Tag Archives: AWS Security Hub

Integrate Kubernetes policy-as-code solutions into Security Hub

Post Syndicated from Joaquin Manuel Rinaudo original https://aws.amazon.com/blogs/security/integrate-kubernetes-policy-as-code-solutions-into-security-hub/

Using Kubernetes policy-as-code (PaC) solutions, administrators and security professionals can enforce organization policies to Kubernetes resources. There are several publicly available PAC solutions that are available for Kubernetes, such as Gatekeeper, Polaris, and Kyverno.

PaC solutions usually implement two features:

  • Use Kubernetes admission controllers to validate or modify objects before they’re created to help enforce configuration best practices for your clusters.
  • Provide a way for you to scan your resources created before policies were deployed or against new policies being evaluated.

This post presents a solution to send policy violations from PaC solutions using Kubernetes policy report format (for example, using Kyverno) or from Gatekeeper’s constraints status directly to AWS Security Hub. With this solution, you can visualize Kubernetes security misconfigurations across your Amazon Elastic Kubernetes Service (Amazon EKS) clusters and your organizations in AWS Organizations. This can also help you implement standard security use cases—such as unified security reporting, escalation through a ticketing system, or automated remediation—on top of Security Hub to help improve your overall Kubernetes security posture and reduce manual efforts.

Solution overview

The solution uses the approach described in A Container-Free Way to Configure Kubernetes Using AWS Lambda to deploy an AWS Lambda function that periodically synchronizes the security status of a Kubernetes cluster from a Kubernetes or Gatekeeper policy report with Security Hub. Figure 1 shows the architecture diagram for the solution.

Figure 1: Diagram of solution

Figure 1: Diagram of solution

This solution works using the following resources and configurations:

  1. A scheduled event which invokes a Lambda function on a 10-minute interval.
  2. The Lambda function iterates through each running EKS cluster that you want to integrate and authenticate by using a Kubernetes Python client and an AWS Identity and Access Management (IAM) role of the Lambda function.
  3. For each running cluster, the Lambda function retrieves the selected Kubernetes policy reports (or the Gatekeeper constraint status, depending on the policy selected) and sends active violations, if present, to Security Hub. With Gatekeeper, if more violations exist than those reported in the constraint, an additional INFORMATIONAL finding is generated in Security Hub to let security teams know of the missing findings.

    Optional: EKS cluster administrators can raise the limit of reported policy violations by using the –constraint-violations-limit flag in their Gatekeeper audit operation.

  4. For each running cluster, the Lambda function archives archive previously raised and resolved findings in Security Hub.

You can download the solution from this GitHub repository.

Walkthrough

In the walkthrough, I show you how to deploy a Kubernetes policy-as-code solution and forward the findings to Security Hub. We’ll configure Kyverno and a Kubernetes demo environment with findings in an existing EKS cluster to Security Hub.

The code provided includes an example constraint and noncompliant resource to test against.

Prerequisites

An EKS cluster is required to set up this solution within your AWS environments. The cluster should be configured with either aws-auth ConfigMap or access entries. Optional: You can use eksctl to create a cluster.

The following resources need to be installed on your computer:

Step 1: Set up the environment

The first step is to install Kyverno on an existing Kubernetes cluster. Then deploy examples of a Kyverno policy and noncompliant resources.

Deploy Kyverno example and policy

  1. Deploy Kyverno in your Kubernetes cluster according to its installation manual using the Kubernetes CLI. 
    kubectl create -f https://github.com/kyverno/kyverno/releases/download/v1.10.0/install.yaml

  2. Set up a policy that requires namespaces to use the label thisshouldntexist. 
    kubectl create -f - << EOF
apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-ns-labels
spec:
  validationFailureAction: Audit
  background: true
  rules:
  - name: check-for-labels-on-namespace
    match:
      any:
      - resources:
          kinds:
          - Namespace
    validate:
      message: "The label thisshouldntexist is required."
      pattern:
        metadata:
          labels:
            thisshouldntexist: "?*"
EOF

Deploy a noncompliant resource to test this solution

  1. Create a noncompliant namespace. 
    kubectl create namespace non-compliant

  2. Check the Kubernetes policy report status using the following command: 
    kubectl get clusterpolicyreport -o yaml

You should see output similar to the following:

apiVersion: v1
items:
- apiVersion: wgpolicyk8s.io/v1alpha2
  kind: ClusterPolicyReport
  metadata:
    creationTimestamp: "2024-02-20T14:00:37Z"
    generation: 1
    labels:
      app.kubernetes.io/managed-by: kyverno
      cpol.kyverno.io/require-ns-labels: "3734083"
    name: cpol-require-ns-labels
    resourceVersion: "3734261"
    uid: 3cfcf1da-bd28-453f-b2f5-512c26065986
  results:
   ...
  - message: 'validation error: The label thisshouldntexist is required. rule check-for-labels-on-namespace
      failed at path /metadata/labels/thisshouldntexist/'
    policy: require-ns-labels
    resources:
    - apiVersion: v1
      kind: Namespace
      name: non-compliant
      uid: d62eb1ad-8a0b-476b-848d-ff6542c57840
    result: fail
    rule: check-for-labels-on-namespace
    scored: true
    source: kyverno
    timestamp:
      nanos: 0
      seconds: 1708437615

Step 2: Solution code deployment and configuration

The next step is to clone and deploy the solution that integrates with Security Hub.

To deploy the solution

  1. Clone the GitHub repository by using your preferred command line terminal: 
    git clone https://github.com/aws-samples/securityhub-k8s-policy-integration.git

  2. Open the parameters.json file and configure the following values:
    1. Policy – Name of the product that you want to enable, in this case policyreport, which is supported by tools such as Kyverno.
    2. ClusterNames – List of EKS clusters. When AccessEntryEnabled is enabled, this solution deploys an access entry for the integration to access your EKS clusters.
    3. SubnetIds – (Optional) A comma-separated list of your subnets. If you’ve configured the API endpoints of your EKS clusters as private only, then you need to configure this parameter. If your EKS clusters have public endpoints enabled, you can remove this parameter.
    4. SecurityGroupId – (Optional) A security group ID that allows connectivity to the EKS clusters. This parameter is only required if you’re running private API endpoints; otherwise, you can remove it. This security group should be allowed ingress from the security group of the EKS control plane.
    5. AccessEntryEnabled – (Optional) If you’re using EKS access entries, the solution automatically deploys the access entries with read-only-group permissions deployed in the next step. This parameter is True by default.
  3. Save the changes and close the parameters file.
  4. Set up your AWS_REGION (for example, export AWS_REGION=eu-west-1) and make sure that your credentials are configured for the delegated administrator account.
  5. Enter the following command to deploy: 
    ./deploy.sh

You should see the following output:

Waiting for changeset to be created..
Waiting for stack create/update to complete
Successfully created/updated stack - aws-securityhub-k8s-policy-integration

Step 3: Set up EKS cluster access

You need to create the Kubernetes Group read-only-group to allow read-only permissions to the IAM role of the Lambda function. If you aren’t using access entries, you will also need to modify the aws-auth ConfigMap of the Kubernetes clusters.

To configure access to EKS clusters

  1. For each cluster that’s running in your account, run the kube-setup.sh script to create the Kubernetes read-only cluster role and cluster role binding.
  2. (Optional) Configure aws-auth ConfigMap using eksctl if you aren’t using access entries.

Step 4: Verify AWS service integration

The next step is to verify that the Lambda integration to Security Hub is running.

To verify the integration is running

  1. Open the Lambda console, and navigate to the aws-securityhub-k8s-policy-integration-<region> function.
  2. Start a test to import your cluster’s noncompliant findings to Security Hub.
  3. In the Security Hub console, review the recently created findings from Kyverno.
     
    Figure 2: Sample Kyverno findings in Security Hub

    Figure 2: Sample Kyverno findings in Security Hub

Step 5: Clean up

The final step is to clean up the resources that you created for this walkthrough.

To destroy the stack

  • Use the command line terminal in your laptop to run the following command: 
    ./cleanup.sh

Conclusion

In this post, you learned how to integrate Kubernetes policy report findings with Security Hub and tested this setup by using the Kyverno policy engine. If you want to test the integration of this solution with Gatekeeper, you can find alternative commands for step 1 of this post in the GitHub repository’s README file.

Using this integration, you can gain visibility into your Kubernetes security posture across EKS clusters and join it with a centralized view, together with other security findings such as those from AWS Config, Amazon Inspector, and more across your organization. You can also try this solution with other tools, such as kube-bench or Gatekeeper. You can extend this setup to notify security teams of critical misconfigurations or implement automated remediation actions by using AWS Security Hub.

For more information on how to use PaC solutions to secure Kubernetes workloads in the AWS cloud, see Amazon Elastic Kubernetes Service (Amazon EKS) workshop, Amazon EKS best practices, Using Gatekeeper as a drop-in Pod Security Policy replacement in Amazon EKS and Policy-based countermeasures for Kubernetes.

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

Author

Joaquin Manuel Rinaudo

Joaquin is a Principal Security Architect with AWS Professional Services. He is passionate about building solutions that help developers improve their software quality. Prior to AWS, he worked across multiple domains in the security industry, from mobile security to cloud and compliance related topics. In his free time, Joaquin enjoys spending time with family and reading science fiction novels.

Accelerate security automation using Amazon CodeWhisperer

Post Syndicated from Brendan Jenkins original https://aws.amazon.com/blogs/security/accelerate-security-automation-using-amazon-codewhisperer/

In an ever-changing security landscape, teams must be able to quickly remediate security risks. Many organizations look for ways to automate the remediation of security findings that are currently handled manually. Amazon CodeWhisperer is an artificial intelligence (AI) coding companion that generates real-time, single-line or full-function code suggestions in your integrated development environment (IDE) to help you quickly build software. By using CodeWhisperer, security teams can expedite the process of writing security automation scripts for various types of findings that are aggregated in AWS Security Hub, a cloud security posture management (CSPM) service.

In this post, we present some of the current challenges with security automation and walk you through how to use CodeWhisperer, together with Amazon EventBridge and AWS Lambda, to automate the remediation of Security Hub findings. Before reading further, please read the AWS Responsible AI Policy.

Current challenges with security automation

Many approaches to security automation, including Lambda and AWS Systems Manager Automation, require software development skills. Furthermore, the process of manually writing code for remediation can be a time-consuming process for security professionals. To help overcome these challenges, CodeWhisperer serves as a force multiplier for qualified security professionals with development experience to quickly and effectively generate code to help remediate security findings.

Security professionals should still cultivate software development skills to implement robust solutions. Engineers should thoroughly review and validate any generated code, as manual oversight remains critical for security.

Solution overview

Figure 1 shows how the findings that Security Hub produces are ingested by EventBridge, which then invokes Lambda functions for processing. The Lambda code is generated with the help of CodeWhisperer.

Figure 1: Diagram of the solution

Security Hub integrates with EventBridge so you can automatically process findings with other services such as Lambda. To begin remediating the findings automatically, you can configure rules to determine where to send findings. This solution will do the following:

  1. Ingest an Amazon Security Hub finding into EventBridge.
  2. Use an EventBridge rule to invoke a Lambda function for processing.
  3. Use CodeWhisperer to generate the Lambda function code.

It is important to note that there are two types of automation for Security Hub finding remediation:

  • Partial automation, which is initiated when a human worker selects the Security Hub findings manually and applies the automated remediation workflow to the selected findings.
  • End-to-end automation, which means that when a finding is generated within Security Hub, this initiates an automated workflow to immediately remediate without human intervention.

Important: When you use end-to-end automation, we highly recommend that you thoroughly test the efficiency and impact of the workflow in a non-production environment first before moving forward with implementation in a production environment.

Prerequisites

To follow along with this walkthrough, make sure that you have the following prerequisites in place:

Implement security automation

In this scenario, you have been tasked with making sure that versioning is enabled across all Amazon Simple Storage Service (Amazon S3) buckets in your AWS account. Additionally, you want to do this in a way that is programmatic and automated so that it can be reused in different AWS accounts in the future.

To do this, you will perform the following steps:

  1. Generate the remediation script with CodeWhisperer
  2. Create the Lambda function
  3. Integrate the Lambda function with Security Hub by using EventBridge
  4. Create a custom action in Security Hub
  5. Create an EventBridge rule to target the Lambda function
  6. Run the remediation

Generate a remediation script with CodeWhisperer

The first step is to use VS Code to create a script so that CodeWhisperer generates the code for your Lambda function in Python. You will use this Lambda function to remediate the Security Hub findings generated by the [S3.14] S3 buckets should use versioning control.

Note: The underlying model of CodeWhisperer is powered by generative AI, and the output of CodeWhisperer is nondeterministic. As such, the code recommended by the service can vary by user. By modifying the initial code comment to prompt CodeWhisperer for a response, customers can change the corresponding output to help meet their needs. Customers should subject all code generated by CodeWhisperer to typical testing and review protocols to verify that it is free of errors and is in line with applicable organizational security policies. To learn about best practices on prompt engineering with CodeWhisperer, see this AWS blog post.

To generate the remediation script

  1. Open a new VS Code window, and then open or create a new folder for your file to reside in.
  2. Create a Python file called cw-blog-remediation.py as shown in Figure 2.
     
    Figure 2: New VS Code file created called cw-blog-remediation.py

    Figure 2: New VS Code file created called cw-blog-remediation.py

  3. Add the following imports to the Python file. 
    import json
import boto3

  4. Because you have the context added to your file, you can now prompt CodeWhisperer by using a natural language comment. In your file, below the import statements, enter the following comment and then press Enter. 
    # Create lambda function that turns on versioning for an S3 bucket after the function is triggered from Amazon EventBridge

  5. Accept the first recommendation that CodeWhisperer provides by pressing Tab to use the Lambda function handler, as shown in Figure 3.
    &ngsp;
    Figure 3: Generation of Lambda handler

    Figure 3: Generation of Lambda handler

  6. To get the recommendation for the function from CodeWhisperer, press Enter. Make sure that the recommendation you receive looks similar to the following. CodeWhisperer is nondeterministic, so its recommendations can vary. 
    import json
import boto3

# Create lambda function that turns on versioning for an S3 bucket after function is triggered from Amazon EventBridge
def lambda_handler(event, context):
    s3 = boto3.client('s3')
    bucket = event['detail']['requestParameters']['bucketName']
    response = s3.put_bucket_versioning(
        Bucket=bucket,
        VersioningConfiguration={
            'Status': 'Enabled'
        }
    )
    print(response)
    return {
        'statusCode': 200,
        'body': json.dumps('Versioning enabled for bucket ' + bucket)
    }

  7. Take a moment to review the user actions and keyboard shortcut keys. Press Tab to accept the recommendation.
  8. You can change the function body to fit your use case. To get the Amazon Resource Name (ARN) of the S3 bucket from the EventBridge event, replace the bucket variable with the following line: 
    bucket = event['detail']['findings'][0]['Resources'][0]['Id']

  9. To prompt CodeWhisperer to extract the bucket name from the bucket ARN, use the following comment: 
    # Take the S3 bucket name from the ARN of the S3 bucket

    Your function code should look similar to the following:

    import json
import boto3

# Create lambda function that turns on versioning for an S3 bucket after function is triggered from Amazon EventBridge
def lambda_handler(event, context):
    s3 = boto3.client('s3')
   bucket = event['detail']['findings'][0]['Resources'][0]['Id']
         # Take the S3 bucket name from the ARN of the S3 bucket
   bucket = bucket.split(':')[5]

    response = s3.put_bucket_versioning(
        Bucket=bucket,
        VersioningConfiguration={
            'Status': 'Enabled'
        }
    )
    print(response)
    return {
        'statusCode': 200,
        'body': json.dumps('Versioning enabled for bucket ' + bucket)
    }

  10. Create a .zip file for cw-blog-remediation.py. Find the file in your local file manager, right-click the file, and select compress/zip. You will use this .zip file in the next section of the post.

Create the Lambda function

The next step is to use the automation script that you generated to create the Lambda function that will enable versioning on applicable S3 buckets.

To create the Lambda function

  1. Open the AWS Lambda console.
  2. In the left navigation pane, choose Functions, and then choose Create function.
  3. Select Author from Scratch and provide the following configurations for the function:
    1. For Function name, select sec_remediation_function.
    2. For Runtime, select Python 3.12.
    3. For Architecture, select x86_64.
    4. For Permissions, select Create a new role with basic Lambda permissions.
  4. Choose Create function.
  5. To upload your local code to Lambda, select Upload from and then .zip file, and then upload the file that you zipped.
  6. Verify that you created the Lambda function successfully. In the Code source section of Lambda, you should see the code from the automation script displayed in a new tab, as shown in Figure 4.
     
    Figure 4: Source code that was successfully uploaded

    Figure 4: Source code that was successfully uploaded

  7. Choose the Code tab.
  8. Scroll down to the Runtime settings pane and choose Edit.
  9. For Handler, enter cw-blog-remediation.lambda_handler for your function handler, and then choose Save, as shown in Figure 5.
     
    Figure 5: Updated Lambda handler

    Figure 5: Updated Lambda handler

  10. For security purposes, and to follow the principle of least privilege, you should also add an inline policy to the Lambda function’s role to perform the tasks necessary to enable versioning on S3 buckets.
    1. In the Lambda console, navigate to the Configuration tab and then, in the left navigation pane, choose Permissions. Choose the Role name, as shown in Figure 6.
       
      Figure 6: Lambda role in the AWS console

      Figure 6: Lambda role in the AWS console

    2. In the Add permissions dropdown, select Create inline policy.
       
      Figure 7: Create inline policy

      Figure 7: Create inline policy

    3. Choose JSON, add the following policy to the policy editor, and then choose Next. 
      {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": "s3:PutBucketVersioning",
            "Resource": "*"
        }
    ]
}

    4. Name the policy PutBucketVersioning and choose Create policy.

Create a custom action in Security Hub

In this step, you will create a custom action in Security Hub.

To create the custom action

  1. Open the Security Hub console.
  2. In the left navigation pane, choose Settings, and then choose Custom actions.
  3. Choose Create custom action.
  4. Provide the following information, as shown in Figure 8:
    • For Name, enter TurnOnS3Versioning.
    • For Description, enter Action that will turn on versioning for a specific S3 bucket.
    • For Custom action ID, enter TurnOnS3Versioning.
       
      Figure 8: Create a custom action in Security Hub

      Figure 8: Create a custom action in Security Hub

  5. Choose Create custom action.
  6. Make a note of the Custom action ARN. You will need this ARN when you create a rule to associate with the custom action in EventBridge.

Create an EventBridge rule to target the Lambda function

The next step is to create an EventBridge rule to capture the custom action. You will define an EventBridge rule that matches events (in this case, findings) from Security Hub that were forwarded by the custom action that you defined previously.

