource": [
        "arn:aws:s3:::<my-data-bucket>",
        "arn:aws:s3:::<my-data-bucket>/*"
      ],
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:PrincipalOrgID": "<my-org-id>",
          "aws:PrincipalAccount": [
            "<load-balancing-account-id>",
            "<third-party-account-a>",
            "<third-party-account-b>"
          ]
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false"
        }
      }
    }
  ]
}

Replace values of the aws:PrincipalOrgID and aws:PrincipalAccount condition keys based on what trusted identities mean for your organization and on your knowledge of the intended access patterns you need to support. See the GitHub repository README file for information on elements of the policy.

To assess the effects of the preceding policy before deployment, review your IAM Access Analyzer external access findings to discover the external entities that are allowed in your S3 bucket policies. Then to accelerate your analysis, review your CloudTrail logs to learn who is performing API calls on your S3 buckets. This can help you accelerate the removal of granted but unused external accesses.

Data perimeter helper provides queries that streamline these processes for you:

Run these queries by using the following command, replacing <ACCOUNT_ID> with the AWS account ID of the buckets you want to analyze the access activity of:

data_perimeter_helper --list-account <ACCOUNT_ID> --list-query s3_external_access_org_boundary s3_bucket_policy_identity_perimeter_org_boundary

The query s3_external_access_org_boundary performs this action:

  • Extracts IAM Access Analyzer external access findings from either:
    • IAM Access Analyzer if the variable external_access_findings in the data perimeter variable file is set to IAM_ACCESS_ANALYZER
    • AWS Security Hub if the same variable is set to SECURITY_HUB. Security Hub provides cross-Region aggregation, enabling you to retrieve external access findings across your organization

The query s3_external_access_org_boundary performs this action:

  • Runs an Athena query to list S3 API calls made on S3 buckets in the selected account, filtering out:
    • API calls made by principals in the same organization
    • API calls made by principals belonging to trusted accounts listed in the data perimeter configuration file (identity_perimeter_trusted_account parameter)
    • API calls made by trusted identities listed in the data perimeter configuration file (identity_perimeter_trusted_principal parameter)

Figure 5 shows a sample of results for this query in HTML:

Figure 5: Sample of the s3_bucket_policy_identity_perimeter_org_boundary and s3_external_access_org_boundary queries results

Figure 5: Sample of the s3_bucket_policy_identity_perimeter_org_boundary and s3_external_access_org_boundary queries results

The result shows that only the bucket my-bucket-open-to-partner grants access (PutObject) to principals not in your organization. Plus, in the configured time frame, your CloudTrail trail hasn’t recorded S3 API calls made by principals not in your organization on buckets that the account 111111111111 owns.

This means that your proposed identity perimeter policy accounts for the access patterns observed in your environment. After reviewing with your developers, if the granted action on the bucket my-bucket-open-to-partner is not needed, you could deploy it on the analyzed account with a reduced risk of impacting business applications.

Example 3: Investigate resource configurations to support network perimeter controls implementation

The blog post Require services to be created only within expected networks provides an example of an SCP you can use to make sure that AWS Lambda functions can only be created or updated if associated with an Amazon Virtual Private Cloud (Amazon VPC).

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceVPCFunction",
      "Action": [
          "lambda:CreateFunction",
          "lambda:UpdateFunctionConfiguration"
       ],
      "Effect": "Deny",
      "Resource": "*",
      "Condition": {
        "Null": {
           "lambda:VpcIds": "true"
        }
      }
    }
  ]
}

Before implementing the preceding policy or to continuously review the configuration of your Lambda functions, you can use your AWS Config aggregator to understand whether there are functions in your environment that aren’t attached to a VPC.

Data perimeter helper provides the referential_lambda_function query that helps you automate the analysis. Run the query by using the following command:

data_perimeter_helper --list-query referential_lambda_function

Figure 6 shows a sample of results for this query in HTML:

Figure 6: Sample of the referential_lambda_function query results

Figure 6: Sample of the referential_lambda_function query results

By reviewing the inVpc column, you can quickly identify functions that aren’t currently associated with a VPC and investigate with your development teams before enforcing your network perimeter controls.

Example 4: Investigate access denied errors to help troubleshoot your controls

While you refine your data perimeter controls or after deploying them, you might encounter API calls that fail with an access denied error message. You can use CloudTrail logs to review those API calls and use the record to investigate the root-cause.

Data perimeter helper provides the common_only_denied query, which lists the API calls with access denied errors in the configured time frame. Run the query by using the following command, replacing <ACCOUNT_ID> with your account ID:

data_perimeter_helper --list-account <ACCOUNT_ID> --list-query common_only_denied

Figure 7 shows a sample of results for this query in HTML:

Figure 7: Sample of the common_only_denied query results

Figure 7: Sample of the common_only_denied query results

Let’s say you want to review S3 API calls with access denied error messages for one of your developers who uses a role called DevOps. You can update, in the HTML report, the input fields below the principal_arn and eventsource columns to match your lookup.

Then by reviewing the columns principal_arn, eventname, isAssumableBy, and nb_reqs, you learn that the role DevOps is assumable through a SAML provider and performed two GetObject API calls that failed with an access denied error message. By reviewing the sourceipaddress field you discover that the request has been performed from an IP address outside of your network perimeter boundary, you can then advise your developer to perform the API calls again from an expected network.

Data perimeter helper provides several ready-to-use queries and a framework to add new queries based on your data perimeter objectives and needs. See Guidelines to build a new query for detailed instructions.

Clean up

If you followed the configuration steps in this blog only to test the solution, you can clean up your account to avoid recurring charges.

If you used the data perimeter helper deployment templates, use the respective infrastructure as code commands to delete the provisioned resources (for example, for Terraform, terraform destroy).

To delete configured resources manually, follow these steps:

  • If you created a CloudTrail organization trail:
    • Navigate to the CloudTrail console, select the trail your created, and choose Delete.
    • Navigate to the Amazon S3 console and delete the S3 bucket you created to store CloudTrail logs from all accounts.
  • If you created an Athena table:
    • Navigate to the Athena console and select Query editor in the left navigation panel.
    • Run the following SQL query by replacing <TABLE_NAME> with the name of the created table:
      DROP TABLE <TABLE_NAME>

  • If you created an AWS Config aggregator:
    • Navigate to the AWS Config console and select Aggregators in the left navigation panel.
    • Select the created aggregator and select Delete from the Actions drop-down list.
  • If you installed data perimeter helper:
    • Follow the uninstallation steps in the data perimeter helper README file.

Conclusion

In this blog post, we reviewed how you can analyze access activity in your organization by using the CloudTrail logs to evaluate impact of your data perimeter controls and perform troubleshooting. We discussed how the log events data can be enriched using resource configuration information from AWS Config to streamline your analysis. Finally, we introduced the open source tool, data perimeter helper, that provides a set of data perimeter tailored queries to speed up your review process and a framework to create new queries.

For additional learning opportunities, see the Data perimeters on AWS page, which provides additional material such as a data perimeter workshop, blog posts, whitepapers, and webinar sessions.

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 Security, Identity, and Compliance re:Post or contact AWS Support.

Want more AWS Security news? Follow us on X.

Achraf Moussadek-Kabdani

Achraf Moussadek-Kabdani

Achraf is a Senior Security Specialist at AWS. He works with global financial services customers to assess and improve their security posture. He is both a builder and advisor, supporting his customers to meet their security objectives while making security a business enabler.

Tatyana Yatskevich

Tatyana Yatskevich

Tatyana is a Principal Solutions Architect in AWS Identity. She works with customers to help them build and operate in AWS in the most secure and efficient manner.

Establishing a data perimeter on AWS: Allow access to company data only from expected networks

Post Syndicated from Laura Reith original https://aws.amazon.com/blogs/security/establishing-a-data-perimeter-on-aws-allow-access-to-company-data-only-from-expected-networks/

A key part of protecting your organization’s non-public, sensitive data is to understand who can access it and from where. One of the common requirements is to restrict access to authorized users from known locations. To accomplish this, you should be familiar with the expected network access patterns and establish organization-wide guardrails to limit access to known networks. Additionally, you should verify that the credentials associated with your AWS Identity and Access Management (IAM) principals are only usable within these expected networks. On Amazon Web Services (AWS), you can use the network perimeter to apply network coarse-grained controls on your resources and principals. In this fourth blog post of the Establishing a data perimeter on AWS series, we explore the benefits and implementation considerations of defining your network perimeter.

The network perimeter is a set of coarse-grained controls that help you verify that your identities and resources can only be used from expected networks.

To achieve these security objectives, you first must define what expected networks means for your organization. Expected networks usually include approved networks your employees and applications use to access your resources, such as your corporate IP CIDR range and your VPCs. There are also scenarios where you need to permit access from networks of AWS services acting on your behalf or networks of trusted third-party partners that you integrate with. You should consider all intended data access patterns when you create the definition of expected networks. Other networks are considered unexpected and shouldn’t be allowed access.

Security risks addressed by the network perimeter

The network perimeter helps address the following security risks:

Unintended information disclosure through credential use from non-corporate networks

It’s important to consider the security implications of having developers with preconfigured access stored on their laptops. For example, let’s say that to access an application, a developer uses a command line interface (CLI) to assume a role and uses the temporary credentials to work on a new feature. The developer continues their work at a coffee shop that has great public Wi-Fi while their credentials are still valid. Accessing data through a non-corporate network means that they are potentially bypassing their company’s security controls, which might lead to the unintended disclosure of sensitive corporate data in a public space.

Unintended data access through stolen credentials

Organizations are prioritizing protection from credential theft risks, as threat actors can use stolen credentials to gain access to sensitive data. For example, a developer could mistakenly share credentials from an Amazon EC2 instance CLI access over email. After credentials are obtained, a threat actor can use them to access your resources and potentially exfiltrate your corporate data, possibly leading to reputational risk.

Figure 1 outlines an undesirable access pattern: using an employee corporate credential to access corporate resources (in this example, an Amazon Simple Storage Service (Amazon S3) bucket) from a non-corporate network.

Figure 1: Unintended access to your S3 bucket from outside the corporate network

Figure 1: Unintended access to your S3 bucket from outside the corporate network

Implementing the network perimeter

During the network perimeter implementation, you use IAM policies and global condition keys to help you control access to your resources based on which network the API request is coming from. IAM allows you to enforce the origin of a request by making an API call using both identity policies and resource policies.

The following two policies help you control both your principals and resources to verify that the request is coming from your expected network:

  • Service control policies (SCPs) are policies you can use to manage the maximum available permissions for your principals. SCPs help you verify that your accounts stay within your organization’s access control guidelines.
  • Resource based policies are policies that are attached to resources in each AWS account. With resource based policies, you can specify who has access to the resource and what actions they can perform on it. For a list of services that support resource based policies, see AWS services that work with IAM.