To create the EventBridge rule

  1. Navigate to the EventBridge console.
  2. On the right side, choose Create rule.
  3. On the Define rule detail page, give your rule a name and description that represents the rule’s purpose—for example, you could use the same name and description that you used for the custom action. Then choose Next.
  4. Scroll down to Event pattern, and then do the following:
    1. For Event source, make sure that AWS services is selected.
    2. For AWS service, select Security Hub.
    3. For Event type, select Security Hub Findings – Custom Action.
    4. Select Specific custom action ARN(s) and enter the ARN for the custom action that you created earlier.
       
    Figure 9: Specify the EventBridge event pattern for the Security Hub custom action workflow

    Figure 9: Specify the EventBridge event pattern for the Security Hub custom action workflow

    As you provide this information, the Event pattern updates.

  5. Choose Next.
  6. On the Select target(s) step, in the Select a target dropdown, select Lambda function. Then from the Function dropdown, select sec_remediation_function.
  7. Choose Next.
  8. On the Configure tags step, choose Next.
  9. On the Review and create step, choose Create rule.

Run the automation

Your automation is set up and you can now test the automation. This test covers a partial automation workflow, since you will manually select the finding and apply the remediation workflow to one or more selected findings.

Important: As we mentioned earlier, if you decide to make the automation end-to-end, you should assess the impact of the workflow in a non-production environment. Additionally, you may want to consider creating preventative controls if you want to minimize the risk of event occurrence across an entire environment.

To run the automation

  1. In the Security Hub console, on the Findings tab, add a filter by entering Title in the search box and selecting that filter. Select IS and enter S3 general purpose buckets should have versioning enabled (case sensitive). Choose Apply.
  2. In the filtered list, choose the Title of an active finding.
  3. Before you start the automation, check the current configuration of the S3 bucket to confirm that your automation works. Expand the Resources section of the finding.
  4. Under Resource ID, choose the link for the S3 bucket. This opens a new tab on the S3 console that shows only this S3 bucket.
  5. In your browser, go back to the Security Hub tab (don’t close the S3 tab—you will need to return to it), and on the left side, select this same finding, as shown in Figure 10.
     
    Figure 10: Filter out Security Hub findings to list only S3 bucket-related findings

    Figure 10: Filter out Security Hub findings to list only S3 bucket-related findings

  6. In the Actions dropdown list, choose the name of your custom action.
     
    Figure 11: Choose the custom action that you created to start the remediation workflow

    Figure 11: Choose the custom action that you created to start the remediation workflow

  7. When you see a banner that displays Successfully started action…, go back to the S3 browser tab and refresh it. Verify that the S3 versioning configuration on the bucket has been enabled as shown in figure 12.
     
    Figure 12: Versioning successfully enabled

    Figure 12: Versioning successfully enabled

Conclusion

In this post, you learned how to use CodeWhisperer to produce AI-generated code for custom remediations for a security use case. We encourage you to experiment with CodeWhisperer to create Lambda functions that remediate other Security Hub findings that might exist in your account, such as the enforcement of lifecycle policies on S3 buckets with versioning enabled, or using automation to remove multiple unused Amazon EC2 elastic IP addresses. The ability to automatically set public S3 buckets to private is just one of many use cases where CodeWhisperer can generate code to help you remediate Security Hub findings.

To sum up, CodeWhisperer acts as a tool that can help boost the productivity of security experts who have coding abilities, assisting them to swiftly write code to address security issues. However, security specialists should continue building their software development capabilities to implement robust solutions. Engineers should carefully review and test any generated code, since human oversight is still vital for security.

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

Brendan Jenkins

Brendan Jenkins

Brendan is a Solutions Architect at AWS who works with enterprise customers, providing them with technical guidance and helping them achieve their business goals. He specializes in DevOps and machine learning (ML) technology.

Chris Shea

Chris Shea

Chris is an AWS Solutions Architect serving enterprise customers in the PropTech and AdTech industry verticals, providing guidance and the tools that customers need for success. His areas of interest include AI for DevOps and AI/ML technology.

Tim Manik

Tim Manik

Tim is a Solutions Architect at AWS working with enterprise customers on migrations and modernizations. He specializes in cybersecurity and AI/ML and is passionate about bridging the gap between the two fields.

Angel Tolson

Angel Tolson

Angel is a Solutions Architect at AWS working with small to medium size businesses, providing them with technical guidance and helping them achieve their business goals. She is particularly interested in cloud operations and networking.

How to generate security findings to help your security team with incident response simulations

Post Syndicated from Jonathan Nguyen original https://aws.amazon.com/blogs/security/how-to-generate-security-findings-to-help-your-security-team-with-incident-response-simulations/

Continually reviewing your organization’s incident response capabilities can be challenging without a mechanism to create security findings with actual Amazon Web Services (AWS) resources within your AWS estate. As prescribed within the AWS Security Incident Response whitepaper, it’s important to periodically review your incident response capabilities to make sure your security team is continually maturing internal processes and assessing capabilities within AWS. Generating sample security findings is useful to understand the finding format so you can enrich the finding with additional metadata or create and prioritize detections within your security information event management (SIEM) solution. However, if you want to conduct an end-to-end incident response simulation, including the creation of real detections, sample findings might not create actionable detections that will start your incident response process because of alerting suppressions you might have configured, or imaginary metadata (such as synthetic Amazon Elastic Compute Cloud (Amazon EC2) instance IDs), which might confuse your remediation tooling.

In this post, we walk through how to deploy a solution that provisions resources to generate simulated security findings for actual provisioned resources within your AWS account. Generating simulated security findings in your AWS account gives your security team an opportunity to validate their cyber capabilities, investigation workflow and playbooks, escalation paths across teams, and exercise any response automation currently in place.

Important: It’s strongly recommended that the solution be deployed in an isolated AWS account with no additional workloads or sensitive data. No resources deployed within the solution should be used for any purpose outside of generating the security findings for incident response simulations. Although the security findings are non-destructive to existing resources, they should still be done in isolation. For any AWS solution deployed within your AWS environment, your security team should review the resources and configurations within the code.

Conducting incident response simulations

Before deploying the solution, it’s important that you know what your goal is and what type of simulation to conduct. If you’re primarily curious about the format that active Amazon GuardDuty findings will create, you should generate sample findings with GuardDuty. At the time of this writing, Amazon Inspector doesn’t currently generate sample findings.

If you want to validate your incident response playbooks, make sure you have playbooks for the security findings the solution generates. If those playbooks don’t exist, it might be a good idea to start with a high-level tabletop exercise to identify which playbooks you need to create.

Because you’re running this sample in an AWS account with no workloads, it’s recommended to run the sample solution as a purple team exercise. Purple team exercises should be periodically run to support training for new analysts, validate existing playbooks, and identify areas of improvement to reduce the mean time to respond or identify areas where processes can be optimized with automation.

Now that you have a good understanding of the different simulation types, you can create security findings in an isolated AWS account.

Prerequisites

  1. [Recommended] A separate AWS account containing no customer data or running workloads
  2. GuardDuty, along with GuardDuty Kubernetes Protection
  3. Amazon Inspector must be enabled
  4. [Optional] AWS Security Hub can be enabled to show a consolidated view of security findings generated by GuardDuty and Inspector

Solution architecture

The architecture of the solution can be found in Figure 1.

Figure 1: Sample solution architecture diagram

Figure 1: Sample solution architecture diagram

  1. A user specifies the type of security findings to generate by passing an AWS CloudFormation parameter.
  2. An Amazon Simple Notification Service (Amazon SNS) topic is created to subscribe to findings for notifications. Subscribed users are notified of the finding through the deployed SNS topic.
  3. Upon user selection of the CloudFormation parameter, EC2 instances are provisioned to run commands to generate security findings.

    Note: If the parameter inspector is provided during deployment, then only one EC2 instance is deployed. If the parameter guardduty is provided during deployment, then two EC2 instances are deployed.

  4. For Amazon Inspector findings:
    1. The Amazon EC2 user data creates a .txt file with vulnerable images, pulls down Docker images from open source vulhub, and creates an Amazon Elastic Container Registry (Amazon ECR) repository with the vulnerable images.
    2. The EC2 user data pushes and tags the images in the ECR repository which results in Amazon Inspector findings being generated.
    3. An Amazon EventBridge cron-style trigger rule, inspector_remediation_ecr, invokes an AWS Lambda function.
    4. The Lambda function, ecr_cleanup_function, cleans up the vulnerable images in the deployed Amazon ECR repository based on applied tags and sends a notification to the Amazon SNS topic.

      Note: The ecr_cleanup_function Lambda function is also invoked as a custom resource to clean up vulnerable images during deployment. If there are issues with cleanup, the EventBridge rule continually attempts to clean up vulnerable images.

  5. For GuardDuty, the following actions are taken and resources are deployed:
    1. An AWS Identity and Access Management (IAM) user named guardduty-demo-user is created with an IAM access key that is INACTIVE.
    2. An AWS Systems Manager parameter stores the IAM access key for guardduty-demo-user.
    3. An AWS Secrets Manager secret stores the inactive IAM secret access key for guardduty-demo-user.
    4. An Amazon DynamoDB table is created, and the table name is stored in a Systems Manager parameter to be referenced within the EC2 user data.
    5. An Amazon Simple Storage Service (Amazon S3) bucket is created, and the bucket name is stored in a Systems Manager parameter to be referenced within the EC2 user data.
    6. A Lambda function adds a threat list to GuardDuty that includes the IP addresses of the EC2 instances deployed as part of the sample.
    7. EC2 user data generates GuardDuty findings for the following:
      1. Amazon Elastic Kubernetes Service (Amazon EKS)
        1. Installs eksctl from GitHub.
        2. Creates an EC2 key pair.
        3. Creates an EKS cluster (dependent on availability zone capacity).
        4. Updates EKS cluster configuration to make a dashboard public.
      2. DynamoDB
        1. Adds an item to the DynamoDB table for Joshua Tree.
      3. EC2
        1. Creates an AWS CloudTrail trail named guardduty-demo-trail-<GUID> and subsequently deletes the same CloudTrail trail. The <GUID> is randomly generated by using the $RANDOM function
        2. Runs portscan on 172.31.37.171 (an RFC 1918 private IP address) and private IP of the EKS Deployment EC2 instance provisioned as part of the sample. Port scans are primarily used by bad actors to search for potential vulnerabilities. The target of the port scans are internal IP addresses and do not leave the sample VPC deployed.
        3. Curls DNS domains that are labeled for bitcoin, command and control, and other domains associated with known threats.
      4. Amazon S3
        1. Disables Block Public Access and server access logging for the S3 bucket provisioned as part of the solution.
      5. IAM
        1. Deletes the existing account password policy and creates a new password policy with a minimum length of six characters.
  6. The following Amazon EventBridge rules are created:
    1. guardduty_remediation_eks_rule – When a GuardDuty finding for EKS is created, a Lambda function attempts to delete the EKS resources. Subscribed users are notified of the finding through the deployed SNS topic.
    2. guardduty_remediation_credexfil_rule – When a GuardDuty finding for InstanceCredentialExfiltration is created, a Lambda function is used to revoke the IAM role’s temporary security credentials and AWS permissions. Subscribed users are notified of the finding through the deployed SNS topic.
    3. guardduty_respond_IAMUser_rule – When a GuardDuty finding for IAM is created, subscribed users are notified through the deployed SNS topic. There is no remediation activity triggered by this rule.
    4. Guardduty_notify_S3_rule – When a GuardDuty finding for Amazon S3 is created, subscribed users are notified through the deployed Amazon SNS topic. This rule doesn’t invoke any remediation activity.
  7. The following Lambda functions are created:
    1. guardduty_iam_remediation_function – This function revokes active sessions and sends a notification to the SNS topic.
    2. eks_cleanup_function – This function deletes the EKS resources in the EKS CloudFormation template.

      Note: Upon attempts to delete the overall sample CloudFormation stack, this runs to delete the EKS CloudFormation template.

  8. An S3 bucket stores EC2 user data scripts run from the EC2 instances

Solution deployment

You can deploy the SecurityFindingGeneratorStack solution by using either the AWS Management Console or the AWS Cloud Development Kit (AWS CDK).

Option 1: Deploy the solution with AWS CloudFormation using the console

Use the console to sign in to your chosen AWS account and then choose the Launch Stack button to open the AWS CloudFormation console pre-loaded with the template for this solution. It takes approximately 10 minutes for the CloudFormation stack to complete.

Launch Stack

Option 2: Deploy the solution by using the AWS CDK

You can find the latest code for the SecurityFindingGeneratorStack solution in the SecurityFindingGeneratorStack GitHub repository, where you can also contribute to the sample code. For instructions and more information on using the AWS Cloud Development Kit (AWS CDK), see Get Started with AWS CDK.

To deploy the solution by using the AWS CDK

  1. To build the app when navigating to the project’s root folder, use the following commands: 
    npm install -g aws-cdk-lib
npm install

  2. Run the following command in your terminal while authenticated in your separate deployment AWS account to bootstrap your environment. Be sure to replace <INSERT_AWS_ACCOUNT> with your account number and replace <INSERT_REGION> with the AWS Region that you want the solution deployed to. 
    cdk bootstrap aws://<INSERT_AWS_ACCOUNT>/<INSERT_REGION>

  3. Deploy the stack to generate findings based on a specific parameter that is passed. The following parameters are available:
    1. inspector
    2. guardduty
    cdk deploy SecurityFindingGeneratorStack –parameters securityserviceuserdata=inspector

Reviewing security findings

After the solution successfully deploys, security findings should start appearing in your AWS account’s GuardDuty console within a couple of minutes.

Amazon GuardDuty findings

In order to create a diverse set of GuardDuty findings, the solution uses Amazon EC2 user data to run scripts. Those scripts can be found in the sample repository. You can also review and change scripts as needed to fit your use case or to remove specific actions if you don’t want specific resources to be altered or security findings to be generated.

A comprehensive list of active GuardDuty finding types and details for each finding can be found in the Amazon GuardDuty user guide. In this solution, activities which cause the following GuardDuty findings to be generated, are performed:

To generate the EKS security findings, the EKS Deployment EC2 instance is running eksctl commands that deploy CloudFormation templates. If the EKS cluster doesn’t deploy, it might be because of capacity restraints in a specific Availability Zone. If this occurs, manually delete the failed EKS CloudFormation templates.

If you want to create the EKS cluster and security findings manually, you can do the following:

  1. Sign in to the Amazon EC2 console.
  2. Connect to the EKS Deployment EC2 instance using an IAM role that has access to start a session through Systems Manager. After connecting to the ssm-user, issue the following commands in the Session Manager session:
    1. sudo chmod 744 /home/ec2-user/guardduty-script.sh
    2. chown ec2-user /home/ec2-user/guardduty-script.sh
    3. sudo /home/ec2-user/guardduty-script.sh

It’s important that your security analysts have an incident response playbook. If playbooks don’t exist, you can refer to the GuardDuty remediation recommendations or AWS sample incident response playbooks to get started building playbooks.

Amazon Inspector findings

The findings for Amazon Inspector are generated by using the open source Vulhub collection. The open source collection has pre-built vulnerable Docker environments that pull images into Amazon ECR.

The Amazon Inspector findings that are created vary depending on what exists within the open source library at deployment time. The following are examples of findings you will see in the console:

For Amazon Inspector findings, you can refer to parts 1 and 2 of Automate vulnerability management and remediation in AWS using Amazon Inspector and AWS Systems Manager.

Clean up

If you deployed the security finding generator solution by using the Launch Stack button in the console or the CloudFormation template security_finding_generator_cfn, do the following to clean up:

  1. In the CloudFormation console for the account and Region where you deployed the solution, choose the SecurityFindingGeneratorStack stack.
  2. Choose the option to Delete the stack.

If you deployed the solution by using the AWS CDK, run the command cdk destroy.

Important: The solution uses eksctl to provision EKS resources, which deploys additional CloudFormation templates. There are custom resources within the solution that will attempt to delete the provisioned CloudFormation templates for EKS. If there are any issues, you should verify and manually delete the following CloudFormation templates:

  • eksctl-GuardDuty-Finding-Demo-cluster
  • eksctl-GuardDuty-Finding-Demo-addon-iamserviceaccount-kube-system-aws-node
  • eksctl-GuardDuty-Finding-Demo-nodegroup-ng-<GUID>

Conclusion

In this blog post, I showed you how to deploy a solution to provision resources in an AWS account to generate security findings. This solution provides a technical framework to conduct periodic simulations within your AWS environment. By having real, rather than simulated, security findings, you can enable your security teams to interact with actual resources and validate existing incident response processes. Having a repeatable mechanism to create security findings also provides your security team the opportunity to develop and test automated incident response capabilities in your AWS environment.

AWS has multiple services to assist with increasing your organization’s security posture. Security Hub provides native integration with AWS security services as well as partner services. From Security Hub, you can also implement automation to respond to findings using custom actions as seen in Use Security Hub custom actions to remediate S3 resources based on Amazon Macie discovery results. In part two of a two-part series, you can learn how to use Amazon Detective to investigate security findings in EKS clusters. Amazon Security Lake automatically normalizes and centralizes your data from AWS services such as Security Hub, AWS CloudTrail, VPC Flow Logs, and Amazon Route 53, as well as custom sources to provide a mechanism for comprehensive analysis and visualizations.

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 Incident Response re:Post or contact AWS Support.

Author

Jonathan Nguyen

Jonathan is a Principal Security Architect at AWS. His background is in AWS security with a focus on threat detection and incident response. He helps enterprise customers develop a comprehensive AWS security strategy and deploy security solutions at scale, and trains customers on AWS security best practices.

Introducing new central configuration capabilities in AWS Security Hub

Post Syndicated from Nicholas Jaeger original https://aws.amazon.com/blogs/security/introducing-new-central-configuration-capabilities-in-aws-security-hub/

As cloud environments—and security risks associated with them—become more complex, it becomes increasingly critical to understand your cloud security posture so that you can quickly and efficiently mitigate security gaps. AWS Security Hub offers close to 300 automated controls that continuously check whether the configuration of your cloud resources aligns with the best practices identified by Amazon Web Services (AWS) security experts and with industry standards. Furthermore, you can manage your cloud security posture at scale by using a single action to enable Security Hub across your organization with the default settings, and by aggregating findings across your organization accounts and Regions to a single account and Region of your choice.

With the release of the new central configuration feature of Security Hub, the setup and management of control and policy configurations is simplified and centralized to the same account you have already been using to aggregate findings. In this blog post, we will explain the benefits of the new feature and describe how you can quickly onboard to it.