With the help of these two policy types, you can enforce the control objectives using the following IAM global condition keys:

  • aws:SourceIp: You can use this condition key to create a policy that only allows request from a specific IP CIDR range. For example, this key helps you define your expected networks as your corporate IP CIDR range.
  • aws:SourceVpc: This condition key helps you check whether the request comes from the list of VPCs that you specified in the policy. In a policy, this condition key is used to only allow access to an S3 bucket if the VPC where the request originated matches the VPC ID listed in your policy.
  • aws:SourceVpce: You can use this condition key to check if the request came from one of the VPC endpoints specified in your policy. Adding this key to your policy helps you restrict access to API calls that originate from VPC endpoints that belong to your organization.
  • aws:ViaAWSService: You can use this key to write a policy to allow an AWS service that uses your credentials to make calls on your behalf. For example, when you upload an object to Amazon S3 with server-side encryption with AWS Key Management Service (AWS KMS) on, S3 needs to encrypt the data on your behalf. To do this, S3 makes a subsequent request to AWS KMS to generate a data key to encrypt the object. The call that S3 makes to AWS KMS is signed with your credentials and originates outside of your network.
  • aws:PrincipalIsAWSService: This condition key helps you write a policy to allow AWS service principals to access your resources. For example, when you create an AWS CloudTrail trail with an S3 bucket as a destination, CloudTrail uses a service principal, cloudtrail.amazonaws.com, to publish logs to your S3 bucket. The API call from CloudTrail comes from the service network.

The following table summarizes the relationship between the control objectives and the capabilities used to implement the network perimeter.

Control objective Implemented by using Primary IAM capability
My resources can only be accessed from expected networks. Resource-based policies aws:SourceIp
aws:SourceVpc
aws:SourceVpce
aws:ViaAWSService
aws:PrincipalIsAWSService
My identities can access resources only from expected networks. SCPs aws:SourceIp
aws:SourceVpc
aws:SourceVpce
aws:ViaAWSService

My resources can only be accessed from expected networks

Start by implementing the network perimeter on your resources using resource based policies. The perimeter should be applied to all resources that support resource- based policies in each AWS account. With this type of policy, you can define which networks can be used to access the resources, helping prevent access to your company resources in case of valid credentials being used from non-corporate networks.

The following is an example of a resource-based policy for an S3 bucket that limits access only to expected networks using the aws:SourceIp, aws:SourceVpc, aws:PrincipalIsAWSService, and aws:ViaAWSService condition keys. Replace <my-data-bucket>, <my-corporate-cidr>, and <my-vpc> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceNetworkPerimeter",
      "Effect": "Deny",
      "Principal": "*",
      "Action": "s3:*",
      "Resource": [
        "arn:aws:s3:::<my-data-bucket>",
        "arn:aws:s3:::<my-data-bucket>/*"
      ],
      "Condition": {
        "NotIpAddressIfExists": {
          "aws:SourceIp": "<my-corporate-cidr>"
        },
        "StringNotEqualsIfExists": {
          "aws:SourceVpc": "<my-vpc>"
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false",
          "aws:ViaAWSService": "false"
        }
      }
    }
  ]
}

The Deny statement in the preceding policy has four condition keys where all conditions must resolve to true to invoke the Deny effect. Use the IfExists condition operator to clearly state that each of these conditions will still resolve to true if the key is not present on the request context.

This policy will deny Amazon S3 actions unless requested from your corporate CIDR range (NotIpAddressIfExists with aws:SourceIp), or from your VPC (StringNotEqualsIfExists with aws:SourceVpc). Notice that aws:SourceVpc and aws:SourceVpce are only present on the request if the call was made through a VPC endpoint. So, you could also use the aws:SourceVpce condition key in the policy above, however this would mean listing every VPC endpoint in your environment. Since the number of VPC endpoints is greater than the number of VPCs, this example uses the aws:SourceVpc condition key.

This policy also creates a conditional exception for Amazon S3 actions requested by a service principal (BoolIfExists with aws:PrincipalIsAWSService), such as CloudTrail writing events to your S3 bucket, or by an AWS service on your behalf (BoolIfExists with aws:ViaAWSService), such as S3 calling AWS KMS to encrypt or decrypt an object.

Extending the network perimeter on resource

There are cases where you need to extend your perimeter to include AWS services that access your resources from outside your network. For example, if you’re replicating objects using S3 bucket replication, the calls to Amazon S3 originate from the service network outside of your VPC, using a service role. Another case where you need to extend your perimeter is if you integrate with trusted third-party partners that need access to your resources. If you’re using services with the described access pattern in your AWS environment or need to provide access to trusted partners, the policy EnforceNetworkPerimeter that you applied on your S3 bucket in the previous section will deny access to the resource.

In this section, you learn how to extend your network perimeter to include networks of AWS services using service roles to access your resources and trusted third-party partners.

AWS services that use service roles and service-linked roles to access resources on your behalf

Service roles are assumed by AWS services to perform actions on your behalf. An IAM administrator can create, change, and delete a service role from within IAM; this role exists within your AWS account and has an ARN like arn:aws:iam::<AccountNumber>:role/<RoleName>. A key difference between a service-linked role (SLR) and a service role is that the SLR is linked to a specific AWS service and you can view but not edit the permissions and trust policy of the role. An example is AWS Identity and Access Management Access Analyzer using an SLR to analyze resource metadata. To account for this access pattern, you can exempt roles on the service-linked role dedicated path arn:aws:iam::<AccountNumber>:role/aws-service-role/*, and for service roles, you can tag the role with the tag network-perimeter-exception set to true.

If you are exempting service roles in your policy based on a tag-value, you must also include a policy to enforce the identity perimeter on your resource as shown in this sample policy. This helps verify that only identities from your organization can access the resource and cannot circumvent your network perimeter controls with network-perimeter-exception tag.

Partners accessing your resources from their own networks

There might be situations where your company needs to grant access to trusted third parties. For example, providing a trusted partner access to data stored in your S3 bucket. You can account for this type of access by using the aws:PrincipalAccount condition key set to the account ID provided by your partner.

The following is an example of a resource-based policy for an S3 bucket that incorporates the two access patterns described above. Replace <my-data-bucket>, <my-corporate-cidr>, <my-vpc>, <third-party-account-a>, <third-party-account-b>, and <my-account-id> with your information.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "EnforceNetworkPerimeter",
            "Principal": "*",
            "Action": "s3:*",
            "Effect": "Deny",
            "Resource": [
              "arn:aws:s3:::<my-data-bucket>",
              "arn:aws:s3:::<my-data-bucket>/*"
            ],
            "Condition": {
                "NotIpAddressIfExists": {
                  "aws:SourceIp": "<my-corporate-cidr>"
                },
                "StringNotEqualsIfExists": {
                    "aws:SourceVpc": "<my-vpc>",
       "aws:PrincipalTag/network-perimeter-exception": "true",
                    "aws:PrincipalAccount": [
                        "<third-party-account-a>",
                        "<third-party-account-b>"
                    ]
                },
                "BoolIfExists": {
                    "aws:PrincipalIsAWSService": "false",
                    "aws:ViaAWSService": "false"
                },
                "ArnNotLikeIfExists": {
                    "aws:PrincipalArn": "arn:aws:iam::<my-account-id>:role/aws-service-role/*"
                }
            }
        }
    ]
}

There are four condition operators in the policy above, and you need all four of them to resolve to true to invoke the Deny effect. Therefore, this policy only allows access to Amazon S3 from expected networks defined as: your corporate IP CIDR range (NotIpAddressIfExists and aws:SourceIp), your VPC (StringNotEqualsIfExists and aws:SourceVpc), networks of AWS service principals (aws:PrincipalIsAWSService), or an AWS service acting on your behalf (aws:ViaAWSService). It also allows access to networks of trusted third-party accounts (StringNotEqualsIfExists and aws:PrincipalAccount: <third-party-account-a>), and AWS services using an SLR to access your resources (ArnNotLikeIfExists and aws:PrincipalArn).

My identities can access resources only from expected networks

Applying the network perimeter on identity can be more challenging because you need to consider not only calls made directly by your principals, but also calls made by AWS services acting on your behalf. As described in access pattern 3 Intermediate IAM roles for data access in this blog post, many AWS services assume an AWS service role you created to perform actions on your behalf. The complicating factor is that even if the service supports VPC-based access to your data — for example AWS Glue jobs can be deployed within your VPC to access data in your S3 buckets — the service might also use the service role to make other API calls outside of your VPC. For example, with AWS Glue jobs, the service uses the service role to deploy elastic network interfaces (ENIs) in your VPC. However, these calls to create ENIs in your VPC are made from the AWS Glue managed network and not from within your expected network. A broad network restriction in your SCP for all your identities might prevent the AWS service from performing tasks on your behalf.

Therefore, the recommended approach is to only apply the perimeter to identities that represent the highest risk of inappropriate use based on other compensating controls that might exist in your environment. These are identities whose credentials can be obtained and misused by threat actors. For example, if you allow your developers access to the Amazon Elastic Compute Cloud (Amazon EC2) CLI, a developer can obtain credentials from the Amazon EC2 instance profile and use the credentials to access your resources from their own network.

To summarize, to enforce your network perimeter based on identity, evaluate your organization’s security posture and what compensating controls are in place. Then, according to this evaluation, identify which service roles or human roles have the highest risk of inappropriate use, and enforce the network perimeter on those identities by tagging them with data-perimeter-include set to true.

The following policy shows the use of tags to enforce the network perimeter on specific identities. Replace <my-corporate-cidr>, and <my-vpc> with your own information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceNetworkPerimeter",
      "Effect": "Deny",
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "BoolIfExists": {
          "aws:ViaAWSService": "false"
        },
        "NotIpAddressIfExists": {
          "aws:SourceIp": [
            "<my-corporate-cidr>"
          ]
        },
        "StringNotEqualsIfExists": {
          "aws:SourceVpc": [
            "<my-vpc>"
          ]
        }, 
       "ArnNotLikeIfExists": {
          "aws:PrincipalArn": [
            "arn:aws:iam::*:role/aws:ec2-infrastructure"
          ]
        },
        "StringEquals": {
          "aws:PrincipalTag/data-perimeter-include": "true"
        }
      }
    }
  ]
}

The above policy statement uses the Deny effect to limit access to expected networks for identities with the tag data-perimeter-include attached to them (StringEquals and aws:PrincipalTag/data-perimeter-include set to true). This policy will deny access to those identities unless the request is done by an AWS service on your behalf (aws:ViaAWSService), is coming from your corporate CIDR range (NotIpAddressIfExists and aws:SourceIp), or is coming from your VPCs (StringNotEqualsIfExists with the aws:SourceVpc).

Amazon EC2 also uses a special service role, also known as infrastructure role, to decrypt Amazon Elastic Block Store (Amazon EBS). When you mount an encrypted Amazon EBS volume to an EC2 instance, EC2 calls AWS KMS to decrypt the data key that was used to encrypt the volume. The call to AWS KMS is signed by an IAM role, arn:aws:iam::*:role/aws:ec2-infrastructure, which is created in your account by EC2. For this use case, as you can see on the preceding policy, you can use the aws:PrincipalArn condition key to exclude this role from the perimeter.

IAM policy samples

This GitHub repository contains policy examples that illustrate how to implement network perimeter controls. The policy samples don’t represent a complete list of valid access patterns and are for reference only. They’re intended for you to tailor and extend to suit the needs of your environment. Make sure you thoroughly test the provided example policies before implementing them in your production environment.

Conclusion

In this blog post you learned about the elements needed to build the network perimeter, including policy examples and strategies on how to extend that perimeter. You now also know different access patterns used by AWS services that act on your behalf, how to evaluate those access patterns, and how to take a risk-based approach to apply the perimeter based on identities in your organization.

For additional learning opportunities, see the Data perimeters on AWS. This information resource provides additional materials such as a data perimeter workshop, blog posts, whitepapers, and webinar sessions.

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 Security, Identity, & Compliance re:Post or contact AWS Support.

Want more AWS Security news? Follow us on Twitter.

Author

Laura Reith

Laura is an Identity Solutions Architect at Amazon Web Services. Before AWS, she worked as a Solutions Architect in Taiwan focusing on physical security and retail analytics.

Establishing a data perimeter on AWS: Allow only trusted resources from my organization

Post Syndicated from Laura Reith original https://aws.amazon.com/blogs/security/establishing-a-data-perimeter-on-aws-allow-only-trusted-resources-from-my-organization/

Companies that store and process data on Amazon Web Services (AWS) want to prevent transfers of that data to or from locations outside of their company’s control. This is to support security strategies, such as data loss prevention, or to comply with the terms and conditions set forth by various regulatory and privacy agreements. On AWS, a resource perimeter is a set of AWS Identity and Access Management (IAM) features and capabilities that you can use to build your defense-in-depth protection against unintended data transfers. In this third blog post of the Establishing a data perimeter on AWS series, we review the benefits and implementation considerations when you define your resource perimeter.

The resource perimeter is one of the three perimeters in the data perimeter framework on AWS and has the following two control objectives:

  • My identities can access only trusted resources – This helps to ensure that IAM principals that belong to your AWS Organizations organization can access only the resources that you trust.
  • Only trusted resources can be accessed from my network – This helps to ensure that only resources that you trust can be accessed through expected networks, regardless of the principal that is making the API call.

Trusted resources are the AWS resources, such as Amazon Simple Storage Service (Amazon S3) buckets and objects or Amazon Simple Notification Service (Amazon SNS) topics, that are owned by your organization and in which you store and process your data. Additionally, there are resources outside your organization that your identities or AWS services acting on your behalf might need to access. You will need to consider these access patterns when you define your resource perimeter.

Security risks addressed by the resource perimeter

The resource perimeter helps address three main security risks.

Unintended data disclosure through use of corporate credentials — Your developers might have a personal AWS account that is not part of your organization. In that account, they could configure a resource with a resource-based policy that allows their corporate credentials to interact with the resource. For example, they could write an S3 bucket policy that allows them to upload objects by using their corporate credentials. This could allow the intentional or unintentional transfer of data from your corporate environment — your on-premises network or virtual private cloud (VPC) — to their personal account. While you advance through your least privilege journey, you should make sure that access to untrusted resources is prohibited, regardless of the permissions granted by identity-based policies that are attached to your IAM principals. Figure 1 illustrates an unintended access pattern where your employee uses an identity from your organization to move data from your on-premises or AWS environment to an S3 bucket in a non-corporate AWS account.

Figure 1: Unintended data transfer to an S3 bucket outside of your organization by your identities

Figure 1: Unintended data transfer to an S3 bucket outside of your organization by your identities

Unintended data disclosure through non-corporate credentials usage — There is a risk that developers could introduce personal IAM credentials to your corporate network and attempt to move company data to personal AWS resources. We discussed this security risk in a previous blog post: Establishing a data perimeter on AWS: Allow only trusted identities to access company data. In that post, we described how to use the aws:PrincipalOrgID condition key to prevent the use of non-corporate credentials to move data into an untrusted location. In the current post, we will show you how to implement resource perimeter controls as a defense-in-depth approach to mitigate this risk.

Unintended data infiltration — There are situations where your developers might start the solution development process using commercial datasets, tooling, or software and decide to copy them from repositories, such as those hosted on public S3 buckets. This could introduce malicious components into your corporate environment, your on-premises network, or VPCs. Establishing the resource perimeter to only allow access to trusted resources from your network can help mitigate this risk. Figure 2 illustrates the access pattern where an employee with corporate credentials downloads assets from an S3 bucket outside of your organization.

Figure 2: Unintended data infiltration

Figure 2: Unintended data infiltration

Implement the resource perimeter

To achieve the resource perimeter control objectives, you can implement guardrails in your AWS environment by using the following AWS policy types:

  • Service control policies (SCPs) – Organization policies that are used to centrally manage and set the maximum available permissions for your IAM principals. SCPs help you ensure that your accounts stay within your organization’s access control guidelines. In the context of the resource perimeter, you will use SCPs to help prevent access to untrusted resources from AWS principals that belong to your organization.
  • VPC endpoint policy – An IAM resource-based policy that is attached to a VPC endpoint to control which principals, actions, and resources can be accessed through a VPC endpoint. In the context of the resource perimeter, VPC endpoint policies are used to validate that the resource the principal is trying to access belongs to your organization.

The condition key used to constrain access to resources in your organization is aws:ResourceOrgID. You can set this key in an SCP or VPC endpoint policy. The following table summarizes the relationship between the control objectives and the AWS capabilities used to implement the resource perimeter.

Control objective Implemented by using Primary IAM capability
My identities can access only trusted resources SCPs aws:ResourceOrgID
Only trusted resources can be accessed from my network VPC endpoint policies aws:ResourceOrgID

In the next section, you will learn how to use the IAM capabilities listed in the preceding table to implement each control objective of the resource perimeter.

My identities can access only trusted resources

The following is an example of an SCP that limits all actions to only the resources that belong to your organization. Replace <MY-ORG-ID> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceResourcePerimeter",
      "Effect": "Deny",
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<MY-ORG-ID>"
        }
      }
    }
  ]
}

In this policy, notice the use of the negated condition key StringNotEqualsIfExists. This means that this condition will evaluate to true and the policy will deny API calls if the organization identifier of the resource that is being accessed differs from the one specified in the policy. It also means that this policy will deny API calls if the resource being accessed belongs to a standalone account, which isn’t part of an organization. The negated condition operators in the Deny statement mean that the condition still evaluates to true if the key is not present in the request; however, as a best practice, I added IfExists to the end of the StringNotEquals operator to clearly express the intent in the policy.

Note that for a permission to be allowed for a specific account, a statement that allows access must exist at every level of the hierarchy of your organization.

Only trusted resources can be accessed from my network

You can achieve this objective by combining the SCP we just reviewed with the use of aws:PrincipalOrgID in your VPC endpoint policies, as shown in the Establishing a data perimeter on AWS: Allow only trusted identities to access company data blog post. However, as a defense in depth, you can also apply resource perimeter controls on your networks by using aws:ResourceOrgID in your VPC endpoint policies.

The following is an example of a VPC endpoint policy that allows access to all actions but limits access to only trusted resources and identities that belong to your organization. Replace <MY-ORG-ID> with your information.

{
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "AllowRequestsByOrgsIdentitiesToOrgsResources",
			"Effect": "Allow",
			"Principal": {
				"AWS": "*"
			},
			"Action": "*",
			"Resource": "*",
			"Condition": {
				"StringEquals": {
					"aws:PrincipalOrgID": "<MY-ORG-ID>",
					"aws:ResourceOrgID": "<MY-ORG-ID>"
				}
			}
		}
	]
}

The preceding VPC endpoint policy uses the StringEquals condition operator. To invoke the Allow effect, the principal making the API call and the resource they are trying to access both need to belong to your organization. Compared to the SCP example that we reviewed earlier, your intent for this policy is different — you want to make sure that the Allow condition evaluates to true only if the specified key exists in the request. Additionally, VPC endpoint policies apply to principals, as long as their request flows through the VPC endpoint.

In VPC endpoint policies, you do not grant permissions; rather, you define the maximum allowed access through the network. Therefore, this policy uses an Allow effect.

Extend your resource perimeter

The previous two policies help you ensure that your identities and networks can only be used to access AWS resources that belong to your organization. However, your company might require that you extend your resource perimeter to also include AWS owned resources — resources that do not belong to your organization and that are accessed by your principals or by AWS services acting on your behalf. For example, if you use the AWS Service Catalog in your environment, the service creates and uses Amazon S3 buckets that are owned by the service to store products. To allow your developers to successfully provision AWS Service Catalog products, your resource perimeter needs to account for this access pattern. The following statement shows how to account for the service catalog access pattern. Replace <MY-ORG-ID> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceResourcePerimeter",
      "Effect": "Deny",
      "NotAction": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": "*",
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<MY-ORG-ID>"
        }
      }
    },
    {
      "Sid": "ExtendResourcePerimeter",
      "Effect": "Deny",
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": [
        "*"
      ],
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<MY-ORG-ID>"
        },
        "ForAllValues:StringNotEquals": {
          "aws:CalledVia": [
            "servicecatalog.amazonaws.com"
          ]
        }
      }
    }
  ]
}

Note that the EnforceResourcePerimeter statement in the SCP was modified to exclude s3:GetObject, s3:PutObject, and s3:PutObjectAcl actions from its effect (NotAction element). This is because these actions are performed by the Service Catalog to access service-owned S3 buckets. These actions are then restricted in the ExtendResourcePerimeter statement, which includes two negated condition keys. The second statement denies the previously mentioned S3 actions unless the resource that is being accessed belongs to your organization (StringNotEqualsIfExists with aws:ResourceOrgID), or the actions are performed by Service Catalog on your behalf (ForAllValues:StringNotEquals with aws:CalledVia). The aws:CalledVia condition key compares the services specified in the policy with the services that made requests on behalf of the IAM principal by using that principal’s credentials. In the case of the Service Catalog, the credentials of a principal who launches a product are used to access S3 buckets that are owned by the Service Catalog.

It is important to highlight that we are purposely not using the aws:ViaAWSService condition key in the preceding policy. This is because when you extend your resource perimeter, we recommend that you restrict access to only calls to buckets that are accessed by the service you are using.