Central configuration overview

With the release of the new central configuration capabilities in Security Hub, you are now able to use your delegated administrator (DA) account (an AWS Organizations account designated to manage Security Hub throughout your organization) to centrally manage Security Hub controls and standards and to view your Security Hub configuration throughout your organization from a single place. To facilitate this functionality, central configuration allows you to set up policies that specify whether or not Security Hub should be enabled and which standards and controls should be turned on. You can then choose to associate your policies with your entire organization or with specific accounts or organizational units (OUs), with your policies applying automatically across linked Regions. Policies applied to specific OUs (or to the entire organization) are inherited by child accounts. This not only applies to existing accounts, but also to new accounts added to those OUs (or to the entire organization) after you created the policy. Furthermore, when you add a new linked Region to Security Hub, your existing policies will be applied to that Region immediately. This allows you to stop maintaining manual lists of accounts and Regions to which you’d like to apply your custom configurations; instead, you can maintain several policies for your organization, with each one being associated to a different set of accounts in your organization. As a result, by using the central configuration capabilities, you can significantly reduce the time spent on configuring Security Hub and switch your focus to remediating its findings.

After applying your policies, Security Hub also provides you with a view of your organization that shows the policy status per OU and account while also preventing drift. This means that after you set up your organization by using central configuration, account owners will not be able to deviate from your chosen settings—your policies will serve as the source of truth for your organizational configuration, and you can use them to understand how Security Hub is configured for your organization.

The use of the new central configuration feature is now the recommended approach to configuring Security Hub, and its standards and controls, across some or all AWS accounts in your AWS Organizations structure.

Prerequisites

To get started with central configuration, you need to complete three prerequisites:

  1. Enable AWS Config in the accounts and Regions where you plan to enable Security Hub. (For more information on how to optimize AWS Config configuration for Security Hub usage, see this blog post.)
  2. Turn on Security Hub in your AWS Organizations management account at least in one Region where you plan to use Security Hub.
  3. Use your Organizations management account to delegate an administrator account for Security Hub.

If you are new to Security Hub, simply navigate to it in the AWS Management Console from your organization management account, and the console will walk you through setting the last two prerequisites listed here. If you already use Security Hub, these can be configured from the Settings page in Security Hub. In both cases, upon completing these three prerequisites, you can proceed with the central configuration setup from the account you set as the DA.

Recommended setup

To begin the setup, open the Security Hub console from your AWS Organizations management account or from your Security Hub delegated administrator account. In the left navigation menu, choose Configuration to open the new Configuration page, shown in Figure 1. Choose Start central configuration.

Figure 1: The new Configuration page, where you can see your current organizational configuration and start using the new capabilities

Figure 1: The new Configuration page, where you can see your current organizational configuration and start using the new capabilities

If you signed in to Security Hub using the AWS Organizations management account, you will be brought to step 1, Designate delegated administrator, where you will be able to designate a new delegated administrator or confirm your existing selection before continuing the setup. If you signed in to Security Hub using your existing delegated administrator account, you will be brought directly to step 2, Centralize organization, which is shown in Figure 2. In step 2, you are first asked to choose your home Region, which is the AWS Region you will use to create your configuration policies. By default, the current Region is selected as your home Region, unless you already use cross-Region finding aggregation — in which case, your existing aggregation Region is pre-selected as your home Region.

You are then prompted to select your linked Regions, which are the Regions you will configure by using central configuration. Regions that were already linked as part of your cross-Region aggregation settings will be pre-selected. You will also be able to add additional Regions or choose to include all AWS Regions, including future Regions. If your selection includes opt-in Regions, note that Security Hub will not be enabled in them until you enable those Regions directly.

Figure 2: The Centralize organization page

Figure 2: The Centralize organization page

Step 3, Configure organization, is shown in Figure 3. You will see a recommendation that you use the AWS recommended Security Hub configuration policy (SHCP) across your entire organization. This includes enabling the AWS Foundational Security Best Practices (FSBP) v1.0.0 standard and enabling new and existing FSBP controls in accounts in your AWS Organizations structure. This is the recommended configuration for most customers, because the AWS FSBP have been carefully curated by AWS security experts and represent trusted security practices for customers to build on.

Alternatively, if you already have a custom configuration in Security Hub and would like to import it into the new capabilities, choose Customize my Security Hub configuration and then choose Pre-populate configuration.

Figure 3: Step 3 – creating your first policy

Figure 3: Step 3 – creating your first policy

Step 4, Review and apply, is where you can review the policy you just created. Until you complete this step, your organization’s configuration will not be changed. This step will override previous account configurations and create and apply your new policy. After you choose Create policy and apply, you will be taken to the new Configuration page, which was previously shown in Figure 1. The user interface will now be updated to include three tabs — Organization, Policies, and Invitation account — where you can do the following:

  • On the Organization tab, which serves as a single pane of glass for your organization configuration in Security Hub, you can see the policy status for each account and OU and verify that your desired configuration is in effect.
  • On the Policies tab, you can view your policies, update them, and create new ones.
  • On the Invitation accounts tab, you can view and update findings for invitation accounts, which do not belong to your AWS Organizations structure. These accounts cannot be configured using the new central configuration capabilities.

Together, those tabs serve as a single pane of glass for your organization configuration in Security Hub. To that end, the organization chart you now see shows which of your accounts have already been affected by the policy you just created and which are still pending. Normally, an account will show as pending only for a few minutes after you create new policies or update existing ones. However, an account can stay in pending status for up to 24 hours. During this time, Security Hub will try to configure the account with your chosen policy settings.

If Security Hub determines that a policy cannot be successfully propagated to an account, it will show its status as failed (see Figure 4). This is most likely to happen when you missed completing the prerequisites in the account where the failure is showing. For example, if AWS Config is not yet enabled in an account, the policy will have a failed status. When you hover your pointer over the word “Failed”, Security Hub will show an error message with details about the issue. After you fix the error, you can try again to apply the policy by selecting the failed account and choosing the Re-apply policy button.

Figure 4: The Organization tab on the <strong>Configuration</strong> page shows all your organization accounts, if they are being managed by a policy, and the policy status for each account and OU” width=”780″ class=”size-full wp-image-32053″ style=”border: 1px solid #bebebe”></p> <p id=Figure 4: The Organization tab on the Configuration page shows all your organization accounts, if they are being managed by a policy, and the policy status for each account and OU

Flexibility in onboarding to central configuration

As mentioned earlier, central configuration makes it significantly more accessible for you to centrally manage Security Hub and its controls and standards. This feature also gives you the granularity to choose the specific accounts to which your chosen settings will be applied. Even though we recommend to use central configuration to configure all your accounts, one advantage of the feature is that you can initially create a test configuration and then apply it across your organization. This is especially useful when you have already configured Security Hub using previously available methods and you would like to check that you have successfully imported your existing configuration.

When you onboard to central configuration, accounts in the organization are self-managed by default, which means that they still maintain their previous configuration until you apply a policy to them, to one of their parent OUs, or to the entire organization. This gives you the option to create a test policy when you onboard, apply it only to a test account or OU, and check that you achieved your desired outcome before applying it to other accounts in the organization.

Configure and deploy different policies per OU

Although we recommend that you use the policy recommended by Security Hub whenever possible, every customer has a different environment and some customization might be required. Central configuration does not require you to use the recommended policy, and you can instead create your own custom policies that specify how Security Hub is used across organization accounts and Regions. You can create one configuration policy for your entire organization, or multiple policies to customize Security Hub settings in different accounts.

In addition, you might need to implement different policies per OU. For example, you might need to do that when you have a finance account or OU in which you want to use Payment Card Industry Data Security Standard (PCI DSS) v3.2.1. In this case, you can go to the Policies tab, choose Create policy, specify the configuration you’d like to have, and apply it to those specific OUs or accounts, as shown in Figure 5. Note that each policy must be complete — which means that it must contain the full configuration settings you would like to apply to the chosen set of accounts or OUs. In particular, an account cannot inherit part of its settings from a policy associated with a parent OU, and the other part from its own policy. The benefit of this requirement is that each policy serves as the source of truth for the configuration of the accounts it is applied to. For more information on this behavior or on how to create new policies, see the Security Hub documentation.

Figure 5: Creation of a new policy with the FSBP and the PCI DSS standards

Figure 5: Creation of a new policy with the FSBP and the PCI DSS standards

You might find it necessary to exempt accounts from being centrally configured. You have the option to set an account or OU to self-managed status. Then only the account owner can configure the settings for that account. This is useful if your organization has teams that need to be able to set their own security coverage. Unless you disassociate self-managed accounts from your Security Hub organization, you will still see findings from self-managed accounts, giving you organization-wide visibility into your security posture. However, you won’t be able to view the configuration of those accounts, because they are not centrally managed.

Understand and manage where controls are applied

In addition to being able to centrally create and view your policies, you can use the control details page to define, review, and apply how policies are configured at a control level. To access the control details page, go to the left navigation menu in Security Hub, choose Controls, and then choose any individual control.

The control details page allows you to review the findings of a control in accounts where it is already enabled. Then, if you decide that these findings are not relevant to specific accounts and OUs, or if you decide that you want to use the control in additional accounts where it is not currently enabled, you can choose Configure, view the policies to which the control currently applies, and update the configuration accordingly as shown in Figure 6.

Figure 6: Configuring a control from the control details page

Figure 6: Configuring a control from the control details page

Organizational visibility

As you might already have noticed in the earlier screenshot of the Organization view (Figure 4), the new central configuration capability gives you a new view of the policies applied (and by extension, the controls and standards deployed) to each account and OU. If you need to customize this configuration, you can modify an existing policy or create a new policy to quickly apply to all or a subset of your accounts. At a glance, you can also see which accounts are self-managed or don’t have Security Hub turned on.

Conclusion

Security Hub central configuration helps you to seamlessly configure Security Hub and its controls and standards across your accounts and Regions so that your organization’s accounts have the level of security controls coverage that you want. AWS recommends that you use this feature when configuring, deploying, and managing controls in Security Hub across your organization’s accounts and Regions. Central configuration is now available in all commercial AWS Regions. Try it out today by visiting the new Configuration page in Security Hub from your DA. You can benefit from the Security Hub 30-day free trial even if you use central configuration, and the trial offer will be automatically applied to organization accounts in which you didn’t use Security Hub before.

 
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.

Nicholas Jaeger

Nicholas Jaeger

Nicholas is a Principal Security Solutions Architect at AWS. His background includes software engineering, teaching, solutions architecture, and AWS security. Today, he focuses on helping companies and organizations operate as securely as possible on AWS. Nicholas also hosts AWS Security Activation Days to provide customers with prescriptive guidance while using AWS security services to increase visibility and reduce risk.

Gal Ordo

Gal Ordo

Gal is a Senior Product Manager for AWS Security Hub at AWS. He has more than a decade of experience in cybersecurity, having focused on IoT, network, and cloud security throughout his career. He is passionate about making sure that customers can continue to scale and grow their environments without compromising on security. Outside of work, Gal enjoys video games, reading, and exploring new places.

Download AWS Security Hub CSV report

Post Syndicated from Pablo Pagani original https://aws.amazon.com/blogs/security/download-aws-security-hub-csv-report/

AWS Security Hub provides a comprehensive view of your security posture in Amazon Web Services (AWS) and helps you check your environment against security standards and best practices. In this post, I show you a solution to export Security Hub findings to a .csv file weekly and send an email notification to download the file from Amazon Simple Storage Service (Amazon S3). By using this solution, you can share the report with others without providing access to your AWS account. You can also use it to generate assessment reports and prioritize and build a remediation roadmap.

When you enable Security Hub, it collects and consolidates findings from AWS security services that you’re using, such as threat detection findings from Amazon GuardDuty, vulnerability scans from Amazon Inspector, S3 bucket policy findings from Amazon Macie, publicly accessible and cross-account resources from AWS Identity and Access Management Access Analyzer, and resources missing AWS WAF coverage from AWS Firewall Manager. Security Hub also consolidates findings from integrated AWS Partner Network (APN) security solutions.

Cloud security processes can differ from traditional on-premises security in that security is often decentralized in the cloud. With traditional on-premises security operations, security alerts are typically routed to centralized security teams operating out of security operations centers (SOCs). With cloud security operations, it’s often the application builders or DevOps engineers who are best situated to triage, investigate, and remediate security alerts.

This solution uses the Security Hub API, AWS Lambda, Amazon S3, and Amazon Simple Notification Service (Amazon SNS). Findings are aggregated into a .csv file to help identify common security issues that might require remediation action.

Solution overview

This solution assumes that Security Hub is enabled in your AWS account. If it isn’t enabled, set up the service so that you can start seeing a comprehensive view of security findings across your AWS accounts.

How the solution works

  1. An Amazon EventBridge time-based event invokes a Lambda function for processing.
  2. The Lambda function gets finding results from the Security Hub API and writes them into a .csv file.
  3. The API uploads the file into Amazon S3 and generates a presigned URL with a 24-hour duration, or the duration of the temporary credential used in Lambda, whichever ends first.
  4. Amazon SNS sends an email notification to the address provided during deployment. This email address can be updated afterwards through the Amazon SNS console.
  5. The email includes a link to download the file.
Figure 1: Solution overview, deployed through AWS CloudFormation

Figure 1: Solution overview, deployed through AWS CloudFormation

Fields included in the report:

Note: You can extend the report by modifying the Lambda function to add fields as needed.

Solution resources

The solution provided with this blog post consists of an AWS CloudFormation template named security-hub-full-report-email.json that deploys the following resources:

  1. An Amazon SNS topic named SecurityHubRecurringFullReport and an email subscription to the topic.
    Figure 2: SNS topic created by the solution

    Figure 2: SNS topic created by the solution

  2. The email address that subscribes to the topic is captured through a CloudFormation template input parameter. The subscriber is notified by email to confirm the subscription. After confirmation, the subscription to the SNS topic is created. Additional subscriptions can be added as needed to include additional emails or distribution lists.
    Figure 3: SNS email subscription

    Figure 3: SNS email subscription

  3. The SendSecurityHubFullReportEmail Lambda function queries the Security Hub API to get findings into a .csv file that’s written to Amazon S3. A pre-authenticated link to the file is generated and sends the email message to the SNS topic described above.
    Figure 4: Lambda function created by the solution

    Figure 4: Lambda function created by the solution

  4. An IAM role for the Lambda function to be able to create logs in CloudWatch, get findings from Security Hub, publish messages to SNS, and put objects into an S3 bucket.
    Figure 5: Permissions policy for the Lambda function

    Figure 5: Permissions policy for the Lambda function

  5. An EventBridge rule that runs on a schedule named SecurityHubFullReportEmailSchedule used to invoke the Lambda function that generates the findings report. The default schedule is every Monday at 8:00 AM UTC. This schedule can be overwritten by using a CloudFormation input parameter. Learn more about creating cron expressions.
    Figure 6: Example of the EventBridge schedule created by the solution

    Figure 6: Example of the EventBridge schedule created by the solution

Deploy the solution

Use the following steps to deploy this solution in a single AWS account. If you have a Security Hub administrator account or are using Security Hub cross-Region aggregation, the report will get the findings from the linked AWS accounts and Regions.

To deploy the solution

  1. Download the CloudFormation template security-hub-full-report-email.json from our GitHub repository.
  2. Copy the template to an S3 bucket within your target AWS account and Region. Copy the object URL for the CloudFormation template .json file.
  3. On the AWS Management Console, go to the CloudFormation console. Choose Create Stack and select With new resources.
    Figure 7: Create stack with new resources

    Figure 7: Create stack with new resources

  4. Under Specify template, in the Amazon S3 URL textbox, enter the S3 object URL for the .json file that you uploaded in step 1.
    Figure 8: Specify S3 URL for CloudFormation template

    Figure 8: Specify S3 URL for CloudFormation template

  5. Choose Next. On the next page, do the following:
    1. Stack name: Enter a name for the stack.
    2. Email address: Enter the email address of the subscriber to the Security Hub findings email.
    3. RecurringScheduleCron: Enter the cron expression for scheduling the Security Hub findings email. The default is every Monday at 8:00 AM UTC. Learn more about creating cron expressions.
    4. SecurityHubRegion: Enter the Region where Security Hub is aggregating the findings.
    Figure 9: Enter stack name and parameters

    Figure 9: Enter stack name and parameters

  6. Choose Next.
  7. Keep all defaults in the screens that follow and choose Next.
  8. Check the box I acknowledge that AWS CloudFormation might create IAM resources, and then choose Create stack.

Test the solution

You can send a test email after the deployment is complete. To do this, open the Lambda console and locate the SendSecurityHubFullReportEmail Lambda function. Perform a manual invocation with an event payload to receive an email within a few minutes. You can repeat this procedure as many times as you want.

Conclusion

In this post I’ve shown you an approach for rapidly building a solution for sending weekly findings report of the security posture of your AWS account as evaluated by Security Hub. This solution helps you to be diligent in reviewing outstanding findings and to remediate findings in a timely way based on their severity. You can extend the solution in many ways, including:

  • Send a file to an email-enabled ticketing service, such as ServiceNow or another security information and event management (SIEM) that you use.
  • Add links to internal wikis for workflows such as organizational exceptions to vulnerabilities or other internal processes.
  • Extend the solution by modifying the filters, email content, and delivery frequency.

To learn more about how to set up and customize Security Hub, see these additional blog posts.

If you have feedback about this post, submit comments in the Comments section below. If you have any questions about this post, start a thread on the AWS Security Hub re:Post forum.

Want more AWS Security news? Follow us on Twitter.

Pablo Pagani

Pablo Pagani

Pablo is the Sr. Latam Security Manager for AWS Professional Services based in Buenos Aires, Argentina. He helps customers build a secure journey in AWS. He developed his passion for computers while writing his first lines of code in BASIC using a Talent MSX.

How to share security telemetry per OU using Amazon Security Lake and AWS Lake Formation

Post Syndicated from Chris Lamont-Smith original https://aws.amazon.com/blogs/security/how-to-share-security-telemetry-per-ou-using-amazon-security-lake-and-aws-lake-formation/

This is the final part of a three-part series on visualizing security data using Amazon Security Lake and Amazon QuickSight. In part 1, Aggregating, searching, and visualizing log data from distributed sources with Amazon Athena and Amazon QuickSight, you learned how you can visualize metrics and logs centrally with QuickSight and AWS Lake Formation irrespective of the service or tool generating them. In part 2, How to visualize Amazon Security Lake findings with Amazon QuickSight (LINK NOT LIVE YET), you learned how to integrate Amazon Athena with Security Lake and create visualizations with QuickSight of the data and events captured by Security Lake.

For companies where security administration and ownership are distributed across a single organization in AWS Organizations, it’s important to have a mechanism for securely sharing and visualizing security data. This can be achieved by enriching data within Security Lake with organizational unit (OU) structure and account tags and using AWS Lake Formation to securely share data across your organization on a per-OU basis. Users can then analyze and visualize security data of only those AWS accounts in the OU that they have been granted access to. Enriching the data enables users to effectively filter information using business-specific criteria, minimizing distractions and enabling them to concentrate on key priorities.