You might also need to extend your resource perimeter to include the third-party resources of your partners. For example, you could be working with business partners that require your principals to upload or download data to or from S3 buckets that belong to their account. In this case, you can use the aws:ResourceAccount condition key in your resource perimeter policy to specify resources that belong to the trusted third-party account.

The following is an example of an SCP that accounts for access to the Service Catalog and third-party partner resources. Replace <MY-ORG-ID> and <THIRD-PARTY-ACCOUNT> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceResourcePerimeter",
      "Effect": "Deny",
      "NotAction": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": "*",
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<MY-ORG-ID>"
        }
      }
    },
    {
      "Sid": "ExtendResourcePerimeter",
      "Effect": "Deny",
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": [
        "*"
      ],
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:ResourceOrgID": "<MY-ORG-ID>",
          "aws:ResourceAccount": "<THIRD-PARTY-ACCOUNT>"
        },
        "ForAllValues:StringNotEquals": {
          "aws:CalledVia": [
            "servicecatalog.amazonaws.com"
          ]
        }
      }
    }
  ]
}

To account for access to trusted third-party account resources, the condition StringNotEqualsIfExists in the ExtendResourcePerimeter statement now also contains the condition key aws:ResourceAccount. Now, the second statement denies the previously mentioned S3 actions unless the resource that is being accessed belongs to your organization (StringNotEqualsIfExists with aws:ResourceOrgID), to a trusted third-party account (StringNotEqualsIfExists with aws:ResourceAccount), or the actions are performed by Service Catalog on your behalf (ForAllValues:StringNotEquals with aws:CalledVia).

The next policy example demonstrates how to extend your resource perimeter to permit access to resources that are owned by your trusted third parties through the networks that you control. This is required if applications running in your VPC or on-premises need to be able to access a dataset that is created and maintained in your business partner AWS account. Similar to the SCP example, you can use the aws:ResourceAccount condition key in your VPC endpoint policy to account for this access pattern. Replace <MY-ORG-ID>, <THIRD-PARTY-ACCOUNT>, and <THIRD-PARTY-RESOURCE-ARN> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "AllowRequestsByOrgsIdentitiesToOrgsResources",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "StringEquals": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>",
          "aws:ResourceOrgID": "<MY-ORG-ID>"
        }
      }
    },
    {
      "Sid": "AllowRequestsByOrgsIdentitiesToThirdPartyResources",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": [
        "s3:GetObject",
        "s3:PutObject",
        "s3:PutObjectAcl"
      ],
      "Resource": [
        "<THIRD-PARTY-RESOURCE-ARN>"
      ],
      "Condition": {
        "StringEquals": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>",
          "aws:ResourceAccount": [
            "<THIRD-PARTY-ACCOUNT>"
          ]
        }
      }
    }
  ]
}

The second statement, AllowRequestsByOrgsIdentitiesToThirdPartyResources, in the updated VPC endpoint policy allows s3:GetObject, s3:PutObject, and s3:PutObjectAcl actions on trusted third-party resources (StringEquals with aws:ResourceAccount) by principals that belong to your organization (StringEquals with aws:PrincipalOrgID).

Note that you do not need to modify your VPC endpoint policy to support the previously discussed Service Catalog operations. This is because calls to Amazon S3 made by Service Catalog on your behalf originate from the Service Catalog service network and do not traverse your VPC endpoint. However, you should consider access patterns that are similar to the Service Catalog example when defining your trusted resources. To learn about services with similar access patterns, see the IAM policy samples section later in this post.

Deploy the resource perimeter at scale

For recommendations on deploying a data perimeter at scale, see the Establishing a data perimeter on AWS: Allow only trusted identities to access company data blog post. The section titled Deploying the identity perimeter at scale provides the details on how to achieve this for your organization.

IAM policy samples

Our GitHub repository contains policy examples that illustrate how to implement perimeter controls for a variety of AWS services. The policy examples in the repository are for reference only. You will need to tailor them to suit the specific needs of your AWS environment.

Conclusion

In this blog post, you learned about the resource perimeter, the control objectives achieved by the perimeter, and how to write SCPs and VPC endpoint policies that help achieve these objectives for your organization. You also learned how to extend your perimeter to include AWS service-owned resources and your third-party partner-owned resources.

For additional learning opportunities, see the Data perimeters on AWS page. This information resource provides additional materials such as a data perimeter workshop, blog posts, whitepapers, and webinar sessions.

If you have questions, comments, or concerns, contact AWS Support or browse AWS re:Post. If you have feedback about this post, submit comments in the Comments section below.

Want more AWS Security news? Follow us on Twitter.

Author

Laura Reith

Laura is an Identity Solutions Architect at Amazon Web Services. Before AWS, she worked as a Solutions Architect in Taiwan focusing on physical security and retail analytics.

Tatyana Yatskevich

Tatyana Yatskevich

Tatyana is a Principal Solutions Architect in AWS Identity. She works with customers to help them build and operate in AWS in the most secure and efficient manner.

Establishing a data perimeter on AWS: Allow only trusted identities to access company data

Post Syndicated from Tatyana Yatskevich original https://aws.amazon.com/blogs/security/establishing-a-data-perimeter-on-aws-allow-only-trusted-identities-to-access-company-data/

As described in an earlier blog post, Establishing a data perimeter on AWS, Amazon Web Services (AWS) offers a set of capabilities you can use to implement a data perimeter to help prevent unintended access. One type of unintended access that companies want to prevent is access to corporate data by users who do not belong to the company. A combination of AWS Identity and Access Management (AWS IAM) features and capabilities that can help you achieve this goal in AWS while fostering innovation and agility form the identity perimeter. In this blog post, I will provide an overview of some of the security risks the identity perimeter is designed to address, policy examples, and implementation guidance for establishing the perimeter.

The identity perimeter is a set of coarse-grained preventative controls that help achieve the following objectives:

  • Only trusted identities can access my resources
  • Only trusted identities are allowed from my network

Trusted identities encompass IAM principals that belong to your company, which is typically represented by an AWS Organizations organization. In AWS, an IAM principal is a person or application that can make a request for an action or operation on an AWS resource. There are also scenarios when AWS services perform actions on your behalf using identities that do not belong to your organization. You should consider both types of data access patterns when you create a definition of trusted identities that is specific to your company and your use of AWS services. All other identities are considered untrusted and should have no access except by explicit exception.

Security risks addressed by the identity perimeter

The identity perimeter helps address several security risks, including the following.

Unintended data disclosure due to misconfiguration. Some AWS services support resource-based IAM policies that you can use to grant principals (including principals outside of your organization) permissions to perform actions on the resources they are attached to. While this allows developers to configure resource-based policies based on their application requirements, you should ensure that access to untrusted identities is prohibited even if the developers grant broad access to your resources, such as Amazon Simple Storage Service (Amazon S3) buckets. Figure 1 illustrates examples of access patterns you would want to prevent—specifically, principals outside of your organization accessing your S3 bucket from a non-corporate AWS account, your on-premises network, or the internet.

Figure 1: Unintended access to your S3 bucket by identities outside of your organization

Figure 1: Unintended access to your S3 bucket by identities outside of your organization

Unintended data disclosure through non-corporate credentials. Some AWS services, such as Amazon Elastic Compute Cloud (Amazon EC2) and AWS Lambda, let you run code using the IAM credentials of your choosing. Similar to on-premises environments where developers might have access to physical and virtual servers, there is a risk that the developers can bring personal IAM credentials to a corporate network and attempt to move company data to personal AWS resources. For example, Figure 2 illustrates unintended access patterns where identities outside of your AWS Organizations organization are used to transfer data from your on-premises networks or VPC to an S3 bucket in a non-corporate AWS account.

Figure 2: Unintended access from your networks by identities outside of your organization

Figure 2: Unintended access from your networks by identities outside of your organization

Implementing the identity perimeter

Before you can implement the identity perimeter by using preventative controls, you need to have a way to evaluate whether a principal is trusted and do this evaluation effectively in a multi-account AWS environment. IAM policies allow you to control access based on whether the IAM principal belongs to a particular account or an organization, with the following IAM condition keys:

  • The aws:PrincipalOrgID condition key gives you a succinct way to refer to all IAM principals that belong to a particular organization. There are similar condition keys, such as aws:PrincipalOrgPaths and aws:PrincipalAccount, that allow you to define different granularities of trust.
  • The aws:PrincipalIsAWSService condition key gives you a way to refer to AWS service principals when those are used to access resources on your behalf. For example, when you create a flow log with an S3 bucket as the destination, VPC Flow Logs uses a service principal, delivery.logs.amazonaws.com, which does not belong to your organization, to publish logs to Amazon S3.

In the context of the identity perimeter, there are two types of IAM policies that can help you ensure that the call to an AWS resource is made by a trusted identity:

Using the IAM condition keys and the policy types just listed, you can now implement the identity perimeter. The following table illustrates the relationship between identity perimeter objectives and the AWS capabilities that you can use to achieve them.

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
Only trusted identities are allowed from my network. VPC endpoint policies

Let’s see how you can use these capabilities to mitigate the risk of unintended access to your data.

Only trusted identities can access my resources

Resource-based policies allow you to specify who has access to the resource and what actions they can perform. Resource-based policies also allow you to apply identity perimeter controls to mitigate the risk of unintended data disclosure due to misconfiguration. The following is an example of a resource-based policy for an S3 bucket that limits access to only trusted identities. Make sure to replace <DOC-EXAMPLE-MY-BUCKET> and <MY-ORG-ID> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceIdentityPerimeter",
      "Effect": "Deny",
      "Principal": "*",
      "Action": "s3:*",
      "Resource": [
        "arn:aws:s3:::<DOC-EXAMPLE-MY-BUCKET>",
        "arn:aws:s3:::<DOC-EXAMPLE-MY-BUCKET>/*"
      ],
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>"
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false"
        }
      }
    }
  ]
}

The Deny statement in the preceding policy has two condition keys where both conditions must resolve to true to invoke the Deny effect. This means that this policy will deny any S3 action unless it is performed by an IAM principal within your organization (StringNotEqualsIfExists with aws:PrincipalOrgID) or a service principal (BoolIfExists with aws:PrincipalIsAWSService). Note that resource-based policies on AWS resources do not allow access outside of the account by default. Therefore, in order for another account or an AWS service to be able to access your resource directly, you need to explicitly grant access permissions with appropriate Allow statements added to the preceding policy.

Some AWS resources allow sharing through the use of AWS Resource Access Manager (AWS RAM). When you create a resource share in AWS RAM, you should choose Allow sharing with principals in your organization only to help prevent access from untrusted identities. In addition to the primary capabilities for the identity perimeter, you should also use the ram:RequestedAllowsExternalPrincipals condition key in the AWS Organizations service control policies (SCPs) to specify that resource shares cannot be created or modified to allow sharing with untrusted identities. For an example SCP, see Example service control policies for AWS Organizations and AWS RAM in the AWS RAM User Guide.

Only trusted identities are allowed from my network

When you access AWS services from on-premises networks or VPCs, you can use public service endpoints or connect to supported AWS services by using VPC endpoints. VPC endpoints allow you to apply identity perimeter controls to mitigate the risk of unintended data disclosure through non-corporate credentials. The following is an example of a VPC endpoint policy that allows access to all actions but limits the access to trusted identities only. Replace <MY-ORG-ID> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "AllowRequestsByOrgsIdentities",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "StringEquals": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>"
        }
      }
    },
    {
      "Sid": "AllowRequestsByAWSServicePrincipals",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "Bool": {
          "aws:PrincipalIsAWSService": "true"
        }
      }
    }
  ]
}

As opposed to the resource-based policy example, the preceding policy uses Allow statements to enforce the identity perimeter. This is because VPC endpoint policies do not grant any permissions but define the maximum access allowed through the endpoint. Your developers will be using identity-based or resource-based policies to grant permissions required by their applications. We use two statements in this example policy to invoke the Allow effect in two scenarios: if an action is performed by an IAM principal that belongs to your organization (StringEquals with aws:PrincipalOrgID in the AllowRequestsByOrgsIdentities statement) or if an action is performed by a service principal (Bool with aws:PrincipalIsAWSService in the AllowRequestsByAWSServicePrincipals statement). We do not use IfExists in the end of the condition operators in this case, because we want the condition elements to evaluate to true only if the specified keys exist in the request.

It is important to note that in order to apply the VPC endpoint policies to requests originating from your on-premises environment, you need to configure private connectivity to AWS through AWS Direct Connect and/or AWS Site-to-Site VPN. Proper routing rules and DNS configurations will help you to ensure that traffic to AWS services is flowing through your VPC interface endpoints and is governed by the applied policies for supported services. You might also need to implement a mechanism to prevent cross-Region API requests from bypassing the identity perimeter controls within your network.

Extending your identity perimeter

There might be circumstances when you want to grant access to your resources to principals outside of your organization. For example, you might be hosting a dataset in an Amazon S3 bucket that is being accessed by your business partners from their own AWS accounts. In order to support this access pattern, you can use the aws:PrincipalAccount condition key to include third-party account identities as trusted identities in a policy. This is shown in the following resource-based policy example. Replace <DOC-EXAMPLE-MY-BUCKET>, <MY-ORG-ID>, <THIRD-PARTY-ACCOUNT-A>, and <THIRD-PARTY-ACCOUNT-B> with your information.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EnforceIdentityPerimeter",
      "Effect": "Deny",
      "Principal": "*",
      "Action": "s3:*",
      "Resource": [
        "arn:aws:s3:::<DOC-EXAMPLE-MY-BUCKET>",
        "arn:aws:s3:::<DOC-EXAMPLE-MY-BUCKET>/*"
      ],
      "Condition": {
        "StringNotEqualsIfExists": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>",
          "aws:PrincipalAccount": [
            "<THIRD-PARTY-ACCOUNT-A>",
            "<THIRD-PARTY-ACCOUNT-B>"
          ]
        },
        "BoolIfExists": {
          "aws:PrincipalIsAWSService": "false"
        }
      }
    }
  ]
}

The preceding policy adds the aws:PrincipalAccount condition key to the StringNotEqualsIfExists operator. You now have a Deny statement with three condition keys where all three conditions must resolve to true to invoke the Deny effect. Therefore, this policy denies any S3 action unless it is performed by an IAM principal that belongs to your organization (StringNotEqualsIfExists with aws:PrincipalOrgID), by an IAM principal that belongs to specified third-party accounts (StringNotEqualsIfExists with aws:PrincipalAccount), or a service principal (BoolIfExists with aws:PrincipalIsAWSService).

There might also be circumstances when you want to grant access from your networks to identities external to your organization. For example, your applications could be uploading or downloading objects to or from a third-party S3 bucket by using third-party generated pre-signed Amazon S3 URLs. The principal that generates the pre-signed URL will belong to the third-party AWS account. Similar to the previously discussed S3 bucket policy, you can extend your identity perimeter to include identities that belong to trusted third-party accounts by using the aws:PrincipalAccount condition key in your VPC endpoint policy.

Additionally, some AWS services make unauthenticated requests to AWS owned resources through your VPC endpoint. An example of such a pattern is Kernel Live Patching on Amazon Linux 2, which allows you to apply security vulnerability and critical bug patches to a running Linux kernel. Amazon EC2 makes an unauthenticated call to Amazon S3 to download packages from Amazon Linux repositories hosted on Amazon EC2 service-owned S3 buckets. To include this access pattern into your identity perimeter definition, you can choose to allow unauthenticated API calls to AWS owned resources in the VPC endpoint policies.

The following example VPC endpoint policy demonstrates how to extend your identity perimeter to include access to Amazon Linux repositories and to Amazon S3 buckets owned by a third-party. Replace <MY-ORG-ID>, <REGION>, <ACTION>, <THIRD-PARTY-ACCOUNT-A>, and <THIRD-PARTY-BUCKET-ARN> with your information.

{
 "Version": "2012-10-17",  
 "Statement": [
    {
      "Sid": "AllowRequestsByOrgsIdentities",
      "Effect": "Allow",     
      "Principal": {
        "AWS": "*"
      },
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "StringEquals": {
          "aws:PrincipalOrgID": "<MY-ORG-ID>"
        }
      }
    },
    {
      "Sid": "AllowRequestsByAWSServicePrincipals",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": "*",
      "Resource": "*",
      "Condition": {
        "Bool": {
          "aws:PrincipalIsAWSService": "true"
        }
      }
    },
    {
      "Sid": "AllowUnauthenticatedRequestsToAWSResources",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": [
        "s3:GetObject"
      ],
      "Resource": [
        "arn:aws:s3:::packages.<REGION>.amazonaws.com/*",
        "arn:aws:s3:::repo.<REGION>.amazonaws.com/*",
        "arn:aws:s3:::amazonlinux.<REGION>.amazonaws.com/*",
        "arn:aws:s3:::amazonlinux-2-repos-<REGION>/*"
      ]
    },
    {
      "Sid": "AllowRequestsByThirdPartyIdentitiesToThirdPartyResources",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },
      "Action": "<ACTION>",
      "Resource": "<THIRD-PARTY-BUCKET-ARN>",
      "Condition": {
        "StringEquals": {
          "aws:PrincipalAccount": [
            "<THIRD-PARTY-ACCOUNT-A>"
          ]
        }
      }
    }
  ]
}

The preceding example adds two new statements to the VPC endpoint policy. The AllowUnauthenticatedRequestsToAWSResources statement allows the s3:GetObject action on buckets that host Amazon Linux repositories. The AllowRequestsByThirdPartyIdentitiesToThirdPartyResources statement allows actions on resources owned by a third-party entity by principals that belong to the third-party account (StringEquals with aws:PrincipalAccount).

Note that identity perimeter controls do not eliminate the need for additional network protections, such as making sure that your private EC2 instances or databases are not inadvertently exposed to the internet due to overly permissive security groups.

Apart from preventative controls established by the identity perimeter, we also recommend that you configure AWS Identity and Access Management Access Analyzer. IAM Access Analyzer helps you identify unintended access to your resources and data by monitoring policies applied to supported resources. You can review IAM Access Analyzer findings to identify resources that are shared with principals that do not belong to your AWS Organizations organization. You should also consider enabling Amazon GuardDuty to detect misconfigurations or anomalous access to your resources that could lead to unintended disclosure of your data. GuardDuty uses threat intelligence, machine learning, and anomaly detection to analyze data from various sources in your AWS accounts. You can review GuardDuty findings to identify unexpected or potentially malicious activity in your AWS environment, such as an IAM principal with no previous history invoking an S3 API.

IAM policy samples

This AWS git repository contains policy examples that illustrate how to implement identity perimeter controls for a variety of AWS services and actions. The policy samples do not represent a complete list of valid data access patterns and are for reference purposes only. They are intended for you to tailor and extend to suit the needs of your environment. Make sure that you thoroughly test the provided example policies before you implement them in your production environment.

Deploying the identity perimeter at scale

As discussed earlier, you implement the identity perimeter as coarse-grained preventative controls. These controls typically need to be implemented for each VPC by using VPC endpoint policies and on all resources that support resource-based policies. The effectiveness of these controls relies on their ability to scale with the environment and to adapt to its dynamic nature.

The methodology you use to deploy identity perimeter controls will depend on the deployment mechanisms you use to create and manage AWS accounts. For example, you might choose to use AWS Control Tower and the Customizations for AWS Control Tower solution (CfCT) to govern your AWS environment at scale. You can use CfCT or your custom CI/CD pipeline to deploy VPC endpoints and VPC endpoint policies that include your identity perimeter controls.

Because developers will be creating resources such as S3 buckets and AWS KMS keys on a regular basis, you might need to implement automation to enforce identity perimeter controls when those resources are created or their policies are changed. One option is to use custom AWS Config rules. Alternatively, you can choose to enforce resource deployment through AWS Service Catalog or a CI/CD pipeline. With the AWS Service Catalog approach, you can have identity perimeter controls built into the centrally controlled products that are made available to developers to deploy within their accounts. With the CI/CD pipeline approach, the pipeline can have built-in compliance checks that enforce identity perimeter controls during the deployment. If you are deploying resources with your CI/CD pipeline by using AWS CloudFormation, see the blog post Proactively keep resources secure and compliant with AWS CloudFormation Hooks.

Regardless of the deployment tools you select, identity perimeter controls, along with other baseline security controls applicable to your multi-account environment, should be included in your account provisioning process. You should also audit your identity perimeter configurations periodically and upon changes in your organization, which could lead to modifications in your identity perimeter controls (for example, disabling a third-party integration). Keeping your identity perimeter controls up to date will help ensure that they are consistently enforced and help prevent unintended access during the entire account lifecycle.

Conclusion

In this blog post, you learned about the foundational elements that are needed to define and implement the identity perimeter, including sample policies that you can use to start defining guardrails that are applicable to your environment and control objectives.

Following are additional resources that will help you further explore the identity perimeter topic, including a whitepaper and a hands-on-workshop.

If you have any questions, comments, or concerns, contact AWS Support or browse AWS re:Post. If you have feedback about this post, submit comments in the Comments section below.

Want more AWS Security news? Follow us on Twitter.

Tatyana Yatskevich

Tatyana Yatskevich

Tatyana is a Principal Solutions Architect in AWS Identity. She works with customers to help them build and operate in AWS in the most secure and efficient manner.