Distributed security ownership

It’s not unusual to find security ownership distributed across an organization in AWS Organizations. Take for example a parent company with legal entities operating under it, which are responsible for the security posture of the AWS accounts within their lines of business. Not only is each entity accountable for managing and reporting on security within its area, it must not be able to view the security data of other entities within the same organization.

In this post, we discuss a common example of distributing dashboards on a per-OU basis for visualizing security posture measured by the AWS Foundational Security Best Practices (FSBP) standard as part of AWS Security Hub. In this post, you learn how to use a simple tool published on AWS Samples to extract OU and account tags from your organization and automatically create row-level security policies to share Security Lake data to AWS accounts you specify. At the end, you will have an aggregated dataset of Security Hub findings enriched with AWS account metadata that you can use as a basis for building QuickSight dashboards.

Although this post focuses on sharing Security Hub data through Security Lake, the same steps can be performed to share any data—including Security Hub findings in Amazon S3—according to OU. You need to ensure any tables you want to share contain an AWS account ID column and that the tables are managed by Lake Formation.

Prerequisites

This solution assumes you have:

  • Followed the previous posts in this series and understand how Security Lake, Lake Formation, and QuickSight work together.
  • Enabled Security Lake across your organization and have set up a delegated administrator account.
  • Configured Security Hub across your organization and have enabled the AWS FSBP standard.

Example organization

AnyCorp Inc, a fictional organization, wants to provide security compliance dashboards to its two subsidiaries, ExampleCorpEast and ExampleCorpWest, so that each only has access to data for their respective companies.

Each subsidiary has an OU under AnyCorp’s organization as well as multiple nested OUs for each line of business they operate. ExampleCorpEast and ExampleCorpWest have their own security teams and each operates a security tooling AWS account and uses QuickSight for visibility of security compliance data. AnyCorp has implemented Security Lake to centralize the collection and availability of security data across their organization and has enabled Security Hub and the AWS FSBP standard across every AWS account.

Figure 1 – Overview of AnyCorp Inc OU structure and AWS accounts

Figure 1: Overview of AnyCorp Inc OU structure and AWS accounts


Note: Although this post describes a fictional OU structure to demonstrate the grouping and distribution of security data, you can substitute your specific OU and AWS account details and achieve the same results.

Logical architecture

Figure 2 – Logical overview of solution components

Figure 2: Logical overview of solution components

The solution includes the following core components:

  • An AWS Lambda function is deployed into the Security Lake delegated administrator account (Account A) and extracts AWS account metadata for grouping Security Lake data and manages secure sharing through Lake Formation.
  • Lake Formation implements row-level security using data filters to restrict access to Security Lake data to only records from AWS accounts in a particular OU. Lake Formation also manages the grants that allow consumer AWS accounts access to the filtered data.
  • An Amazon Simple Storage Service (Amazon S3) bucket is used to store metadata tables that the solution uses. Apache Iceberg tables are used to allow record-level updates in S3.
  • QuickSight is configured within each data consumer AWS account (Account B) and is used to visualize the data for the AWS accounts within an OU.

Deploy the solution

You can deploy the solution through either the AWS Management Console or the AWS Cloud Development Kit (AWS CDK).

To deploy the solution using the AWS Management Console, follow these steps:

  1. Download the CloudFormation template.
  2. In your Amazon Security Lake delegated administrator account (Account A), navigate to create a new AWS CloudFormation stack.
  3. Under Specify a template, choose Upload a template file and upload the file downloaded in the previous step. Then choose Next.
  4. Enter RowLevelSecurityLakeStack as the stack name.

    The table names used by Security Lake include AWS Region identifiers that you might need to change depending on the Region you’re using Security Lake in. Edit the following parameters if required and then choose Next.

    • MetadataDatabase: the name you want to give the metadata database.
      • Default: aws_account_metadata_db
    • SecurityLakeDB: the Security Lake database as registered by Security Lake.
      • Default: amazon_security_lake_glue_db_ap_southeast_2
    • SecurityLakeTable: the Security Lake table you want to share.
      • Default: amazon_security_lake_table_ap_southeast_2_sh_findings_1_0
  5. On the Configure stack options screen, leave all other values as default and choose Next.
  6. On the next screen, navigate to the bottom of the page and select the checkbox next to I acknowledge that AWS CloudFormation might create IAM resources. Choose Submit.

The solution takes about 5 minutes to deploy.

To deploy the solution using the AWS CDK, follow these steps:

  1. Download the code from the row-level-security-lake GitHub repository, where you can also contribute to the sample code. The CDK initializes your environment and uploads the Lambda assets to Amazon S3. Then, deploy the solution to your account.
  2. For a CDK deployment, you can edit the same Region identifier parameters discussed in the CloudFormation deployment option by editing the cdk.context.json file and changing the metadata_database, security_lake_db, and security_lake_table values if required.
  3. While you’re authenticated in the Security Lake delegated administrator account, you can bootstrap the account and deploy the solution by running the following commands:

    4. cdk bootstrap
    cdk deploy

Configuring the solution in the Security Lake delegated administrator account

After the solution has been successfully deployed, you can review the OUs discovered within your organization and specify which consumer AWS accounts (Account B) you want to share OU data with.

To specify AWS accounts to share OU security data with, follow these steps:

  1. While in the Security Lake delegated administrator account (Account A), go to the Lake Formation console.
  2. To view and update the metadata discovered by the Lambda function, you first must grant yourself access to the tables where it’s stored. Select the radio button for aws_account_metadata_db. Then, under the Action dropdown menu, select Grant.
    3. Figure 3: Creating a grant for your IAM role

    Figure 3: Creating a grant for your IAM role

  3. On the Grant data permissions page, under Principals, select the IAM users and roles dropdown and select the IAM role that you are currently logged in as.
  4. Under LF-Tags or catalog resources, select the Tables dropdown and select All tables.
    5. Figure 4: Choosing All Tables for the grant

    Figure 4: Choosing All Tables for the grant

  5. Under Table permissions, select Select, Insert, and Alter. These permissions let you view and update the data in the tables.
  6. Leave all other options as default and choose Grant.
  7. Now go to the AWS Athena console.

    8. Note: To use Athena for queries you must configure an S3 bucket to store query results. If this is the first time Athena is being used in your account, you will receive a message saying that you need to configure an S3 bucket. To do this, select the Edit settings button in the blue information notice and follow the instructions.

  8. On the left side, select aws_account_metadata_db> as the Database. You will see aws_account_metadata and ou_groups >as tables within the database.
    9. Figure 5: List of tables under the aws_accounts_metadata_db database

    Figure 5: List of tables under the aws_accounts_metadata_db database

  9. To view the OUs available within your organization, paste the following query into the Athena query editor window and choose Run.
    10. SELECT * FROM "aws_account_metadata_db"."ou_groups"

  10. Next, you must specify an AWS account you want to share an OU’s data with. Run the following SQL query in Athena and replace <AWS account Id> and <OU to assign> with values from your organization:
    11. UPDATE "aws_account_metadata_db"."ou_groups"
SET consumer_aws_account_id = '<AWS account Id>'
WHERE ou = '<OU to assign>'

    In the example organization, all ExampleCorpWest security data is shared with AWS account 123456789012 (Account B) using the following SQL query:

    UPDATE "aws_account_metadata_db"."ou_groups"
SET consumer_aws_account_id = '123456789012'
WHERE ou = 'OU=root,OU=ExampleCorpWest'

    Note: You must specify the full OU path beginning with OU=root.

  11. Repeat this process for each OU you want to assign different AWS accounts to.

    12. Note: You can only assign one AWS account ID to each OU group

  12. You can confirm that changes have been applied by running the Athena query from Step 3 again.
    13. SELECT * FROM "aws_account_metadata_db"."ou_groups"

You should see the AWS account ID you specified next to your OU.

Figure 6 – Consumer AWS account listed against ExampleCorpWest OU

Figure 6: Consumer AWS account listed against ExampleCorpWest OU

Invoke the Lambda function manually

By default, the Lambda function is scheduled to run hourly to monitor for changes to AWS account metadata and to update Lake Formation sharing permissions (grants) if needed. To perform the remaining steps in this post without having to wait for the hourly run, you must manually invoke the Lambda function.

To invoke the Lambda function manually, follow these steps:

  1. Open the AWS Lambda console.
  2. Select the RowLevelSecurityLakeStack-* Lambda function.
  3. Under Code source, choose Test.
  4. The Lambda function doesn’t take any parameters. Enter rl-sec-lake-test as the Event name and leave all other options as the default. Choose Save.
  5. Choose Test again. The Lambda function will take approximately 5 minutes to complete in an environment with less than 100 AWS accounts.

After the Lambda function has finished, you can review the data cell filters and grants that have been created in Lake Formation to securely share Security Lake data with your consumer AWS account (Account B).

To review the data filters and grants, follow these steps:

  1. Open the Lake Formation console.
  2. In the navigation pane, select Data filters under Data catalog to see a list of data cells filters that have been created for each OU that you assigned a consumer AWS account to. One filter is created per table. Each consumer AWS account is granted restricted access to the aws_account_metadata table and the aggregated Security Lake table.
    3. Figure 7 – Viewing data filters in Lake Formation

    Figure 7: Viewing data filters in Lake Formation

  3. Select one of the filters in the list and choose Edit. Edit data filter displays information about the filter such as the database and table it’s applied to, as well as the Row filter expression that enforces row-level security to only return rows where the AWS account ID is in the OU it applies to. Choose Cancel to close the window.
    4. Figure 8 – Details of a data filter showing row filter expression

    Figure 8: Details of a data filter showing row filter expression

  4. To see how the filters are used to grant restricted access to your tables, select Data lake permission under Permissions from navigation pane. In the search bar under Data permissions, enter the AWS account ID for your consumer AWS account (Account B) and press Enter. You will see a list of all the grants applied to that AWS account. Scroll to the right to see a column titled Resource that lists the names of the data cell filters you saw in the previous step.
    5. Figure 9 – Grants to the data consumer account for data filters

    Figure 9: Grants to the data consumer account for data filters

You can now move on to setting up the consumer AWS account.

Configuring QuickSight in the consumer AWS account (Account B)

Now that you’ve configured everything in the Security Lake delegated administrator account (Account A), you can configure QuickSight in the consumer account (Account B).

To confirm you can access shared tables, follow these steps:

  1. Sign in to your consumer AWS account (also known  as Account B).
  2. Follow the same steps as outlined in this previous post (NEEDS 2ND POST IN SERIES LINK WHEN LIVE) to accept the AWS Resource Access Manager invitation, create a new database, and create resource links for the aws_account_metadata and amazon_security_lake_table_<region>_sh_findings_1_0 tables that have been shared with your consumer AWS account. Make sure you create resource links for both tables shared with the account. When done, return to this post and continue with step 3.
  3. [Optional] After the resource links have been created, test that you’re able to query the data by selecting the radio button next to the aws_account_metadata resource link, select Actions, and then select View data under Table. This takes you to the Athena query editor where you can now run queries on the shared tables.
    4. Figure 10 – Selecting View data in Lake Formation to open Athena

    Figure 10: Selecting View data in Lake Formation to open Athena

    Note: To use Athena for queries you must configure an S3 bucket to store query results. If this is the first time using Athena in your account, you will receive a message saying that you need to configure an S3 bucket. To do this, choose Edit settings in the blue information notice and follow the instructions.

  4. In the Editor configuration, select AwsDataCatalog from the Data source options. The Database should be the database you created in the previous steps, for example security_lake_visualization. After selecting the database, copy the SQL query that follows and paste it into your Athena query editor, and choose Run. You will only see rows of account information from the OU you previously shared.
    5. SELECT * FROM "security_lake_visualization"."aws_account_metadata"

  5. Next, to enrich your Security Lake data with the AWS account metadata you need to create an Athena View that will join the datasets and filter the results to only return findings from the AWS Foundational Security Best Practices Standard. You can do this by copying the below query and running it in the Athena query editor.
    6. CREATE OR REPLACE VIEW "security_hub_fsbps_joined_view" AS 
WITH
  security_hub AS (
   SELECT *
   FROM
     "security_lake_visualization"."amazon_security_lake_table_ap_southeast_2_sh_findings_1_0"
   WHERE (metadata.product.feature.uid LIKE 'aws-foundational-security-best-practices%')
) 
SELECT
  amm.*
, security_hub.*
FROM
  (security_hub
INNER JOIN "security_lake_visualization"."aws_account_metadata" amm ON (security_hub.cloud.account_uid = amm.id))

The SQL above performs a subquery to find only those findings in the Security Lake table that are from the AWS FSBP standard and then joins those rows with the aws_account_metadata table based on the AWS account ID. You can see it has created a new view listed under Views containing enriched security data that you can import as a dataset in QuickSight.

Figure 11 – Additional view added to the security_lake_visualization database

Figure 11: Additional view added to the security_lake_visualization database

Configuring QuickSight

To perform the initial steps to set up QuickSight in the consumer AWS account, you can follow the steps listed in the second post in this series. You must also provide the following grants to your QuickSight user:

Type Resource Permissions
GRANT security_hub_fsbps_joined_view SELECT
GRANT aws_metadata_db (resource link) DESCRIBE
GRANT amazon_security_lake_table_<region>_sh_findings_1_0 (resource link) DESCRIBE
GRANT ON TARGET aws_metadata_db (resource link) SELECT
GRANT ON TARGET amazon_security_lake_table_<region>_sh_findings_1_0 (resource link) SELECT

To create a new dataset in QuickSight, follow these steps:

  1. After your QuickSight user has the necessary permissions, open the QuickSight console and verify that you’re in same Region where Lake Formation is sharing the data.
  2. Add your data by choosing Datasets from the navigation pane and then selecting New dataset. To create a new dataset from new data sources, select Athena.
  3. Enter a data source name, for example security_lake_visualization, leave the Athena workgroup as [ primary ]. Then choose Create data source.
  4. The next step is to select the tables to build your dashboards. On the Choose your table prompt, for Catalog, select AwsDataCatalog. For Database, select the database you created in the previous steps, for example security_lake_visualization. For Table, select the security_hub_fsbps_joined_view you created previously and choose Edit/Preview data.
    5. Figure 12: Choosing the joined dataset in QuickSight

    Figure 12 – Choosing the joined dataset in QuickSight

  5. You will be taken to a screen where you can preview the data in your dataset.
    6. Figure 13: Previewing data in QuickSight

    Figure 13: Previewing data in QuickSight

  6. After you confirm you’re able to preview the data from the view, select the SPICE radio button in the bottom left of the screen and then choose PUBLISH & VISUALIZE.
  7. You can now create analyses and dashboards from Security Hub AWS FSBP standard findings per OU and filter data based on business dimensions available to you through OU structure and account tags.
    8. Figure 14 – QuickSight dashboard showing only ExampleCorpWest OU data and incorporating business dimensions

    Figure 14: QuickSight dashboard showing only ExampleCorpWest OU data and incorporating business dimensions

Clean up the resources

To clean up the resources that you created for this example:

  1. Sign in to the Security Lake delegated admin account and delete the CloudFormation stack by either:
    • Using the CloudFormation console to delete the stack, or
    • Using the AWS CDK to run cdk destroy in your terminal. Follow the instructions and enter y when prompted to delete the stack.
  2. Remove any data filters you created by navigating to data filters within Lake Formation, selecting each one and choosing Delete.

Conclusion

In this final post of the series on visualizing Security Lake data with QuickSight, we introduced you to using a tool—available from AWS Samples—to extract OU structure and account metadata from your organization and use it to securely share Security Lake data on a per-OU basis across your organization. You learned how to enrich Security Lake data with account metadata and use it to create row-level security controls in Lake Formation. You were then able to address a common example of distributing security posture measured by the AWS Foundational Security Best Practices standard as part of AWS Security Hub.

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

Chris Lamont-Smith

Chris Lamont-Smith

Chris is a Senior Security Consultant working in the Security, Risk and Compliance team for AWS ProServe based out of Perth, Australia. He enjoys working in the area where security and data analytics intersect, and is passionate about helping customers gain actionable insights from their security data. When Chris isn’t working, he is out camping or off-roading with his family in the Australian bush.

Enable Security Hub partner integrations across your organization

Post Syndicated from Joaquin Manuel Rinaudo original https://aws.amazon.com/blogs/security/enable-security-hub-partner-integrations-across-your-organization/

AWS Security Hub offers over 75 third-party partner product integrations, such as Palo Alto Networks Prisma, Prowler, Qualys, Wiz, and more, that you can use to send, receive, or update findings in Security Hub.

We recommend that you enable your corresponding Security Hub third-party partner product integrations when you use these partner solutions. By centralizing findings across your AWS and partner solutions in Security Hub, you can get a holistic cross-account and cross-Region view of your security risks. In this way, you can move beyond security reporting and start implementing automations on top of Security Hub that help improve your overall security posture and reduce manual efforts. For example, you can configure your third-party partner offerings to send findings to Security Hub and build standardized enrichment, escalation, and remediation solutions by using Security Hub automation rules, or other AWS services such as AWS Lambda or AWS Step Functions.

To enable partner integrations, you must configure the integration in each AWS Region and AWS account across your organization in AWS Organizations. In this blog post, we’ll show you how to set up a Security Hub partner integration across your entire organization by using AWS CloudFormation StackSets.

Overview

Figure 1 shows the architecture of the solution. The main steps are as follows:

  1. The deployment script creates a CloudFormation template that deploys a stack set across your AWS accounts.
  2. The stack in the member account deploys a CloudFormation custom resource using a Lambda function.
  3. The Lambda function iterates through target Regions and invokes the Security Hub boto3 method enable_import_findings_for_product to enable the corresponding partner integration.

When you add new accounts to the organizational units (OUs), StackSets deploys the CloudFormation stack and the partner integration is enabled.

Figure 1: Diagram of the solution

Figure 1: Diagram of the solution

Prerequisites

To follow along with this walkthrough, make sure that you have the following prerequisites in place:

  • Security Hub enabled across an organization in the Regions where you want to deploy the partner integration.
  • Trusted access with AWS Organizations enabled so that you can deploy CloudFormation StackSets across your organization. For instructions on how to do this, see Activate trusted access with AWS Organizations.
  • Permissions to deploy CloudFormation StackSets in a delegated administrator account for your organization.
  • AWS Command Line Interface (AWS CLI) installed.

Walkthrough

Next, we show you how to get started with enabling your partner integration across your organization using the following solution.