Get more out of service control policies in a multi-account environment

Post Syndicated from Omar Haq original https://aws.amazon.com/blogs/security/get-more-out-of-service-control-policies-in-a-multi-account-environment/

Many of our customers use AWS Organizations to manage multiple Amazon Web Services (AWS) accounts. There are many benefits to using multiple accounts in your organization, such as grouping workloads with a common business purpose, complying with regulatory frameworks, and establishing strong isolation barriers between applications based on ownership. Customers are even using distinct accounts for development, testing, and production. As these accounts proliferate, customers need a way to centrally set guardrails and controls.

In this blog post, we will walk you through different techniques that you can use to get more out of AWS Organizations service control policies (SCPs) in a multi-account environment. We focus on policy evaluation logic and how SCPs fit into it, show an overview of SCP inheritance, and describe methods for writing compact SCPs. We cover the following five techniques:

  1. Consider the number of policies per entity
  2. Use policy inheritance
  3. Segment by workload type
  4. Combine policies together
  5. Compact your policies

AWS Organizations provides a mechanism to set distinct logical boundaries by using organizational units (OUs). This is useful when you have similar workloads across different AWS accounts that require common guardrails. SCPs are a type of organization policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization. SCPs help you make sure that your accounts stay within your organization’s access control guidelines. A key distinction of SCPs is that they are useful to set broad guardrails across your environment. You can think of guardrails as a way to enforce specific governance policies at varying levels of your environment, which we will discuss in this post.

Policy evaluation logic and how SCPs fit in

Before we dig into the details, let’s first look at how SCPs work from an overall policy perspective, along with the evaluation logic. An explicit Deny statement in any policy trumps an Allow statement. Organization SCPs that apply to any AWS account that is part of an organization in AWS Organizations require an Allow statement before proceeding in the policy evaluation flow.

For an in-depth look at how policies are evaluated, see Policy evaluation logic in the documentation.

Now, let’s walk through five recommended techniques that can help you get more out of SCPs.

1. Consider the number of policies per entity

An organization is a collection of AWS accounts that you manage together. You can use OUs to group accounts within an organization and administer them as a single unit. This greatly simplifies the management of your accounts. It’s possible to create multiple OUs within a single organization, and you can create OUs within other OUs, otherwise known as nested OUs. You have the flexibility to attach multiple policies to the root of the organization, to an OU, or to an account. For example, in an organization that has the root, one OU, and one account, attaching five SCPs to each of them would produce a total of 15 SCPs (five SCPs at the root, five SCPs at the OU, and five SCPs on the one account).

The number of SCPs that you can apply is limited, and being close to or at the quota could restrict your ability to add more policies in the future. The current published quotas are as follows:

  • Maximum number of SCPs attached to the root: 5
  • Maximum number of SCPs attached to each OU: 5
  • OU maximum nesting in a root: 5 levels of OUs under a root
  • Maximum number of SCPs attached to each account: 5

Note: For the latest information on quotas, see Quotas for AWS Organizations.

Consider the following sample organization structure to understand how you can apply multiple SCPs at different levels in an organization.

Figure 1: A sample organization showing the maximum number of SCPs applicable at each level (root, OU, account)

Figure 1: A sample organization showing the maximum number of SCPs applicable at each level (root, OU, account)

2. Use policy inheritance

Policy inheritance refers to the inheritance of policies that are attached to the organization’s root or to an OU. All accounts that are members of the organization root or OU where a policy is attached are affected by that policy, but inheritance works differently for Allow and Deny statements. For a permission to be allowed for a specified account, every SCP from the root through each OU in the direct path to the account, and even attached to the account itself, must allow that permission. In other words, a statement that allows access needs to exist at every level of a hierarchy; it’s not inherited. However, a Deny statement is inherited and evaluated at each level.

At this point, you should start thinking about the policies from a broader controls perspective: Controls that you want to implement on the whole organization should go into your organization’s root-level SCP. Controls should be more granular as you move down the hierarchy in AWS Organizations.

For example, when a Deny policy is attached to the organization’s root, all accounts in the organization are affected by that policy. When you attach a Deny policy to a specific OU, accounts that are directly under that OU or nested OUs under it are affected by that policy. Because you can attach policies to multiple levels in the organization, accounts might have multiple applicable policy documents, as shown in Figure 2.

Figure 2: Sample organization showing applicable policies

Figure 2: Sample organization showing applicable policies

By default, AWS Organizations attaches an AWS managed SCP named FullAWSAccess to every root and OU when it’s created. This policy allows all services and actions.

Note: Adding an SCP with full AWS access doesn’t give all the principals in an account access to everything. SCPs don’t grant permissions; they are used to filter permissions. Principals still need a policy within the account that grants them access.

Additionally, the policies that are applied to an OU only affect the accounts or the child OUs under it and don’t affect other OUs created under the root. For example, a policy applied to the Sandbox OU doesn’t affect the Workloads OU.

The two tables that follow show examples of the policies that result from inheritance. As discussed previously, if an Allow isn’t present at all levels (root, OU, and account) the account won’t have access to any service. Consider the last example in the Sandbox OU table with a “Deny S3 access” SCP at the root, which limits access to Amazon Simple Storage Service (Amazon S3). Although there is “Allow S3 access” applied to the Sandbox OU and “Full AWS access” at the account level, the resultant policy on account A is “No service access” because there is no policy with an effect of “Allow” in the SCP at the root level.

The following table shows the inheritance of policies in the Sandbox OU.

SCP at root SCP at Sandbox OU SCP at account A Resultant policy at account A Resultant policy at accounts B and C
Full AWS access Full AWS access + deny S3 access Full AWS access + deny EC2 access No S3, no EC2 access No S3 access
Full AWS access Allow Amazon Elastic Compute Cloud (Amazon EC2) access Allow EC2 access Allows EC2 access only Allows EC2 access only
Deny S3 access Allow S3 access Full AWS access No service access No service access

The following table shows the inheritance of policies in the Workloads OU.

SCP at root SCP at Workloads OU SCP at Test OU Resultant policy at account D Resultant policies at production OU/accounts E and F
Full AWS access Full AWS access Full AWS access + deny EC2 access No EC2 access Full AWS access
Full AWS access Full AWS access Allow EC2 access Allows EC2 access Full AWS access
Deny S3 access Full AWS access Allow S3 access No service access No service access

Some examples of common root-level policies are as follows:

For sample SCPs, see Example service control policies. For insight into best practices for applying policies at different levels in an organization, see Best practices for SCPs in a multi-account environment.

3. Segment SCPs by workload type

A key feature of AWS Organizations is the ability to create distinct workload boundaries by using organizational units (OUs). You can think of OUs as a logical boundary where you can directly apply SCPs. You can also nest OUs up to five levels deep and apply different policies at each level. By using OUs, you can segment your workload types and create purpose-driven guardrails to match your security and compliance requirements.

To illustrate this, let’s take an example where there are three distinct workload types divided into three separate OUs: Infrastructure, Sandbox, and Workload, as shown in Figure 3. A best practice would be to tailor your SCPs to each specific OU type. Your security organization wouldn’t want to allow private workloads to be reachable from the internet. However, workloads that serve your external customers would require external network connectivity. To support innovation and experimentation, you can establish a Sandbox OU that has fewer policy restrictions but might limit connectivity back to your corporate data center.

For additional information on how to organize your OUs, see Recommended OUs.

Figure 3: Example organization showing different workloads

Figure 3: Example organization showing different workloads

4. Combine policies together

Similar to AWS Identity and Access Management (IAM) policies, you can have multiple statements within a service control policy. You can combine statements in a single policy to avoid hitting the quota limit of five policies per account, OU, or root. An AWS full access policy is attached by default when you enable SCPs on an organization. You can combine the full access policy with additional controls and combine statements, as shown in the following example policy. Each SCP that you apply can have a policy size of 5,120 bytes. When combining statements, make sure that the resultant statement doesn’t alter your original intent. You can combine the Action elements in an SCP if the policy has the same values for Effect, Resource, and Condition.

AWS full access policy (143 bytes)

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": "*",
            "Resource": "*"
        }
    ]
}

You can combine this full access policy with the following deny policy:

Deny bucket deletion and Security Hub disablement (260 bytes)

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Deny",
            "Action": "s3:DeleteBucket",
            "Resource": "*"
        },
        {
            "Effect": "Deny",
            "Action": "securityhub:Disable*",
            "Resource": "*"
        }
    ]
}

The resulting combined policy is as follows:

Combined policy (274 bytes)

{
   "Version":"2012-10-17",
   "Statement":[
      {
         "Effect":"Allow",
         "Action":"*",
         "Resource":"*"
      },
      {
         "Effect":"Deny",
         "Action":[
            "s3:DeleteBucket",
            "securityhub:Disable*"
         ],
         "Resource":"*"
      }
   ]
}

5. Compact your policies

One difference between IAM policies and SCPs is that whitespace counts against the size quota in SCPs. Compacting related actions in a policy can help you shorten the policy. Following are four methods to compact your policy:

  1. Remove whitespace. If you use the AWS Management Console, whitespace is automatically removed. However, if you don’t want to manually update policies by using the console every time, you can incorporate a script that removes the whitespace. (Method four later in this list provides an example of this type of script.)
  2. Use wildcards and prefixes to combine multiple actions. For example, the following policy denies access to disable configuration in AWS Security Hub.
    {
         "Effect": "Deny",
         "Action":[
            "Securityhub:DisableSecurityHub", 
            "Securityhub:DisableOrganizationAdminAccount",
            "Securityhub:DisableImportFindingsForProduct"
         ],
         "Resource": "*"
        }

    By using wildcards and prefixes, you can rewrite this policy as follows:

      {
        "Effect": "Deny",
        "Action": "Securityhub:Disable*",
        "Resource": "*"
    }

    Important: When you combine actions together as in this example, be aware that there could be a potential impact if new actions are released in the future that start with the Disable keyword, because these actions will be covered by the wildcard and denied.

  3. SCPs can be configured to work as either deny lists or allow lists. For additional details on allow lists and deny lists, see Strategies for using SCPs. We recommend that you use deny lists where possible, because they are more flexible and can help simplify your policies, which will result in less maintenance. To expand on this strategy, deny statements support conditions (as shown in the following example), and for specific resources to be specified. For example, when AWS adds a new service, you don’t have to go back and update your policy if you’ve used a deny statement. To support this, AWS Organizations attaches an AWS managed SCP named FullAWSAccess to every root and OU when it’s created. This policy allows all services and actions. Additionally, deny statements coupled with NotAction statements can help you write shorter policies.

    Consider the following scenario: Your security organization requires that application teams use specific AWS Regions. The recommended approach is to create a deny list that blocks everything except what is in the NotAction block. Following is an example where the SCP denies any operation outside of specified Regions that your organization has authorized for use.