Step 1: Clone the repository

In the AWS CLI, run the following command to clone the aws-securityhub-deploy-partner-integration GitHub repository:

git clone https://github.com/aws-samples/aws-securityhub-partner-integration

Step 2: Set up the integration parameters

  1. Open the parameters.json file and configure the following values:
    • ProductName — Name of the product that you want to enable.
    • ProductArn — The unique Amazon Resource Name (ARN) of the Security Hub partner product. For example, the product ARN for Palo Alto PRISMA Cloud Enterprise, is arn:aws:securityhub:<REGION>:188619942792:product/paloaltonetworks/redlock; and for Prowler, it’s arn:aws:securityhub:<REGION>::product/prowler/prowler. To find a product ARN, see Available third-party partner product integrations.
    • DeploymentTargets — List of the IDs of the OUs of the AWS accounts that you want to configure. For example, use the unique identifier (ID) for the root to deploy across your entire organization.
    • DeploymentRegions — List of the Regions in which you’ve enabled Security Hub, and for which the partner integration should be enabled.
  2. Save the changes and close the file.

Step 3: Deploy the solution

  1. Open a command line terminal of your preference.
  2. Set up your AWS_REGION (for example, export AWS_REGION=eu-west-1) and make sure that your credentials are configured for the delegated administrator account.
  3. Enter the following command to deploy: 
    ./setup.sh deploy

Step 4: Verify Security Hub partner integration

To test that the product integration is enabled, run the following command in one of the accounts in the organization. Replace <TARGET-REGION> with one of the Regions where you enabled Security Hub.

aws securityhub list-enabled-products-for-import --region <TARGET-REGION>

Step 5: (Optional) Manage new partners, Regions, and OUs

To add or remove the partner integration in certain Regions or OUs, update the parameters.json file with your desired Regions and OU IDs and repeat Step 3 to redeploy changes to your Security Hub partner integration. You can also directly update the CloudFormation parameters for the securityhub-integration-<PARTNER-NAME> from the CloudFormation console.

To enable new partner integrations, create a new parameters.json file version with the partner’s product name and product ARN to deploy a new stack using the deployment script from Step 3. In the next step, we show you how to disable the partner integrations.

Step 6: Clean up

If needed, you can remove the partner integrations by destroying the stack deployed. To destroy the stack, use the command line terminal configured with the credentials for the AWS StackSets delegated administrator account and run the following command:

 ./setup.sh destroy

You can also directly delete the stack mentioned in Step 5 from the CloudFormation console by accessing the stack page from the CloudFormation console, selecting the stack securityhub-integration-<PARTNER-NAME>, and then choosing Delete.

Conclusion

In this post, you learned how you to enable Security Hub partner integrations across your organization. Now you can configure the partner product of your choice to send, update, or receive Security Hub findings.

You can extend your security automation by using Security Hub automation rules, Amazon EventBridge events, and Lambda functions to start or enrich automated remediation of new ingested findings from partners. For an example of how to do this, see Automated Security Response on AWS.

Developer teams can opt in to configure their own chatbot in AWS Chatbot to receive notifications in Amazon Chime, Slack, or Microsoft Teams channels. Lastly, security teams can use existing bidirectional integrations with Jira Service Management or Jira Core to escalate severe findings to their developer teams.

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.

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Author

Joaquin Manuel Rinaudo

Joaquin is a Principal Security Architect with AWS Professional Services. He is passionate about building solutions that help developers improve their software quality. Prior to AWS, he worked across multiple domains in the security industry, from mobile security to cloud and compliance related topics. In his free time, Joaquin enjoys spending time with family and reading science-fiction novels.

Shachar Hirshberg

Shachar Hirshberg

Shachar is a Senior Product Manager for AWS Security Hub with over a decade of experience in building, designing, launching, and scaling enterprise software. He is passionate about further improving how customers harness AWS services to enable innovation and enhance the security of their cloud environments. Outside of work, Shachar is an avid traveler and a skiing enthusiast.

Improve your security investigations with Detective finding groups visualizations

Post Syndicated from Rich Vorwaller original https://aws.amazon.com/blogs/security/improve-your-security-investigations-with-detective-finding-groups-visualizations/

At AWS, we often hear from customers that they want expanded security coverage for the multiple services that they use on AWS. However, alert fatigue is a common challenge that customers face as we introduce new security protections. The challenge becomes how to operationalize, identify, and prioritize alerts that represent real risk.

In this post, we highlight recent enhancements to Amazon Detective finding groups visualizations. We show you how Detective automatically consolidates multiple security findings into a single security event—called finding groups—and how finding group visualizations help reduce noise and prioritize findings that present true risk. We incorporate additional services like Amazon GuardDuty, Amazon Inspector, and AWS Security Hub to highlight how effective findings groups is at consolidating findings for different AWS security services.

Overview of solution

This post uses several different services. The purpose is twofold: to show how you can enable these services for broader protection, and to show how Detective can help you investigate findings from multiple services without spending a lot of time sifting through logs or querying multiple data sources to find the root cause of a security event. These are the services and their use cases:

  • GuardDuty – a threat detection service that continuously monitors your AWS accounts and workloads for malicious activity. If potential malicious activity, such as anomalous behavior, credential exfiltration, or command and control (C2) infrastructure communication is detected, GuardDuty generates detailed security findings that you can use for visibility and remediation. Recently, GuardDuty released the following threat detections for specific services that we’ll show you how to enable for this walkthrough: GuardDuty RDS Protection, EKS Runtime Monitoring, and Lambda Protection.
  • Amazon Inspector – an automated vulnerability management service that continually scans your AWS workloads for software vulnerabilities and unintended network exposure. Like GuardDuty, Amazon Inspector sends a finding for alerting and remediation when it detects a software vulnerability or a compute instance that’s publicly available.
  • Security Hub – a cloud security posture management service that performs automated, continuous security best practice checks against your AWS resources to help you identify misconfigurations, and aggregates your security findings from integrated AWS security services.
  • Detective – a security service that helps you investigate potential security issues. It does this by collecting log data from AWS CloudTrail, Amazon Virtual Private Cloud (Amazon VPC) flow logs, and other services. Detective then uses machine learning, statistical analysis, and graph theory to build a linked set of data called a security behavior graph that you can use to conduct faster and more efficient security investigations.

The following diagram shows how each service delivers findings along with log sources to Detective.

Figure 1: Amazon Detective log source diagram

Figure 1: Amazon Detective log source diagram

Enable the required services

If you’ve already enabled the services needed for this post—GuardDuty, Amazon Inspector, Security Hub, and Detective—skip to the next section. For instructions on how to enable these services, see the following resources:

Each of these services offers a free 30-day trial and provides estimates on charges after your trial expires. You can also use the AWS Pricing Calculator to get an estimate.

To enable the services across multiple accounts, consider using a delegated administrator account in AWS Organizations. With a delegated administrator account, you can automatically enable services for multiple accounts and manage settings for each account in your organization. You can view other accounts in the organization and add them as member accounts, making central management simpler. For instructions on how to enable the services with AWS Organizations, see the following resources:

Enable GuardDuty protections

The next step is to enable the latest detections in GuardDuty and learn how Detective can identify multiple threats that are related to a single security event.

If you’ve already enabled the different GuardDuty protection plans, skip to the next section. If you recently enabled GuardDuty, the protections plans are enabled by default, except for EKS Runtime Monitoring, which is a two-step process.

For the next steps, we use the delegated administrator account in GuardDuty to make sure that the protection plans are enabled for each AWS account. When you use GuardDuty (or Security Hub, Detective, and Inspector) with AWS Organizations, you can designate an account to be the delegated administrator. This is helpful so that you can configure these security services for multiple accounts at the same time. For instructions on how to enable a delegated administrator account for GuardDuty, see Managing GuardDuty accounts with AWS Organizations.

To enable EKS Protection

  1. Sign in to the GuardDuty console using the delegated administrator account, choose Protection plans, and then choose EKS Protection.
  2. In the Delegated administrator section, choose Edit and then choose Enable for each scope or protection. For this post, select EKS Audit Log Monitoring, EKS Runtime Monitoring, and Manage agent automatically, as shown in Figure 2. For more information on each feature, see the following resources:
  3. To enable these protections for current accounts, in the Active member accounts section, choose Edit and Enable for each scope of protection.
  4. To enable these protections for new accounts, in the New account default configuration section, choose Edit and Enable for each scope of protection.

To enable RDS Protection

The next step is to enable RDS Protection. GuardDuty RDS Protection works by analysing RDS login activity for potential threats to your Amazon Aurora databases (MySQL-Compatible Edition and Aurora PostgreSQL-Compatible Editions). Using this feature, you can identify potentially suspicious login behavior and then use Detective to investigate CloudTrail logs, VPC flow logs, and other useful information around those events.

  1. Navigate to the RDS Protection menu and under Delegated administrator (this account), select Enable and Confirm.
  2. In the Enabled for section, select Enable all if you want RDS Protection enabled on all of your accounts. If you want to select a specific account, choose Manage Accounts and then select the accounts for which you want to enable RDS Protection. With the accounts selected, choose Edit Protection Plans, RDS Login Activity, and Enable for X selected account.
  3. (Optional) For new accounts, turn on Auto-enable RDS Login Activity Monitoring for new member accounts as they join your organization.
Figure 2: Enable EKS Runtime Monitoring

Figure 2: Enable EKS Runtime Monitoring

To enable Lambda Protection

The final step is to enable Lambda Protection. Lambda Protection helps detect potential security threats during the invocation of AWS Lambda functions. By monitoring network activity logs, GuardDuty can generate findings when Lambda functions are involved with malicious activity, such as communicating with command and control servers.

  1. Navigate to the Lambda Protection menu and under Delegated administrator (this account), select Enable and Confirm.
  2. In the Enabled for section, select Enable all if you want Lambda Protection enabled on all of your accounts. If you want to select a specific account, choose Manage Accounts and select the accounts for which you want to enable RDS Protection. With the accounts selected, choose Edit Protection Plans, Lambda Network Activity Monitoring, and Enable for X selected account.
  3. (Optional) For new accounts, turn on Auto-enable Lambda Network Activity Monitoring for new member accounts as they join your organization.
Figure 4: Enable Lambda Network Activity Monitoring

Figure 4: Enable Lambda Network Activity Monitoring

Now that you’ve enabled these new protections, GuardDuty will start monitoring EKS audit logs, EKS runtime activity, RDS login activity, and Lambda network activity. If GuardDuty detects suspicious or malicious activity for these log sources or services, it will generate a finding for the activity, which you can review in the GuardDuty console. In addition, you can automatically forward these findings to Security Hub for consolidation, and to Detective for security investigation.

Detective data sources

If you have Security Hub and other AWS security services such as GuardDuty or Amazon Inspector enabled, findings from these services are forwarded to Security Hub. With the exception of sensitive data findings from Amazon Macie, you’re automatically opted in to other AWS service integrations when you enable Security Hub. For the full list of services that forward findings to Security Hub, see Available AWS service integrations.

With each service enabled and forwarding findings to Security Hub, the next step is to enable the data source in Detective called AWS security findings, which are the findings forwarded to Security Hub. Again, we’re going to use the delegated administrator account for these steps to make sure that AWS security findings are being ingested for your accounts.

To enable AWS security findings

  1. Sign in to the Detective console using the delegated administrator account and navigate to Settings and then General.
  2. Choose Optional source packages, Edit, select AWS security findings, and then choose Save.
    Figure 5: Enable AWS security findings

    Figure 5: Enable AWS security findings

When you enable Detective, it immediately starts creating a security behavior graph for AWS security findings to build a linked dataset between findings and entities, such as RDS login activity from Aurora databases, EKS runtime activity, and suspicious network activity for Lambda functions. For GuardDuty to detect potential threats that affect your database instances, it first needs to undertake a learning period of up to two weeks to establish a baseline of normal behavior. For more information, see How RDS Protection uses RDS login activity monitoring. For the other protections, after suspicious activity is detected, you can start to see findings in both GuardDuty and Security Hub consoles. This is where you can start using Detective to better understand which findings are connected and where to prioritize your investigations.

Detective behavior graph

As Detective ingests data from GuardDuty, Amazon Inspector, and Security Hub, as well as CloudTrail logs, VPC flow logs, and Amazon Elastic Kubernetes Service (Amazon EKS) audit logs, it builds a behavior graph database. Graph databases are purpose-built to store and navigate relationships. Relationships are first-class citizens in graph databases, which means that they’re not computed out-of-band or by interfering with relationships through querying foreign keys. Because Detective stores information on relationships in your graph database, you can effectively answer questions such as “are these security findings related?”. In Detective, you can use the search menu and profile panels to view these connections, but a quicker way to see this information is by using finding groups visualizations.

Finding groups visualizations

Finding groups extract additional information out of the behavior graph to highlight findings that are highly connected. Detective does this by running several machine learning algorithms across your behavior graph to identify related findings and then statically weighs the relationships between those findings and entities. The result is a finding group that shows GuardDuty and Amazon Inspector findings that are connected, along with entities like Amazon Elastic Compute Cloud (Amazon EC2) instances, AWS accounts, and AWS Identity and Access Management (IAM) roles and sessions that were impacted by these findings. With finding groups, you can more quickly understand the relationships between multiple findings and their causes because you don’t need to connect the dots on your own. Detective automatically does this and presents a visualization so that you can see the relationships between various entities and findings.

Enhanced visualizations

Recently, we released several enhancements to finding groups visualizations to aid your understanding of security connections and root causes. These enhancements include:

  • Dynamic legend – the legend now shows icons for entities that you have in the finding group instead of showing all available entities. This helps reduce noise to only those entities that are relevant to your investigation.
  • Aggregated evidence and finding icons – these icons provide a count of similar evidence and findings. Instead of seeing the same finding or evidence repeated multiple times, you’ll see one icon with a counter to help reduce noise.
  • More descriptive side panel information – when you choose a finding or entity, the side panel shows additional information, such as the service that identified the finding and the finding title, in addition to the finding type, to help you understand the action that invoked the finding.
  • Label titles – you can now turn on or off titles for entities and findings in the visualization so that you don’t have to choose each to get a summary of what the different icons mean.

To use the finding groups visualization

  1. Open the Detective console, choose Summary, and then choose View all finding groups.
  2. Choose the title of an available finding group and scroll down to Visualization.
  3. Under the Select layout menu, choose one of the layouts available, or choose and drag each icon to rearrange the layout according to how you’d like to see connections.
  4. For a complete list of involved entities and involved findings, scroll down below the visualization.

Figure 6 shows an example of how you can use finding groups visualization to help identify the root cause of findings quickly. In this example, an IAM role was connected to newly observed geolocations, multiple GuardDuty findings detected malicious API calls, and there were newly observed user agents from the IAM session. The visualization can give you high confidence that the IAM role is compromised. It also provides other entities that you can search against, such as the IP address, S3 bucket, or new user agents.

Figure 6: Finding groups visualization

Figure 6: Finding groups visualization

Now that you have the new GuardDuty protections enabled along with the data source of AWS security findings, you can use finding groups to more quickly visualize which IAM sessions have had multiple findings associated with unauthorized access, or which EC2 instances are publicly exposed with a software vulnerability and active GuardDuty finding—these patterns can help you determine if there is an actual risk.

Conclusion

In this blog post, you learned how to enable new GuardDuty protections and use Detective, finding groups, and visualizations to better identify, operationalize, and prioritize AWS security findings that represent real risk. We also highlighted the new enhancements to visualizations that can help reduce noise and provide summaries of detailed information to help reduce the time it takes to triage findings. If you’d like to see an investigation scenario using Detective, watch the video Amazon Detective Security Scenario Investigation.

If you have feedback about this post, submit comments in the Comments section below. You can also start a new thread on Amazon Detective re:Post or contact AWS Support.

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

Rich Vorwaller

Rich Vorwaller

Rich is a Principal Product Manager of Amazon Detective. He came to AWS with a passion for walking backwards from customer security problems. AWS is a great place for innovation, and Rich is excited to dive deep on how customers are using AWS to strengthen their security posture in the cloud. In his spare time, Rich loves to read, travel, and perform a little bit of amateur stand-up comedy.

Nicholas Doropoulos

Nicholas Doropoulos

Nicholas is an AWS Cloud Security Engineer, a bestselling Udemy instructor, and a subject matter expert in AWS Shield, Amazon GuardDuty, AWS IAM, and AWS Certificate Manager. Outside work, he enjoys spending time with his wife and their beautiful baby son.

AWS Weekly Roundup – Amazon MWAA, EMR Studio, Generative AI, and More – August 14, 2023

Post Syndicated from Antje Barth original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-amazon-mwaa-emr-studio-generative-ai-and-more-august-14-2023/

While I enjoyed a few days off in California to get a dose of vitamin sea, a lot has happened in the AWS universe. Let’s take a look together!

Last Week’s Launches
Here are some launches that got my attention:

Amazon MWAA now supports Apache Airflow version 2.6 – Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate end-to-end data pipelines in the cloud. Apache Airflow version 2.6 introduces important security updates and bug fixes that enhance the security and reliability of your workflows. If you’re currently running Apache Airflow version 2.x, you can now seamlessly upgrade to version 2.6.3. Check out this AWS Big Data Blog post to learn more.

Amazon EMR Studio adds support for AWS Lake Formation fine-grained access control – Amazon EMR Studio is a web-based integrated development environment (IDE) for fully managed Jupyter notebooks that run on Amazon EMR clusters. When you connect to EMR clusters from EMR Studio workspaces, you can now choose the AWS Identity and Access Management (IAM) role that you want to connect with. Apache Spark interactive notebooks will access only the data and resources permitted by policies attached to this runtime IAM role. When data is accessed from data lakes managed with AWS Lake Formation, you can enforce table and column-level access using policies attached to this runtime role. For more details, have a look at the Amazon EMR documentation.

AWS Security Hub launches 12 new security controls – AWS Security Hub is a cloud security posture management (CSPM) service that performs security best practice checks, aggregates alerts, and enables automated remediation. With the newly released controls, Security Hub now supports three additional AWS services: Amazon Athena, Amazon DocumentDB (with MongoDB compatibility), and Amazon Neptune. Security Hub has also added an additional control against Amazon Relational Database Service (Amazon RDS). AWS Security Hub now offers 276 controls. You can find more information in the AWS Security Hub documentation.

Additional AWS services available in the AWS Israel (Tel Aviv) Region – The AWS Israel (Tel Aviv) Region opened on August 1, 2023. This past week, AWS Service Catalog, Amazon SageMaker, Amazon EFS, and Amazon Kinesis Data Analytics were added to the list of available services in the Israel (Tel Aviv) Region. Check the AWS Regional Services List for the most up-to-date availability information.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Other AWS News
Here are some additional blog posts and news items that you might find interesting:

AWS recognized as a Leader in 2023 Gartner Magic Quadrant for Contact Center as a Service with Amazon Connect – AWS was named a Leader for the first time since Amazon Connect, our flexible, AI-powered cloud contact center, was launched in 2017. Read the full story here. 

Generate creative advertising using generative AI –  This AWS Machine Learning Blog post shows how to generate captivating and innovative advertisements at scale using generative AI. It discusses the technique of inpainting and how to seamlessly create image backgrounds, visually stunning and engaging content, and reducing unwanted image artifacts.

AWS open-source news and updates – My colleague Ricardo writes this weekly open-source newsletter in which he highlights new open-source projects, tools, and demos from the AWS Community.

Upcoming AWS Events
Check your calendars and sign up for these AWS events:

Build On AWS - Generative AIBuild On Generative AI – Your favorite weekly Twitch show about all things generative AI is back for season 2 today! Every Monday, 9:00 US PT, my colleagues Emily and Darko look at new technical and scientific patterns on AWS, inviting guest speakers to demo their work and show us how they built something new to improve the state of generative AI.

In today’s episode, Emily and Darko discussed the latest models LlaMa-2 and Falcon, and explored them in retrieval-augmented generation design patterns. You can watch the video here. Check out show notes and the full list of episodes on community.aws.

AWS NLP Conference 2023 – Join this in-person event on September 13–14 in London to hear about the latest trends, ground-breaking research, and innovative applications that leverage natural language processing (NLP) capabilities on AWS. This year, the conference will primarily focus on large language models (LLMs), as they form the backbone of many generative AI applications and use cases. Register here.

AWS Global Summits – The 2023 AWS Summits season is almost coming to an end with the last two in-person events in Mexico City (August 30) and Johannesburg (September 26).

AWS Community Days – Join a community-led conference run by AWS user group leaders in your region: West Africa (August 19), Taiwan (August 26), Aotearoa (September 6), Lebanon (September 9), and Munich (September 14).

AWS re:Invent 2023AWS re:Invent (November 27 – December 1) – Join us to hear the latest from AWS, learn from experts, and connect with the global cloud community. Registration is now open.

You can browse all upcoming in-person and virtual events.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— Antje

P.S. We’re focused on improving our content to provide a better customer experience, and we need your feedback to do so. Take this quick survey to share insights on your experience with the AWS Blog. Note that this survey is hosted by an external company, so the link doesn’t lead to our website. AWS handles your information as described in the AWS Privacy Notice.

Optimize AWS Config for AWS Security Hub to effectively manage your cloud security posture

Post Syndicated from Nicholas Jaeger original https://aws.amazon.com/blogs/security/optimize-aws-config-for-aws-security-hub-to-effectively-manage-your-cloud-security-posture/

AWS Security Hub is a cloud security posture management service that performs security best practice checks, aggregates security findings from Amazon Web Services (AWS) and third-party security services, and enables automated remediation. Most of the checks Security Hub performs on AWS resources happen as soon as there is a configuration change, giving you nearly immediate visibility of non-compliant resources in your environment, compared to checks that run on a periodic basis. This near real-time finding and reporting of non-compliant resources helps you to quickly respond to infrastructure misconfigurations and reduce risk. Security Hub offers these continuous security checks through its integration with the AWS Config configuration recorder.

By default, AWS Config enables recording for more than 300 resource types in your account. Today, Security Hub has controls that cover approximately 60 of those resource types. If you’re using AWS Config only for Security Hub, you can optimize the configuration of the configuration recorder to track only the resources you need, helping to reduce the costs related to monitoring those resources in AWS Config and the amount of data produced, stored, and analyzed by AWS Config. This blog post walks you through how to set up and optimize the AWS Config recorder when it is used for controls in Security Hub.

Using AWS Config and Security Hub for continuous security checks

When you enable Security Hub, you’re alerted to first enable resource recording in AWS Config, as shown in Figure 1. AWS Config continually assesses, audits, and evaluates the configurations and relationships of your resources on AWS, on premises, and in other cloud environments. Security Hub uses this capability to perform change-initiated security checks. Security Hub checks that use periodic rules don’t depend on the AWS Config recorder. You must enable AWS Config resource recording for all the accounts and in all AWS Regions where you plan to enable Security Hub standards and controls. AWS Config charges for the configuration items that are recorded, separately from Security Hub.

Figure 1: Security Hub alerts you to first enable resource recording in AWS Config

Figure 1: Security Hub alerts you to first enable resource recording in AWS Config

When you get started with AWS Config, you’re prompted to set up the configuration recorder, as shown in Figure 2. AWS Config uses the configuration recorder to detect changes in your resource configurations and capture these changes as configuration items. Using the AWS Config configuration recorder not only allows for continuous security checks, it also minimizes the need to query for the configurations of the individual services, saving your service API quotas for other use cases. By default, the configuration recorder records the supported resources in the Region where the recorder is running.

Note: While AWS Config supports the configuration recording of more than 300 resource types, some Regions support only a subset of those resource types. To learn more, see Supported Resource Types and Resource Coverage by Region Availability.

Figure 2: Default AWS Config settings

Figure 2: Default AWS Config settings

Optimizing AWS Config for Security Hub

Recording global resources as well as current and future resources in AWS Config is more than what is necessary to enable Security Hub controls. If you’re using the configuration recorder only for Security Hub controls, and you want to cost optimize your use of AWS Config or reduce the amount of data produced, stored, and analyzed by AWS Config, you only need to record the configurations of approximately 60 resource types, as described in AWS Config resources required to generate control findings.

Set up AWS Config, optimized for Security Hub

We’ve created an AWS CloudFormation template that you can use to set up AWS Config to record only what’s needed for Security Hub. You can download the template from GitHub.

This template can be used in any Region that supports AWS Config (see AWS Services by Region). Although resource coverage varies by Region (Resource Coverage by Region Availability), you can still use this template in every Region. If a resource type is supported by AWS Config in at least one Region, you can enable the recording of that resource type in all Regions supported by AWS Config. For the Regions that don’t support the specified resource type, the recorder will be enabled but will not record any configuration items until AWS Config supports the resource type in the Region.

Security Hub regularly releases new controls that might rely on recording additional resource types in AWS Config. When you use this template, you can subscribe to Security Hub announcements with Amazon Simple Notification Service (SNS) to get information about newly released controls that might require you to update the resource types recorded by AWS Config (and listed in the CloudFormation template). The CloudFormation template receives periodic updates in GitHub, but you should validate that it’s up to date before using it. You can also use AWS CloudFormation StackSets to deploy, update, or delete the template across multiple accounts and Regions with a single operation. If you don’t enable the recording of all resources in AWS Config, the Security Hub control, Config.1 AWS Config should be enabled, will fail. If you take this approach, you have the option to disable the Config.1 Security Hub control or suppress its findings using the automation rules feature in Security Hub.

Customizing for your use cases

You can modify the CloudFormation template depending on your use cases for AWS Config and Security Hub. If your use case for AWS Config extends beyond your use of Security Hub controls, consider what additional resource types you will need to record the configurations of for your use case. For example, AWS Firewall Manager, AWS Backup, AWS Control Tower, AWS Marketplace, and AWS Trusted Advisor require AWS Config recording. Additionally, if you use other features of AWS Config, such as custom rules that depend on recording specific resource types, you can add these resource types in the CloudFormation script. You can see the results of AWS Config rule evaluations as findings in Security Hub.

Another customization example is related to the AWS Config configuration timeline. By default, resources evaluated by Security Hub controls include links to the associated AWS Config rule and configuration timeline in AWS Config for that resource, as shown in Figure 3.

Figure 3: Link from Security Hub control to the configuration timeline for the resource in AWS Config

Figure 3: Link from Security Hub control to the configuration timeline for the resource in AWS Config

The AWS Config configuration timeline, as illustrated in Figure 4, shows you the history of compliance changes for the resource, but it requires the AWS::Config::ResourceCompliance resource type to be recorded. If you need to track changes in compliance for resources and use the configuration timeline in AWS Config, you must add the AWS::Config::ResourceCompliance resource type to the CloudFormation template provided in the preceding section. In this case, Security Hub may change the compliance of the Security Hub managed AWS Config rules, which are recorded as configuration items for the AWS::Config::ResourceCompliance resource type, incurring additional AWS Config recorder charges.

Figure 4: Config resource timeline

Figure 4: Config resource timeline

Summary

You can use the CloudFormation template provided in this post to optimize the AWS Config configuration recorder for Security Hub to reduce your AWS Config costs and to reduce the amount of data produced, stored, and analyzed by AWS Config. Alternatively, you can run AWS Config with the default settings or use the AWS Config console or scripts to further customize your configuration to fit your use case. Visit Getting started with AWS Security Hub to learn more about managing your security alerts.

 
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.

Nicholas Jaeger

Nicholas Jaeger

Nicholas is a Senior Security Specialist Solutions Architect at AWS. His background includes software engineering, teaching, solutions architecture, and AWS security. Today, he focuses on helping as many customers operate as securely as possible on AWS. Nicholas also hosts AWS Security Activation Days to provide customers with prescriptive guidance while using AWS security services to increase visibility and reduce risk.

Dora Karali

Dora Karali

Dora is a Senior Manager of Product Management at AWS External Security Services. She is currently responsible for Security Hub and has previously worked on GuardDuty, too. Dora has more than 15 years of experience in cybersecurity. She has defined strategy for and created, managed, positioned, and sold cybersecurity cloud and on-premises products and services in multiple enterprise and consumer markets.

Consolidating controls in Security Hub: The new controls view and consolidated findings

Post Syndicated from Emmanuel Isimah original https://aws.amazon.com/blogs/security/consolidating-controls-in-security-hub-the-new-controls-view-and-consolidated-findings/

In this blog post, we focus on two recently released features of AWS Security Hub: the consolidated controls view and consolidated control findings. You can use these features to manage controls across standards and to consolidate findings, which can help you significantly reduce finding noise and administrative overhead.

Security Hub is a cloud security posture management service that you can use to apply security best practice controls, such as “EC2 instances should not have a public IP address.” With Security Hub, you can check that your environment is properly configured and that your existing configurations don’t pose a security risk. Security Hub has more than 200 controls that cover more than 30 AWS services, such as Amazon Elastic Compute Cloud (Amazon EC2), Amazon Simple Storage Service (Amazon S3), and AWS Lambda. In addition, Security Hub has integrations with more than 85 partner products. Security Hub can centralize findings across your AWS accounts and AWS Regions into a single delegated administrator account in your aggregation Region of choice, creating a single pane of glass to view findings. This can help you to triage, investigate, and respond to findings in a simpler way and improve your security posture.

The Security Hub controls are grouped into the following security standards:

With the new features — consolidated controls view and consolidated control findings—you can now do the following:

  • Enable or disable controls across standards in a single action. Previously, if you wanted to maintain the same enablement status of controls between standards, you had to take the same action across multiple standards (up to six times!).
  • If you choose to turn on consolidated control findings, you will receive only a single finding for a security check, even if the security check is enabled across several standards. This reduces the number of findings and helps you focus on the most important misconfigured resources in your AWS environment. It allows you to apply actions and updates (such as suppressing the finding or changing its severity) one time rather than having to do so multiple times across non-consolidated findings.

Overview of new features

Now we’ll discuss some of the details of how you can use the two new features to streamline the management of controls.

The new consolidated controls view

On the new Controls page, now available in the Security Hub console as shown in Figure 1, you can view and configure security controls across standards from one central location.

Figure 1: Security Hub Controls page

Figure 1: Security Hub Controls page

Before this release, controls had to be managed within the context of individual security standards. Even if the same control was part of multiple standards, the control had different IDs in each of them. With this recent release, Security Hub now assigns controls a unique security control ID across standards, so that it’s simpler for you to reference the controls and view their findings. Following the current naming convention of the AWS FSBP standard, the consolidated control IDs start with the relevant service in scope for the control. In fact, whenever possible, the new consolidated control ID is the same as the previous FSBP control ID.

For example, before this release, control IAM.6 in FSBP was also referenced as 1.14 in CIS 1.2, and 1.6 in CIS 1.4, PCI.IAM.4, and CT.IAM.6. After the release, the control is now referenced as IAM.6 in the Security Hub standards. This change does not affect the pre-existing API calls for Security Hub, such as UpdateStandardsControl, where you can still provide the previous StandardControlARN in order to make the call.

By using the new Controls view, you can understand the status of controls across your system, view control findings, and prioritize next steps without context switching. The following information is available on the Controls page of the Security Hub console:

  • An overall security score, which is based on the proportion of passed controls to the total number of enabled controls.
  • A breakdown of security checks across controls, with the percentage of failed security checks highlighted. Because many controls can contain multiple security checks and multiple findings, this value might be different from the security score, which considers controls as a single object. You can use this metric, as well as your security score, to monitor your progress as you work to remediate findings.
  • A list of controls that are categorized into different tabs based on enablement and compliance status. If you are an administrator of an organization within Security Hub, the enablement and compliance status will reflect the aggregate status of the entire organization. In your finding aggregation Region, the status will also be aggregated across linked Regions.

From the controls page, you can select a control to view its details (including its title and the standards it belongs to), and view and act on the findings generated by the control.

Security Hub also offers new API operations that match the capabilities of the controls page. Unlike the pre-existing API operations, these new API operations use the consolidated control IDs (also known as security control IDs) to provide a way to know and manage the relationship between controls and standards. You can use these API operations to manage each Security Hub control across standards, to make sure that the status of controls in the standards is aligned. The new API operations include the following:

We also provide an example script that makes use of these API calls and applies them across accounts and Regions so that your configuration is consistent. You can use our script to enable or disable Security Hub controls across your various accounts or Regions.

Consolidating control findings between standards

Before we released the consolidated control findings feature, Security Hub generated separate findings per standard for each related control. Now, you can turn on consolidated control findings, and after doing so, Security Hub will produce a single finding per security check, even when the underlying control is shared across multiple standards. Having a single finding per check across standards will help you investigate, update, and remediate failed findings more quickly, while also reducing finding noise.

As an example, we can look at control CloudTrail.2, which is shared between standards supported by Security Hub. Before you turn on this capability, you might potentially receive up to six findings for each security check generated by this control—with one finding for each security standard. After you turn on consolidated control findings, these older findings will be archived and Security Hub will generate one finding per security check in this control, regardless of how many security standards you have enabled. For an example of how the standard-specific findings compare to the new consolidated finding, see Sample control findings. The following is an example of a consolidated finding for the CloudTrial.2 control; we’ve highlighted the part that shows this finding is shared across standards.

{
  "SchemaVersion": "2018-10-08",
  "Id": "arn:aws:securityhub:us-east-2:123456789012:security-control/CloudTrail.2/finding/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111",
  "ProductArn": "arn:aws:securityhub:us-east-2::product/aws/securityhub",
  "ProductName": "Security Hub",
  "CompanyName": "AWS",
  "Region": "us-east-2",
  "GeneratorId": "security-control/CloudTrail.2",
  "AwsAccountId": "123456789012",
  "Types": [
    "Software and Configuration Checks/Industry and Regulatory Standards"
  ],
  "FirstObservedAt": "2022-10-06T02:18:23.076Z",
  "LastObservedAt": "2022-10-28T16:10:06.956Z",
  "CreatedAt": "2022-10-06T02:18:23.076Z",
  "UpdatedAt": "2022-10-28T16:10:00.093Z",
  "Severity": {
    "Label": "MEDIUM",
    "Normalized": "40",
    "Original": "MEDIUM"
  },
  "Title": "CloudTrail should have encryption at-rest enabled",
  "Description": "This AWS control checks whether AWS CloudTrail is configured to use the server-side encryption (SSE) AWS Key Management Service (AWS KMS) customer master key (CMK) encryption. The check will pass if the KmsKeyId is defined.",
  "Remediation": {
    "Recommendation": {
      "Text": "For directions on how to correct this issue, consult the AWS Security Hub controls documentation.",
      "Url": "https://docs.aws.amazon.com/console/securityhub/CloudTrail.2/remediation"
    }
  },
  "ProductFields": {
    "RelatedAWSResources:0/name": "securityhub-cloud-trail-encryption-enabled-fe95bf3f",
    "RelatedAWSResources:0/type": "AWS::Config::ConfigRule",
    "aws/securityhub/ProductName": "Security Hub",
    "aws/securityhub/CompanyName": "AWS",
    "Resources:0/Id": "arn:aws:cloudtrail:us-east-2:123456789012:trail/AWSMacieTrail-DO-NOT-EDIT",
    "aws/securityhub/FindingId": "arn:aws:securityhub:us-east-2::product/aws/securityhub/arn:aws:securityhub:us-east-2:123456789012:security-control/CloudTrail.2/finding/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111"
  }
  "Resources": [
    {
      "Type": "AwsCloudTrailTrail",
      "Id": "arn:aws:cloudtrail:us-east-2:123456789012:trail/AWSMacieTrail-DO-NOT-EDIT",
      "Partition": "aws",
      "Region": "us-east-2"
    }
  ],
  "Compliance": {
    "Status": "FAILED",
    "RelatedRequirements": [
        "PCI DSS v3.2.1/3.4",
        "CIS AWS Foundations Benchmark v1.2.0/2.7",
        "CIS AWS Foundations Benchmark v1.4.0/3.7"
    ],
    "SecurityControlId": "CloudTrail.2",
    "AssociatedStandards": [
  { "StandardsId": "standards/aws-foundational-security-best-practices/v/1.0.0"},
  { "StandardsId": "standards/pci-dss/v/3.2.1"},
  { "StandardsId": "ruleset/cis-aws-foundations-benchmark/v/1.2.0"},
  { "StandardsId": "standards/cis-aws-foundations-benchmark/v/1.4.0"},
  { "StandardsId": "standards/service-managed-aws-control-tower/v/1.0.0"},
  ]
  },
  "WorkflowState": "NEW",
  "Workflow": {
    "Status": "NEW"
  },
  "RecordState": "ACTIVE",
  "FindingProviderFields": {
    "Severity": {
      "Label": "MEDIUM",
      "Normalized": "40",
      "Original": "MEDIUM"
    },
    "Types": [
      "Software and Configuration Checks/Industry and Regulatory Standards"
    ]
  }
}

To turn on consolidated control findings

  1. Open the Security Hub console.
  2. In the left navigation pane, choose Settings, and then choose the General tab.
  3. Under Controls, turn on Consolidated control findings, and then choose Save.
Figure 2: Turn on consolidated control findings

Figure 2: Turn on consolidated control findings

If you are using the Security Hub integration with AWS Organizations or have invited member accounts through a manual invitation process, consolidated control findings can only be turned on by the administrator account. When this action is taken in the administrator account, the action will also be reflected in each member account in the current Region. It can take up to 18 hours for Security Hub to archive existing standard-specific findings and generate the new, standard-agnostic, findings.