    Note: The list includes AWS global services that cannot be allowlisted based on a Region.

    {
        "Version": "2012-10-17",
        "Statement": [
            {
                "Sid": "DenyAllOutsideEU",
                "Effect": "Deny",
                "NotAction": [
                    "a4b:*",
                    "acm:*",
                    "aws-marketplace-management:*",
                    "aws-marketplace:*",
                    "aws-portal:*",
                    "budgets:*",
                    "ce:*",
                    "chime:*",
                    "cloudfront:*",
                    "config:*",
                    "cur:*",
                    "directconnect:*",
                    "ec2:DescribeRegions",
                    "ec2:DescribeTransitGateways",
                    "ec2:DescribeVpnGateways",
                    "fms:*",
                    "globalaccelerator:*",
                    "health:*",
                    "iam:*",
                    "importexport:*",
                    "kms:*",
                    "mobileanalytics:*",
                    "networkmanager:*",
                    "organizations:*",
                    "pricing:*",
                    "route53:*",
                    "route53domains:*",
                    "s3:GetAccountPublic*",
                    "s3:ListAllMyBuckets",
                    "s3:PutAccountPublic*",
                    "shield:*",
                    "sts:*",
                    "support:*",
                    "trustedadvisor:*",
                    "waf-regional:*",
                    "waf:*",
                    "wafv2:*",
                    "wellarchitected:*"
                ],
                "Resource": "*",
                "Condition": {
                    "StringNotEquals": {
                        "aws:RequestedRegion": [
                            "eu-central-1",
                            "eu-west-1"
                        ]
                    }
                }
            }
        ]
    }

  4. Shorten the Sid value in your policy: The Sid (statement ID) is an optional identifier that you provide for the policy statement. Remove it completely from your policy if it serves no purpose for you. We also have customers who find it effective to maintain a list of SID values and details on corresponding policies in an index file locally.

The following sample Python code can compress a provided policy by removing whitespace and Sid values.

You can export the compressed policy in the file named Compressed_Policy.json or show the output on the terminal by removing # from the following code.

import json
def compress_json(policy):
    statement = policy["Statement"]
    if not isinstance(statement, list):
        statement = [statement]
    for s in statement:
        s.pop("Sid", None)
   
    # json.dumps removes whitespace around separators in a JSON and converts it to a JSON formatted string.
    # To get the most compact representation, specify separators=(item_separator, key_separator)
    policy_without_whitespace = json.dumps(policy, separators=(',', ':'))
   
    return policy_without_whitespace

if __name__ == '__main__':
  path = input("Enter the path to policy file like: \n  /Users/swara/Desktop/policy.json or ./policy.json  \n >  ")
  with open(path) as f:
    policy = json.load(f)
   
original_len = len(str(policy))
mini_policy = compress_json(policy)
#To print the output on the screen
print(mini_policy)
compressed_len = len(str(mini_policy))
print("\n \t original length: {} -> compressed length: {} \n".format(original_len, compressed_len))
#To write output to a file named Compressed_Policy.json
with open("Compressed_Policy.json", "w") as Output_file:
     print(mini_policy, file=Output_file)

Example output on screen:

{"Version":"2012-10-17","Statement":[{"Action":["iam:AttachRolePolicy","iam:DeleteRole","iam:DeleteRolePermissionsBoundary","iam:DeleteRolePolicy","iam:DetachRolePolicy","iam:PutRolePermissionsBoundary","iam:PutRolePolicy","iam:UpdateAssumeRolePolicy","iam:UpdateRole","iam:UpdateRoleDescription"],"Resource":["arn:aws:iam::*:role/role-to-deny"],"Effect":"Deny"}]}

original length: 433 -> compressed length: 364

To download the sample python code and the example policy shown above, download the files compress-policy.py and policy.json.

Conclusion

In this post, we walked you through different techniques that you can use to get more out of service control policies in a multi-account environment. By using these techniques, you can establish a well-considered strategy for how your organization can adopt SCPs in a multi-account environment. You also learned about how SCPs fit into the overall policy landscape for AWS. SCPs are a powerful tool to help customers establish guardrails. As you evaluate your IAM strategy, consider what you’re trying to achieve. If you’re trying to establish broad guardrails for multiple accounts, then we suggest looking at SCPs first.

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

Want more AWS Security news? Follow us on Twitter.

Omar Haq

Omar Haq

Omar is a senior solutions architect with AWS. He has an interest in workload migrations and modernizations, DevOps, containers, and infrastructure security. Omar has previous experience in management consulting, where he worked as a technical lead for various cloud migration projects.

Swara Gandhi

Swara Gandhi

Swara is a solutions architect on the AWS Identity Solutions team. She works on building secure and scalable end-to-end identity solutions. She is passionate about everything identity, security, and cloud.

Establishing a data perimeter on AWS

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.
Only trusted identities are allowed from my network.
Resource My identities can access only trusted resources.
Only trusted resources can be accessed from my network.
Network My identities can access resources only from expected networks.
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:

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
Only trusted identities are allowed from my network. VPC endpoint policies
Resource My identities can access only trusted resources. SCPs
Only trusted resources can be accessed from my network. VPC endpoint policies
Network My identities can access resources only from expected networks. SCPs
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
Only trusted identities are allowed from my network. VPC endpoint policies aws:PrincipalOrgID
Resource My identities can access only trusted resources. SCPs aws:ResourceOrgID
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
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.

Want more AWS Security news? Follow us on Twitter.

Author

Ilya Epshteyn

Ilya is a Senior Manager of Identity Solutions in AWS Identity. He helps customers to innovate on AWS by building highly secure, available, and scalable architectures. He enjoys spending time outdoors and building Lego creations with his kids.

How to restrict IAM roles to access AWS resources from specific geolocations using AWS Client VPN

Post Syndicated from Artem Lovan original https://aws.amazon.com/blogs/security/how-to-restrict-iam-roles-to-access-aws-resources-from-specific-geolocations-using-aws-client-vpn/

You can improve your organization’s security posture by enforcing access to Amazon Web Services (AWS) resources based on IP address and geolocation. For example, users in your organization might bring their own devices, which might require additional security authorization checks and posture assessment in order to comply with corporate security requirements. Enforcing access to AWS resources based on geolocation can help you to automate compliance with corporate security requirements by auditing the connection establishment requests. In this blog post, we walk you through the steps to allow AWS Identity and Access Management (IAM) roles to access AWS resources only from specific geographic locations.

Solution overview

AWS Client VPN is a managed client-based VPN service that enables you to securely access your AWS resources and your on-premises network resources. With Client VPN, you can access your resources from any location using an OpenVPN-based VPN client. A client VPN session terminates at the Client VPN endpoint, which is provisioned in your Amazon Virtual Private Cloud (Amazon VPC) and therefore enables a secure connection to resources running inside your VPC network.

This solution uses Client VPN to implement geolocation authentication rules. When a client VPN connection is established, authentication is implemented at the first point of entry into the AWS Cloud. It’s used to determine if clients are allowed to connect to the Client VPN endpoint. You configure an AWS Lambda function as the client connect handler for your Client VPN endpoint. You can use the handler to run custom logic that authorizes a new connection. When a user initiates a new client VPN connection, the custom logic is the point at which you can determine the geolocation of this user. In order to enforce geolocation authorization rules, you need:

  • AWS WAF to determine the user’s geolocation based on their IP address.
  • A Network address translation (NAT) gateway to be used as the public origin IP address for all requests to your AWS resources.
  • An IAM policy that is attached to the IAM role and validated by AWS when the request origin IP address matches the IP address of the NAT gateway.

One of the key features of AWS WAF is the ability to allow or block web requests based on country of origin. When the client connection handler Lambda function is invoked by your Client VPN endpoint, the Client VPN service invokes the Lambda function on your behalf. The Lambda function receives the device, user, and connection attributes. The user’s public IP address is one of the device attributes that are used to identify the user’s geolocation by using the AWS WAF geolocation feature. Only connections that are authorized by the Lambda function are allowed to connect to the Client VPN endpoint.

Note: The accuracy of the IP address to country lookup database varies by region. Based on recent tests, the overall accuracy for the IP address to country mapping is 99.8 percent. We recommend that you work with regulatory compliance experts to decide if your solution meets your compliance needs.

A NAT gateway allows resources in a private subnet to connect to the internet or other AWS services, but prevents a host on the internet from connecting to those resources. You must also specify an Elastic IP address to associate with the NAT gateway when you create it. Since an Elastic IP address is static, any request originating from a private subnet will be seen with a public IP address that you can trust because it will be the elastic IP address of your NAT gateway.

AWS Identity and Access Management (IAM) is a web service for securely controlling access to AWS services. You manage access in AWS by creating policies and attaching them to IAM identities (users, groups of users, or roles) or AWS resources. A policy is an object in AWS that, when associated with an identity or resource, defines their permissions. In an IAM policy, you can define the global condition key aws:SourceIp to restrict API calls to your AWS resources from specific IP addresses.

Note: Throughout this post, the user is authenticating with a SAML identity provider (IdP) and assumes an IAM role.

Figure 1 illustrates the authentication process when a user tries to establish a new Client VPN connection session.

Figure 1: Enforce connection to Client VPN from specific geolocations

Figure 1: Enforce connection to Client VPN from specific geolocations

Let’s look at how the process illustrated in Figure 1 works.

  1. The user device initiates a new client VPN connection session.
  2. The Client VPN service redirects the user to authenticate against an IdP.
  3. After user authentication succeeds, the client connects to the Client VPN endpoint.
  4. The Client VPN endpoint invokes the Lambda function synchronously. The function is invoked after device and user authentication, and before the authorization rules are evaluated.
  5. The Lambda function extracts the public-ip device attribute from the input and makes an HTTPS request to the Amazon API Gateway endpoint, passing the user’s public IP address in the X-Forwarded-For header.Because you’re using AWS WAF to protect API Gateway, and have geographic match conditions configured, a response with the status code 200 is returned only if the user’s public IP address originates from an allowed country of origin. Additionally, AWS WAF has another rule configured that blocks all requests to API Gateway if the request doesn’t originate from one of the NAT gateway IP addresses. Because Lambda is deployed in a VPC, it has a NAT gateway IP address, and therefore the request isn’t blocked by AWS WAF. To learn more about running a Lambda function in a VPC, see Configuring a Lambda function to access resources in a VPC.The following code example showcases Lambda code that performs the described step.

    Note: Optionally, you can implement additional controls by creating specific authorization rules. Authorization rules act as firewall rules that grant access to networks. You should have an authorization rule for each network for which you want to grant access. To learn more, see Authorization rules.

  6. The Lambda function returns the authorization request response to Client VPN.
  7. When the Lambda function—shown following—returns an allow response, Client VPN establishes the VPN session.
import os
import http.client


cloud_front_url = os.getenv("ENDPOINT_DNS")
endpoint = os.getenv("ENDPOINT")
success_status_codes = [200]


def build_response(allow, status):
    return {
        "allow": allow,
        "error-msg-on-failed-posture-compliance": "Error establishing connection. Please contact your administrator.",
        "posture-compliance-statuses": [status],
        "schema-version": "v1"
    }


def handler(event, context):
    ip = event['public-ip']

    conn = http.client.HTTPSConnection(cloud_front_url)
    conn.request("GET", f'/{endpoint}', headers={'X-Forwarded-For': ip})
    r1 = conn.getresponse()
    conn.close()

    status_code = r1.status

    if status_code in success_status_codes:
        print("User's IP is based from an allowed country. Allowing the connection to VPN.")
        return build_response(True, 'compliant')

    print("User's IP is NOT based from an allowed country. Blocking the connection to VPN.")
    return build_response(False, 'quarantined')

After the client VPN session is established successfully, the request from the user device flows through the NAT gateway. The originating source IP address is recognized, because it is the Elastic IP address associated with the NAT gateway. An IAM policy is defined that denies any request to your AWS resources that doesn’t originate from the NAT gateway Elastic IP address. By attaching this IAM policy to users, you can control which AWS resources they can access.

Figure 2 illustrates the process of a user trying to access an Amazon Simple Storage Service (Amazon S3) bucket.

Figure 2: Enforce access to AWS resources from specific IPs

Figure 2: Enforce access to AWS resources from specific IPs

Let’s look at how the process illustrated in Figure 2 works.

  1. A user signs in to the AWS Management Console by authenticating against the IdP and assumes an IAM role.
  2. Using the IAM role, the user makes a request to list Amazon S3 buckets. The IAM policy of the user is evaluated to form an allow or deny decision.
  3. If the request is allowed, an API request is made to Amazon S3.

The aws:SourceIp condition key is used in a policy to deny requests from principals if the origin IP address isn’t the NAT gateway IP address. However, this policy also denies access if an AWS service makes calls on a principal’s behalf. For example, when you use AWS CloudFormation to provision a stack, it provisions resources by using its own IP address, not the IP address of the originating request. In this case, you use aws:SourceIp with the aws:ViaAWSService key to ensure that the source IP address restriction applies only to requests made directly by a principal.

IAM deny policy

The IAM policy doesn’t allow any actions. What the policy does is deny any action on any resource if the source IP address doesn’t match any of the IP addresses in the condition. Use this policy in combination with other policies that allow specific actions.

Prerequisites

Make sure that you have the following in place before you deploy the solution:

Implementation and deployment details

In this section, you create a CloudFormation stack that creates AWS resources for this solution. To start the deployment process, select the following Launch Stack button.

Select the Launch Stack button to launch the template

You also can download the CloudFormation template if you want to modify the code before the deployment.

The template in Figure 3 takes several parameters. Let’s go over the key parameters.

Figure 3: CloudFormation stack parameters

Figure 3: CloudFormation stack parameters

The key parameters are:

  • AuthenticationOption: Information about the authentication method to be used to authenticate clients. You can choose either AWS Managed Microsoft AD or IAM SAML identity provider for authentication.
  • AuthenticationOptionResourceIdentifier: The ID of the AWS Managed Microsoft AD directory to use for Active Directory authentication, or the Amazon Resource Number (ARN) of the SAML provider for federated authentication.
  • ServerCertificateArn: The ARN of the server certificate. The server certificate must be provisioned in ACM.
  • CountryCodes: A string of comma-separated country codes. For example: US,GB,DE. The country codes must be alpha-2 country ISO codes of the ISO 3166 international standard.
  • LambdaProvisionedConcurrency: Provisioned concurrency for the client connection handler. We recommend that you configure provisioned concurrency for the Lambda function to enable it to scale without fluctuations in latency.

All other input fields have default values that you can either accept or override. Once you provide the parameter input values and reach the final screen, choose Create stack to deploy the CloudFormation stack.

This template creates several resources in your AWS account, as follows:

  • A VPC and associated resources, such as InternetGateway, Subnets, ElasticIP, NatGateway, RouteTables, and SecurityGroup.
  • A Client VPN endpoint, which provides connectivity to your VPC.
  • A Lambda function, which is invoked by the Client VPN endpoint to determine the country origin of the user’s IP address.
  • An API Gateway for the Lambda function to make an HTTPS request.
  • AWS WAF in front of API Gateway, which only allows requests to go through to API Gateway if the user’s IP address is based in one of the allowed countries.
  • A deny policy with a NAT gateway IP addresses condition. Attaching this policy to a role or user enforces that the user can’t access your AWS resources unless they are connected to your client VPN.

Note: CloudFormation stack deployment can take up to 20 minutes to provision all AWS resources.

After creating the stack, there are two outputs in the Outputs section, as shown in Figure 4.

Figure 4: CloudFormation stack outputs

Figure 4: CloudFormation stack outputs

  • ClientVPNConsoleURL: The URL where you can download the client VPN configuration file.
  • IAMRoleClientVpnDenyIfNotNatIP: The IAM policy to be attached to an IAM role or IAM user to enforce access control.

Attach the IAMRoleClientVpnDenyIfNotNatIP policy to a role

This policy is used to enforce access to your AWS resources based on geolocation. Attach this policy to the role that you are using for testing the solution. You can use the steps in Adding IAM identity permissions to do so.

Configure the AWS client VPN desktop application

When you open the URL that you see in ClientVPNConsoleURL, you see the newly provisioned Client VPN endpoint. Select Download Client Configuration to download the configuration file.

Figure 5: Client VPN endpoint

Figure 5: Client VPN endpoint

Confirm the download request by selecting Download.

Figure 6: Client VPN Endpoint - Download Client Configuration

Figure 6: Client VPN Endpoint – Download Client Configuration

To connect to the Client VPN endpoint, follow the steps in Connect to the VPN. After a successful connection is established, you should see the message Connected. in your AWS Client VPN desktop application.

Figure 7: AWS Client VPN desktop application - established VPN connection

Figure 7: AWS Client VPN desktop application – established VPN connection

Troubleshooting

If you can’t establish a Client VPN connection, here are some things to try:

  • Confirm that the Client VPN connection has successfully established. It should be in the Connected state. To troubleshoot connection issues, you can follow this guide.
  • If the connection isn’t establishing, make sure that your machine has TCP port 35001 available. This is the port used for receiving the SAML assertion.
  • Validate that the user you’re using for testing is a member of the correct SAML group on your IdP.
  • Confirm that the IdP is sending the right details in the SAML assertion. You can use browser plugins, such as SAML-tracer, to inspect the information received in the SAML assertion.

Test the solution

Now that you’re connected to Client VPN, open the console, sign in to your AWS account, and navigate to the Amazon S3 page. Since you’re connected to the VPN, your origin IP address is one of the NAT gateway IPs, and the request is allowed. You can see your S3 bucket, if any exist.

Figure 8: Amazon S3 service console view - user connected to AWS Client VPN

Figure 8: Amazon S3 service console view – user connected to AWS Client VPN

Now that you’ve verified that you can access your AWS resources, go back to the Client VPN desktop application and disconnect your VPN connection. Once the VPN connection is disconnected, go back to the Amazon S3 page and reload it. This time you should see an error message that you don’t have permission to list buckets, as shown in Figure 9.

Figure 9: Amazon S3 service console view - user is disconnected from AWS Client VPN

Figure 9: Amazon S3 service console view – user is disconnected from AWS Client VPN

Access has been denied because your origin public IP address is no longer one of the NAT gateway IP addresses. As mentioned earlier, since the policy denies any action on any resource without an established VPN connection to the Client VPN endpoint, access to all your AWS resources is denied.

Scale the solution in AWS Organizations

With AWS Organizations, you can centrally manage and govern your environment as you grow and scale your AWS resources. You can use Organizations to apply policies that give your teams the freedom to build with the resources they need, while staying within the boundaries you set. 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 Organizations, see AWS Organizations terminology and concepts.

SCPs help you to ensure that your accounts stay within your organization’s access control guidelines across all your accounts within OUs. In particular, these are the key benefits of using SCPs in your AWS Organizations:

  • You don’t have to create an IAM policy with each new account, but instead create one SCP and apply it to one or more OUs as needed.
  • You don’t have to apply the IAM policy to every IAM user or role, existing or new.
  • This solution can be deployed in a separate account, such as a shared infrastructure account. This helps to decouple infrastructure tooling from business application accounts.

The following figure, Figure 10, illustrates the solution in an Organizations environment.

Figure 10: Use SCPs to enforce policy across many AWS accounts

Figure 10: Use SCPs to enforce policy across many AWS accounts

The Client VPN account is the account the solution is deployed into. This account can also be used for other networking related services. The SCP is created in the Organizations root account and attached to one or more OUs. This allows you to centrally control access to your AWS resources.

Let’s review the new condition that’s added to the IAM policy:

"ArnNotLikeIfExists": {
    "aws:PrincipalARN": [
    "arn:aws:iam::*:role/service-role/*"
    ]
}

The aws:PrincipalARN condition key allows your AWS services to communicate to other AWS services even though those won’t have a NAT IP address as the source IP address. For instance, when a Lambda function needs to read a file from your S3 bucket.

Note: Appending policies to existing resources might cause an unintended disruption to your application. Consider testing your policies in a test environment or to non-critical resources before applying them to production resources. You can do that by attaching the SCP to a specific OU or to an individual AWS account.

Cleanup

After you’ve tested the solution, you can clean up all the created AWS resources by deleting the CloudFormation stack.

Conclusion

In this post, we showed you how you can restrict IAM users to access AWS resources from specific geographic locations. You used Client VPN to allow users to establish a client VPN connection from a desktop. You used an AWS client connection handler (as a Lambda function), and API Gateway with AWS WAF to identify the user’s geolocation. NAT gateway IPs served as trusted source IPs, and an IAM policy protects access to your AWS resources. Lastly, you learned how to scale this solution to many AWS accounts with Organizations.

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

Want more AWS Security how-to content, news, and feature announcements? Follow us on Twitter.

Author

Artem Lovan

Artem is a Senior Solutions Architect based in New York. He helps customers architect and optimize applications on AWS. He has been involved in IT at many levels, including infrastructure, networking, security, DevOps, and software development.

Author

Faiyaz Desai

Faiyaz leads a solutions architecture team supporting cloud-native customers in New York. His team guides customers in their modernization journeys through business and technology strategies, architectural best practices, and customer innovation. Faiyaz’s focus areas include unified communication, customer experience, network design, and mobile endpoint security.