You can also enable consolidated control findings by using the API (calling the UpdateSecurityHubConfiguration API with the ControlFindingGenerator parameter equal to SECURITY_CONTROL), or by using the AWS CLI (running the update-security-hub-configuration command with control-finding-generator equal to SECURITY_CONTROL), as in the following example.

aws securityhub ‐‐region <Region of choice> update-security-hub-configuration ‐‐control-finding-generator SECURITY_CONTROL

Much like the console behavior, if you have an organizational setup in Security Hub, this API action can only be taken by the administrator, and it will be reflected in each member account in the same Region.

What to expect when you enable consolidated control findings

To allow for these new capabilities to be launched, changes to the AWS Security Finding Format (ASFF) are required. This format is used by Security Hub for findings it generates from its controls or ingests from external providers. When you turn on finding consolidation, Security Hub will archive old standard-specific findings and generate standard-agnostic findings instead. This action will only affect control findings that Security Hub generates, and it will not affect findings ingested from partner products. However, in Security Hub findings, turning on consolidated control findings might cause some updates that you previously made to findings to be archived. Despite this one-time change, after the migration is complete (it can take up to 18 hours), you will be able to update finding fields in a single action and the updates will apply across standards, without the need to make multiple updates.

One field affected by the new capabilities is the Workflow field, which provides information about the status of the investigation into a finding. Manipulating this field can also update the overall compliance status of the control that the finding is related to. For example, if you have a control with one failed finding (and the rest have passed), and the failed finding comes from a resource for which you’d like to make an exception, you can decide to suppress that failed finding by updating the Workflow field. If you suppress failed findings in a control, its compliance status can change to pass.

Before turning on consolidated control findings, if you want to maintain an aligned compliance status in controls that belong to multiple standards, you have to update the Workflow status of findings in each standard. After turning on finding consolidation, you will only have to update the Workflow status once, and the suppression will be applied across standards, helping you to reduce the number of steps needed to suppress the same findings across standards.

As mentioned earlier, when you turn on this new capability, some updates made to the previous, standard-specific findings will be archived and will not be included in the new consolidated control findings generated by Security Hub. In the case of the Workflow status, the new consolidated findings will be created with a value of NEW (for failed findings) or RESOLVED (for new findings) in the Workflow field. However, after you have onboarded to the new finding format, you can update the value of the Workflow field, as well as other fields, and this value will be maintained without requiring you to make continuous updates. For the full list of fields that can be affected by the migration to the consolidated finding format, see Consolidated control findings – ASFF changes. Before you turn on finding consolidation, we suggest that you check if your custom automations refer to those affected fields. If they do, you can update your automations and test them by using the Sample control findings in the documentation.

Conclusion

This blog post covers new Security Hub features that make it simpler for you to manage controls across standards. With the new consolidated control findings feature, you can focus on the most relevant findings and reduce noise, which is why we recommend that you review the new feature and its associated changes and turn it on at your earliest convenience.

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

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Emmanuel Isimah

Emmanuel Isimah

Emmanuel is a solutions architect covering hypergrowth customers in the Digital Native Business sector. He has a background in networking, security, and containers. Emmanuel helps customers build and secure innovative cloud solutions, solving their business problems by using data-driven approaches. Emmanuel’s areas of depth include security and compliance, cloud operations, and containers.

Three ways to accelerate incident response in the cloud: insights from re:Inforce 2023

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/security/three-ways-to-accelerate-incident-response-in-the-cloud-insights-from-reinforce-2023/

AWS re:Inforce took place in Anaheim, California, on June 13–14, 2023. AWS customers, partners, and industry peers participated in hundreds of technical and non-technical security-focused sessions across six tracks, an Expo featuring AWS experts and AWS Security Competency Partners, and keynote and leadership sessions.

The threat detection and incident response track showcased how AWS customers can get the visibility they need to help improve their security posture, identify issues before they impact business, and investigate and respond quickly to security incidents across their environment.

With dozens of service and feature announcements—and innumerable best practices shared by AWS experts, customers, and partners—distilling highlights is a challenge. From an incident response perspective, three key themes emerged.

Proactively detect, contextualize, and visualize security events

When it comes to effectively responding to security events, rapid detection is key. Among the launches announced during the keynote was the expansion of Amazon Detective finding groups to include Amazon Inspector findings in addition to Amazon GuardDuty findings.

Detective, GuardDuty, and Inspector are part of a broad set of fully managed AWS security services that help you identify potential security risks, so that you can respond quickly and confidently.

Using machine learning, Detective finding groups can help you conduct faster investigations, identify the root cause of events, and map to the MITRE ATT&CK framework to quickly run security issues to ground. The finding group visualization panel shown in the following figure displays findings and entities involved in a finding group. This interactive visualization can help you analyze, understand, and triage the impact of finding groups.

Figure 1: Detective finding groups visualization panel

Figure 1: Detective finding groups visualization panel

With the expanded threat and vulnerability findings announced at re:Inforce, you can prioritize where to focus your time by answering questions such as “was this EC2 instance compromised because of a software vulnerability?” or “did this GuardDuty finding occur because of unintended network exposure?”

In the session Streamline security analysis with Amazon Detective, AWS Principal Product Manager Rich Vorwaller, AWS Senior Security Engineer Rima Tanash, and AWS Program Manager Jordan Kramer demonstrated how to use graph analysis techniques and machine learning in Detective to identify related findings and resources, and investigate them together to accelerate incident analysis.

In addition to Detective, you can also use Amazon Security Lake to contextualize and visualize security events. Security Lake became generally available on May 30, 2023, and several re:Inforce sessions focused on how you can use this new service to assist with investigations and incident response.

As detailed in the following figure, Security Lake automatically centralizes security data from AWS environments, SaaS providers, on-premises environments, and cloud sources into a purpose-built data lake stored in your account. Security Lake makes it simpler to analyze security data, gain a more comprehensive understanding of security across an entire organization, and improve the protection of workloads, applications, and data. Security Lake automates the collection and management of security data from multiple accounts and AWS Regions, so you can use your preferred analytics tools while retaining complete control and ownership over your security data. Security Lake has adopted the Open Cybersecurity Schema Framework (OCSF), an open standard. With OCSF support, the service normalizes and combines security data from AWS and a broad range of enterprise security data sources.

Figure 2: How Security Lake works

Figure 2: How Security Lake works

To date, 57 AWS security partners have announced integrations with Security Lake, and we now have more than 70 third-party sources, 16 analytics subscribers, and 13 service partners.

In Gaining insights from Amazon Security Lake, AWS Principal Solutions Architect Mark Keating and AWS Security Engineering Manager Keith Gilbert detailed how to get the most out of Security Lake. Addressing questions such as, “How do I get access to the data?” and “What tools can I use?,” they demonstrated how analytics services and security information and event management (SIEM) solutions can connect to and use data stored within Security Lake to investigate security events and identify trends across an organization. They emphasized how bringing together logs in multiple formats and normalizing them into a single format empowers security teams to gain valuable context from security data, and more effectively respond to events. Data can be queried with Amazon Athena, or pulled by Amazon OpenSearch Service or your SIEM system directly from Security Lake.

Build your security data lake with Amazon Security Lake featured AWS Product Manager Jonathan Garzon, AWS Product Solutions Architect Ross Warren, and Global CISO of Interpublic Group (IPG) Troy Wilkinson demonstrating how Security Lake helps address common challenges associated with analyzing enterprise security data, and detailing how IPG is using the service. Wilkinson noted that IPG’s objective is to bring security data together in one place, improve searches, and gain insights from their data that they haven’t been able to before.

“With Security Lake, we found that it was super simple to bring data in. Not just the third-party data and Amazon data, but also our on-premises data from custom apps that we built.” — Troy Wilkinson, global CISO, Interpublic Group

Use automation and machine learning to reduce mean time to response

Incident response automation can help free security analysts from repetitive tasks, so they can spend their time identifying and addressing high-priority security issues.

In How LLA reduces incident response time with AWS Systems Manager, telecommunications provider Liberty Latin America (LLA) detailed how they implemented a security framework to detect security issues and automate incident response in more than 180 AWS accounts accessed by internal stakeholders and third-party partners by using AWS Systems Manager Incident Manager, AWS Organizations, Amazon GuardDuty, and AWS Security Hub.

LLA operates in over 20 countries across Latin America and the Caribbean. After completing multiple acquisitions, LLA needed a centralized security operations team to handle incidents and notify the teams responsible for each AWS account. They used GuardDuty, Security Hub, and Systems Manager Incident Manager to automate and streamline detection and response, and they configured the services to initiate alerts whenever there was an issue requiring attention.

Speaking alongside AWS Principal Solutions Architect Jesus Federico and AWS Principal Product Manager Sarah Holberg, LLA Senior Manager of Cloud Services Joaquin Cameselle noted that when GuardDuty identifies a critical issue, it generates a new finding in Security Hub. This finding is then forwarded to Systems Manager Incident Manager through an Amazon EventBridge rule. This configuration helps ensure the involvement of the appropriate individuals associated with each account.

“We have deployed a security framework in Liberty Latin America to identify security issues and streamline incident response across over 180 AWS accounts. The framework that leverages AWS Systems Manager Incident Manager, Amazon GuardDuty, and AWS Security Hub enabled us to detect and respond to incidents with greater efficiency. As a result, we have reduced our reaction time by 90%, ensuring prompt engagement of the appropriate teams for each AWS account and facilitating visibility of issues for the central security team.” — Joaquin Cameselle, senior manager, cloud services, Liberty Latin America

How Citibank (Citi) advanced their containment capabilities through automation outlined how the National Institute of Standards and Technology (NIST) Incident Response framework is applied to AWS services, and highlighted Citi’s implementation of a highly scalable cloud incident response framework designed to support the 28 AWS services in their cloud environment.

After describing the four phases of the incident response process — preparation and prevention; detection and analysis; containment, eradication, and recovery; and post-incident activity—AWS ProServe Global Financial Services Senior Engagement Manager Harikumar Subramonion noted that, to fully benefit from the cloud, you need to embrace automation. Automation benefits the third phase of the incident response process by speeding up containment, and reducing mean time to response.

Citibank Head of Cloud Security Operations Elvis Velez and Vice President of Cloud Security Damien Burks described how Citi built the Cloud Containment Automation Framework (CCAF) from the ground up by using AWS Step Functions and AWS Lambda, enabling them to respond to events 24/7 without human error, and reduce the time it takes to contain resources from 4 hours to 15 minutes. Velez described how Citi uses adversary emulation exercises that use the MITRE ATT&CK Cloud Matrix to simulate realistic attacks on AWS environments, and continuously validate their ability to effectively contain incidents.

Innovate and do more with less

Security operations teams are often understaffed, making it difficult to keep up with alerts. According to data from CyberSeek, there are currently 69 workers available for every 100 cybersecurity job openings.

Effectively evaluating security and compliance posture is critical, despite resource constraints. In Centralizing security at scale with Security Hub and Intuit’s experience, AWS Senior Solutions Architect Craig Simon, AWS Senior Security Hub Product Manager Dora Karali, and Intuit Principal Software Engineer Matt Gravlin discussed how to ease security management with Security Hub. Fortune 500 financial software provider Intuit has approximately 2,000 AWS accounts, 10 million AWS resources, and receives 20 million findings a day from AWS services through Security Hub. Gravlin detailed Intuit’s Automated Compliance Platform (ACP), which combines Security Hub and AWS Config with an internal compliance solution to help Intuit reduce audit timelines, effectively manage remediation, and make compliance more consistent.

“By using Security Hub, we leveraged AWS expertise with their regulatory controls and best practice controls. It helped us keep up to date as new controls are released on a regular basis. We like Security Hub’s aggregation features that consolidate findings from other AWS services and third-party providers. I personally call it the super aggregator. A key component is the Security Hub to Amazon EventBridge integration. This allowed us to stream millions of findings on a daily basis to be inserted into our ACP database.” — Matt Gravlin, principal software engineer, Intuit

At AWS re:Inforce, we launched a new Security Hub capability for automating actions to update findings. You can now use rules to automatically update various fields in findings that match defined criteria. This allows you to automatically suppress findings, update the severity of findings according to organizational policies, change the workflow status of findings, and add notes. With automation rules, Security Hub provides you a simplified way to build automations directly from the Security Hub console and API. This reduces repetitive work for cloud security and DevOps engineers and can reduce mean time to response.

In Continuous innovation in AWS detection and response services, AWS Worldwide Security Specialist Senior Manager Himanshu Verma and GuardDuty Senior Manager Ryan Holland highlighted new features that can help you gain actionable insights that you can use to enhance your overall security posture. After mapping AWS security capabilities to the core functions of the NIST Cybersecurity Framework, Verma and Holland provided an overview of AWS threat detection and response services that included a technical demonstration.

Bolstering incident response with AWS Wickr enterprise integrations highlighted how incident responders can collaborate securely during a security event, even on a compromised network. AWS Senior Security Specialist Solutions Architect Wes Wood demonstrated an innovative approach to incident response communications by detailing how you can integrate the end-to-end encrypted collaboration service AWS Wickr Enterprise with GuardDuty and AWS WAF. Using Wickr Bots, you can build integrated workflows that incorporate GuardDuty and third-party findings into a more secure, out-of-band communication channel for dedicated teams.

Evolve your incident response maturity

AWS re:Inforce featured many more highlights on incident response, including How to run security incident response in your Amazon EKS environment and Investigating incidents with Amazon Security Lake and Jupyter notebooks code talks, as well as the announcement of our Cyber Insurance Partners program. Content presented throughout the conference made one thing clear: AWS is working harder than ever to help you gain the insights that you need to strengthen your organization’s security posture, and accelerate incident response in the cloud.

To watch AWS re:Inforce sessions on demand, see the AWS re:Inforce playlists on YouTube.

 
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.

Anne Grahn

Anne Grahn

Anne is a Senior Worldwide Security GTM Specialist at AWS based in Chicago. She has more than a decade of experience in the security industry, and focuses on effectively communicating cybersecurity risk. She maintains a Certified Information Systems Security Professional (CISSP) certification.

Author

Himanshu Verma

Himanshu is a Worldwide Specialist for AWS Security Services. In this role, he leads the go-to-market creation and execution for AWS Security Services, field enablement, and strategic customer advisement. Prior to AWS, he held several leadership roles in Product Management, engineering and development, working on various identity, information security, and data protection technologies. He obsesses brainstorming disruptive ideas, venturing outdoors, photography, and trying various “hole in the wall” food and drinking establishments around the globe.

Jesus Federico

Jesus Federico

Jesus is a Principal Solutions Architect for AWS in the telecommunications vertical, working to provide guidance and technical assistance to communication service providers on their cloud journey. He supports CSPs in designing and implementing secure, resilient, scalable, and high-performance applications in the cloud.

AWS Security Hub launches a new capability for automating actions to update findings

Post Syndicated from Stuart Gregg original https://aws.amazon.com/blogs/security/aws-security-hub-launches-a-new-capability-for-automating-actions-to-update-findings/

If you’ve had discussions with a security organization recently, there’s a high probability that the word automation has come up. As organizations scale and consume the benefits the cloud has to offer, it’s important to factor in and understand how the additional cloud footprint will affect operations. Automation is a key enabler for efficient operations and can help drive down the number of repetitive tasks that the operational teams have to perform.

Alert fatigue is caused when humans work on the same repetitive tasks day in and day out and also have a large volume of alerts that need to be addressed. The repetitive nature of these tasks can cause analysts to become numb to the importance of the task or make errors due to manual processing. This can lead to misclassification of security alerts or higher-severity alerts being overlooked due to investigation times. Automation is key here to reduce the number of repetitive tasks and give analysts time to focus on other areas of importance.

In this blog post, we’ll walk you through new capabilities within AWS Security Hub that you can use to take automated actions to update findings. We’ll show you some example scenarios that use this capability and set you up with the knowledge you need to get started with creating automation rules.

Automation rules in Security Hub

AWS Security Hub is available globally and is designed to give you a comprehensive view of your security posture across your AWS accounts. With Security Hub, you have a single place that aggregates, organizes, and prioritizes your security alerts, or findings, from multiple AWS services, including Amazon GuardDuty, Amazon Inspector, Amazon Macie, AWS Firewall Manager, AWS Systems Manager Patch Manager, AWS Config, AWS Health, and AWS Identity and Access Management (IAM) Access Analyzer, as well as from over 65 AWS Partner Network (APN) solutions.

Previously, Security Hub could take automated actions on findings, but this involved going to the Amazon EventBridge console or API, creating an EventBridge rule, and then building an AWS Lambda function, an AWS Systems Manager Automation runbook, or an AWS Step Functions step as the target of that rule. If you wanted to set up these automated actions in the administrator account and home AWS Region and run them in member accounts and in linked Regions, you would also need to deploy the correct IAM permissions to enable the actions to run across accounts and Regions. After setting up the automation flow, you would need to maintain the EventBridge rule, Lambda function, and IAM roles. Such maintenance could include upgrading the Lambda versions, verifying operational efficiency, and checking that everything is running as expected.

With Security Hub, you can now use rules to automatically update various fields in findings that match defined criteria. This allows you to automatically suppress findings, update findings’ severities according to organizational policies, change findings’ workflow status, and add notes. As findings are ingested, automation rules look for findings that meet defined criteria and update the specified fields in findings that meet the criteria. For example, a user can create a rule that automatically sets the finding’s severity to “Critical” if the finding account ID is of a known business-critical account. A user could also automatically suppress findings for a specific control in an account where the finding represents an accepted risk.

With automation rules, Security Hub provides you a simplified way to build automations directly from the Security Hub console and API. This reduces repetitive work for cloud security and DevOps engineers and can reduce the mean time to response.

Use cases

In this section, we’ve put together some examples of how Security Hub automation rules can help you. There’s a lot of flexibility in how you can use the rules, and we expect there will be many variations that your organization will use when contextual information about security risk has been added.

Scenario 1: Elevate finding severity for specific controls based on account IDs

Security Hub offers protection by using hundreds of security controls that create findings that have a severity associated with them. Sometimes, you might want to elevate that severity according to your organizational policies or according to the context of the finding, such as the account it relates to. With automation rules, you can now automatically elevate the severity for specific controls when they are in a specific account.

For example, the AWS Foundational Security Best Practices control GuardDuty.1 has a “High” severity by default. But you might consider such a finding to have “Critical” severity if it occurs in one of your top production accounts. To change the severity automatically, you can choose GeneratorId as a criteria and check that it’s equal to aws-foundational-security-best-practices/v/1.0.0/GuardDuty.1, and also add AwsAccountId as a criteria and check that it’s equal to YOUR_ACCOUNT_IDs. Then, add an action to update the severity to “Critical,” and add a note to the person who will look at the finding that reads “Urgent — look into these production accounts.”

You can set up this automation rule through the AWS CLI, the console, the Security Hub API, or the AWS SDK for Python (Boto3), as follows.

To set up the automation rule for Scenario 1 (AWS CLI)

  • In the AWS CLI, run the following command to create a new automation rule with a specific Amazon Resource Name (ARN). Note the different modifiable parameters:
    • Rule-name — The name of the rule that will be created.
    • Rule-status — An optional parameter. Specify whether you want Security Hub to activate and start applying the rule to findings after creation. If no value is specified, the default value is ENABLED. A value of DISABLED means that the rule will be paused after creation.
    • Rule-order — Provide the processing order for the rule. Security Hub applies rules with a lower numerical value for this parameter first.
    • Criteria — Provide the criteria that you want Security Hub to use to filter your findings. The rule action will be applied to findings that match the criteria. For a list of supported criteria, see Criteria and actions for automation rules. In this example, the criteria are placeholders and should be replaced.
    • Actions — Provide the actions that you want Security Hub to take when there’s a match between a finding and your defined criteria. For a list of supported actions, see Criteria and actions for automation rules. In this example, the actions are placeholders and should be replaced.
    aws securityhub create-automation-rule \—rule-name "Elevate severity for findings in production accounts - GuardDuty.1" \—rule-status "ENABLED"" \—rule-order 1 \—description "Elevate severity for findings in production accounts - GuardDuty.1" \—criteria '{"GeneratorId": [{"Value": "aws-foundational-security-best-practices/v/1.0.0/GuardDuty.1","Comparison": "EQUALS"}, "AwsAccountId": [{"Value": "<111122223333>","Comparison": "EQUALS"},]}' \—actions '[{"Type": "FINDING_FIELDS_UPDATE","FindingFieldsUpdate": {"Severity": {"Label": "CRITICAL"},"Note": {"Text": "Urgent – look into these production accounts","UpdatedBy": "sechub-automation"}}}]' \—region us-east-1

To set up the automation rule for Scenario 1 (console)

  1. Open the Security Hub console, and in the left navigation pane, choose Automations.
    Figure 1: Automation rules in the Security Hub console

    Figure 1: Automation rules in the Security Hub console

  2. Choose Create rule, and then choose Create a custom rule to get started with creating a rule of your choice. Add a rule name and description.
    Figure 2: Create a new custom rule

    Figure 2: Create a new custom rule

  3. Under Criteria, add the following information.
    • Key 1
      • Key = GeneratorID
      • Operator = EQUALS
      • Value = aws-foundational-security-best-practices/v/1.0.0/GuardDuty.1
    • Key 2
      • Key = AwsAccountId
      • Operator = EQUALS
      • Value = Your AWS account ID
    Figure 3: Information added for the rule criteria

    Figure 3: Information added for the rule criteria

  4. You can preview which findings will match the criteria by looking in the preview section.
    Figure 4: Preview section

    Figure 4: Preview section

  5. Next, under Automated action, specify which finding value to update automatically when findings match your criteria.
    Figure 5: Automated action to be taken against the findings that match the criteria

    Figure 5: Automated action to be taken against the findings that match the criteria

  6. For Rule status, choose Enabled, and then choose Create rule.
    Figure 6: Set the rule status to Enabled

    Figure 6: Set the rule status to Enabled

  7. After you choose Create rule, you will see the newly created rule within the Automations portal.
    Figure 7: Newly created rule within the Security Hub Automations page

    Figure 7: Newly created rule within the Security Hub Automations page

    Note: In figure 7, you can see multiple automation rules. When you create automation rules, you assign each rule an order number. This determines the order in which Security Hub applies your automation rules. This becomes important when multiple rules apply to the same finding or finding field. When multiple rule actions apply to the same finding field, the rule with the highest numerical value for rule order is applied last and has the ultimate effect on that field.

Additionally, if your preferred deployment method is to use the API or AWS SDK for Python (Boto3), we have information on how you can use these means of deployment in our public documentation.

Scenario 2: Change the finding severity to high if a resource is important, based on resource tags

Imagine a situation where you have findings associated to a wide range of resources. Typically, organizations will attempt to prioritize which findings to remediate first. You can achieve this prioritization through Security Hub and the contextual fields that are available for you to use — for example, by using the severity of the finding or the account ID the resource is sitting in. You might also have your own prioritization based on other factors. You could add this additional context to findings by using a tagging strategy. With automation rules, you can now automatically elevate the severity for specific findings based on the tag value associated to the resource.

For example, if a finding comes into Security Hub with the severity rating “Medium,” but the resource in question is critical to the business and has the tag production associated to it, you could automatically raise the severity rating to “High.”

Note: This will work only for findings where there is a resource tag associated with the finding.

Scenario 3: Suppress GuardDuty findings with a severity of “Informational”

GuardDuty provides an overarching view of the state of threats to deployed resources in your organization’s cloud environment. After evaluation, GuardDuty produces findings related to these threats. The findings produced by GuardDuty have different severities, to help organizations with prioritization. Some of these findings will be given an “Informational” severity. “Informational” indicates that no issue was found and the content of the finding is purely to give information. After you have evaluated the context of the finding, you might want to suppress any additional findings that match the same criteria.

For example, you might want to set up a rule so that new findings with the generator ID that produced “Informational” findings are suppressed, keeping only the findings that need action.

Templates

When you create a new rule, you can also choose to create a rule from a template. These templates are regularly updated with use cases that are applicable for many customers.

To set up an automation rule by using a template from the console

  1. In the Security Hub console, choose Automations, and then choose Create rule.
  2. Choose Create a rule from a template to get started with creating a rule of your choice.
  3. Select a rule template from the drop-down menu.
    Figure 8: Select an automation rule template

    Figure 8: Select an automation rule template

  4. (Optional) If necessary, modify the Rule, Criteria, and Automated action sections.
  5. For Rule status, choose whether you want the rule to be enabled or disabled after it’s created.
  6. (Optional) Expand the Additional settings section. Choose Ignore subsequent rules for findings that match these criteria if you want this rule to be the last rule applied to findings that match the rule criteria.
  7. (Optional) For Tags, add tags as key-value pairs to help you identify the rule.
  8. Choose Create rule.

Multi-Region deployment

For organizations that operate in multiple AWS Regions, we’ve provided a solution that you can use to replicate rules created in your central Security Hub admin account into these additional Regions. You can find the sample code for this solution in our GitHub repo.

Conclusion

In this blog post, we’ve discussed the importance of automation and its ability to help organizations scale operations within the cloud. We’ve introduced a new capability in AWS Security Hub, automation rules, that can help reduce the repetitive tasks your operational teams may be facing, and we’ve showcased some example use cases to get you started. Start using automation rules in your environment today. We’re excited to see what use cases you will solve with this feature and as always, are happy to receive any feedback.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on the AWS Security, Identity, & Compliance re:Post or contact AWS Support.

Stuart Gregg

Stuart Gregg

Stuart enjoys providing thought leadership and being a trusted advisor to customers. In his spare time Stuart can be seen either training for an Ironman or snacking.

Shachar Hirshberg

Shachar Hirshberg

Shachar is a Senior Product Manager at AWS Security Hub with over a decade of experience in building, designing, launching, and scaling enterprise software. He is passionate about further improving how customers harness AWS services to enable innovation and enhance the security of their cloud environments. Outside of work, Shachar is an avid traveler and a skiing enthusiast.

New – Simplify the Investigation of AWS Security Findings with Amazon Detective

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/new-simplify-the-investigation-of-aws-security-findings-with-amazon-detective/

With Amazon Detective, you can analyze and visualize security data to investigate potential security issues. Detective collects and analyzes events that describe IP traffic, AWS management operations, and malicious or unauthorized activity from AWS CloudTrail logs, Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, Amazon GuardDuty findings, and, since last year, Amazon Elastic Kubernetes Service (EKS) audit logs. Using this data, Detective constructs a graph model that distills log data using machine learning, statistical analysis, and graph theory to build a linked set of data for your security investigations.

Starting today, Detective offers investigation support for findings in AWS Security Hub in addition to those detected by GuardDuty. Security Hub is a service that provides you with a view of your security state in AWS and helps you check your environment against security industry standards and best practices. If you’ve turned on Security Hub and another integrated AWS security services, those services will begin sending findings to Security Hub.

With this new capability, it is easier to use Detective to determine the cause and impact of findings coming from new sources such as AWS Identity and Access Management (IAM) Access Analyzer, Amazon Inspector, and Amazon Macie. All AWS services that send findings to Security Hub are now supported.

Let’s see how this works in practice.

Enabling AWS Security Findings in the Amazon Detective Console
When you enable Detective for the first time, Detective now identifies findings coming from both GuardDuty and Security Hub, and automatically starts ingesting them along with other data sources. Note that you don’t need to enable or publish these log sources for Detective to start its analysis because this is managed directly by Detective.

If you are an existing Detective customer, you can enable investigation of AWS Security Findings as a data source with one click in the Detective Management Console. I already have Detective enabled, so I add the source package.

In the Detective console, in the Settings section of the navigation pane, I choose General. There, I choose Edit in the Optional source packages section to enable Detective for AWS Security Findings.

Console screenshot.

Once enabled, Detective starts analyzing all the relevant data to identify connections between disparate events and activities. To start your investigation process, you can get a visualization of these connections, including resource behavior and activities. Historical baselines, which you can use to provide comparisons against recent activity, are established after two weeks.

Investigating AWS Security Findings in the Amazon Detective Console
I start in the Security Hub console and choose Findings in the navigation pane. There, I filter findings to only see those where the Product name is Inspector and Severity label is HIGH.

Console screenshot.

The first one looks suspicious, so I choose its Title (CVE-2020-36223 – openldap). The Security Hub console provides me with information about the corresponding Common Vulnerabilities and Exposures (CVE) ID and where and how it was found. At the bottom, I have the option to Investigate in Amazon Detective. I follow the Investigate finding link, and the Detective console opens in another browser tab.

Console screenshot.

Here, I see the entities related to this Inspector finding. First, I open the profile of the AWS account to see all the findings associated with this resource, the overall API call volume issued by this resource, and the container clusters in this account.

For example, I look at the successful and failed API calls to have a better understanding of the impact of this finding.

Console screenshot.

Then, I open the profile for the container image. There, I see the images that are related to this image (because they have the same repository or registry as this image), the containers running from this image during the scope time (managed by Amazon EKS), and the findings associated with this resource.

Depending on the finding, Detective helps me correlate information from different sources such as CloudTrail logs, VPC Flow Logs, and EKS audit logs. This information makes it easier to understand the impact of the finding and if the risk has become an incident. For Security Hub, Detective only ingests findings for configuration checks that failed. Because configuration checks that passed have little security value, we’re filtering these outs.

Availability and Pricing
Amazon Detective investigation support for AWS Security Findings is available today for all existing and new Detective customers in all AWS Regions where Detective is available, including the AWS GovCloud (US) Regions. For more information, see the AWS Regional Services List.

Amazon Detective is priced based on the volume of data ingested. By enabling investigation of AWS Security Findings, you can increase the volume of ingested data. For more information, see Amazon Detective pricing.

When GuardDuty and Security Hub provide a finding, they also suggest the remediation. On top of that, Detective helps me investigate if the vulnerability has been exploited, for example, using logs and network traffic as proof.

Currently, findings coming from Security Hub are not included in the Finding groups section of the Detective console. Our plan is to expand Finding groups to cover the newly integrated AWS security services. Stay tuned!

Start using Amazon Detective to investigate potential security issues.

— Danilo

AWS Week in Review – AWS Notifications, Serverless event, and More – May 8, 2023

Post Syndicated from Marcia Villalba original https://aws.amazon.com/blogs/aws/aws-week-in-review-aws-notifications-serverless-event-and-more-may-8-2023/

At the end of this week, I’m flying to Seattle to take part in the AWS Serverless Innovation Day. Along with many customers and colleagues from AWS, we are going to be live on May 17 at a virtual free event. During the AWS Serverless Innovation Day we will share best practices related to building event-driven applications and using serverless functions and containers. Get a calendar reminder and check the full agenda at the event site.

Serverless innovation day

Last Week’s Launches
Here are some launches that got my attention during the previous week.

New Local Zones in Auckland – AWS Local Zones allow you to deliver applications that require single-digit millisecond latency or local data processing. Starting last week, AWS Local Zones is available in Auckland, New Zealand.

All AWS Local Zones

AWS Notifications – Channy wrote an article explaining how you can view and configure notifications for your AWS account. In addition to the AWS Management Console notifications, the AWS Console Mobile Application now allows you to create and receive actionable push notifications when a resource requires your attention.

AWS SimSpace Weaver – Last reInvent, we launched AWS SimSpace Weaver, a fully managed compute service that helps you deploy large spatial simulations in the cloud. Starting last week, AWS SimSpace Weaver allows you to save the state of the simulations at a specific point in time.

AWS Security Hub – Added four new integration partners to help customers with their cloud security posture monitoring, and now it provides detailed tracking of finding changes with the finding history feature. This last feature provides an immutable trail of changes to get more visibility into the changes made to your findings.

AWS Compute Optimizer – AWS Compute Optimizer supports inferred workload type filtering on Amazon EC2 instance recommendations and automatically detects the applications that might run on your AWS resources. Now AWS Compute Optimizer supports filtering your rightsizing recommendation by tags and identifies and filters Microsoft SQL Server workloads as an inferred workload type.

AWS AppSync– Now AWS AppSync GraphQL APIs support Private API. With Private APIs, you can now create GraphQL APIs that can only be accessed from your Amazon Virtual Private Cloud (Amazon VPC).

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Other AWS News
Some other updates and news that you may have missed:

  • Responsible AI in the Generative Era – Amazon Science published a very interesting blog post this week about the special challenges raised by building a responsible generative AI and the different things builders of applications can do in order to solve these challenges.
  • Patterns for Building an API to Upload Files to Amazon S3 – Amazon S3 is one of the most used services by our customers, and applications often require a way for users to upload files. In this article, Thomas Moore shows different ways to do this in a secure way.
  • The Official AWS Podcast – Listen each week for updates on the latest AWS news and deep dives into exciting use cases. There are also official AWS podcasts in your local languages. Check out the ones in French, German, Italian, and Spanish.
  • AWS Open-Source News and Updates – This is a newsletter curated by my colleague Ricardo to bring you the latest open-source projects, posts, events, and more.

Upcoming AWS Events
Check your calendars and sign up for these AWS events:

  • AWS Serverless Innovation Day – Join us on May 17 for a virtual and free event about AWS Serverless. We will have talks and fireside chats with customers related to AWS Lambda, Amazon ECS with Fargate, AWS Step Functions, and Amazon EventBridge.
  • AWS re:Inforce 2023 – You can now register for AWS re:Inforce, happening in Anaheim, California, on June 13–14.
  • AWS Global Summits – There are many summits going on right now around the world: Stockholm (May 11), Hong Kong (May 23), India (May 25), Amsterdam (June 1), London (June 7), Washington, DC (June 7–8), Toronto (June 14), Madrid (June 15), and Milano (June 22).
  • AWS Community Day – Join a community-led conference run by AWS user group leaders in your region: Warsaw (June 1), Chicago (June 15), Manila (June 29–30), and Munich (September 14).
  • AWS User Group Peru Conference – The local AWS User Group announced a one-day cloud event in Spanish and English in Lima on September 23. Seb, Jeff, and I will be attending the event from the AWS News blog team. Register today!

That’s all for this week. Check back next Monday for another Week in Review!

— Marcia

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Get details on security finding changes with the new Finding History feature in Security Hub

Post Syndicated from Nicholas Jaeger original https://aws.amazon.com/blogs/security/get-details-on-security-finding-changes-with-the-new-finding-history-feature-in-security-hub/

In today’s evolving security threat landscape, security teams increasingly require tools to detect and track security findings to protect their organizations’ assets. One objective of cloud security posture management is to identify and address security findings in a timely and effective manner. AWS Security Hub aggregates, organizes, and prioritizes security alerts and findings from various AWS services and supported security solutions from the AWS Partner Network.

As the volume of findings increases, tracking the changes and actions that have been taken on each finding becomes more difficult, as well as more important to perform timely and effective investigations. In this post, we will show you how to use the new Finding History feature in Security Hub to track and understand the history of a security finding.

Updates to findings occur when finding providers update certain fields, such as resource details, by using the BatchImportFindings API. You, as a user, can update certain fields, such as workflow status, in the AWS Management Console or through the BatchUpdateFindings API. Ticketing, incident management, security information and event management (SIEM), and automatic remediation solutions can also use the BatchUpdateFindings API to update findings. This new capability highlights these various changes and when they occurred so that you don’t need to investigate this yourself.

Finding History

The new Finding History feature in Security Hub helps you understand the state of a finding by providing an immutable history of changes within the finding details. By using this feature, you can track the history of each finding, including the before and after values of the fields that were changed, who or what made the changes, and when the changes were made. This simplifies how you operate on a finding by giving you visibility into the changes made to a finding over time, alongside the rest of the finding details, which removes the need for separate tooling or additional processes. This feature is available at no additional cost in AWS Regions where Security Hub is available, and appears by default for new or updated findings. Finding History is also available through the Security Hub APIs.

To try out this new feature, open the Security Hub console, select a finding, and choose the History tab. There you will see a chronological list of changes that have been made to the finding. The transparency of the finding history helps you quickly assess the status of the finding, understand actions already taken, and take the necessary actions to mitigate risk. For example, upon resolving a finding, you can add a note to the finding to indicate why you resolved it. Both the resolved status and note will appear in the history.

In the following example, the finding was updated and then resolved with an explanatory note left by the person that reviewed the finding. With Finding History, you can see the previous updates and events in the finding’s History tab.

Figure 1: Finding History shows recent updates to the finding

Figure 1: Finding History shows recent updates to the finding

In addition, you can still view the current state of the finding in its Details tab.

Figure 2: Finding Details shows the record of a security check or security-related detection

Figure 2: Finding Details shows the record of a security check or security-related detection

Conclusion

With the new Finding History feature in Security Hub, you have greater visibility into the activity and updates on each finding, allowing for more efficient investigation and response to potential security risks. Next time that you start work to investigate and respond to a security finding in Security Hub, begin by checking the finding history.

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.

Nicholas Jaeger

Nicholas Jaeger

Nicholas is a Senior Security Specialist Solutions Architect at AWS. His background includes software engineering, teaching, solutions architecture, and AWS security. Today, he focuses on helping as many customers operate as securely as possible on AWS. Nicholas also hosts AWS Security Activation Days to provide customers with prescriptive guidance while using AWS security services to increase visibility and reduce risk.

Shachar Hirshberg

Shachar Hirshberg

Shachar is a Senior Product Manager at AWS Security Hub with over a decade of experience in building, designing, launching, and scaling top-tier enterprise software products. He is passionate about further improving how customers harness AWS services to enable innovation and enhance the security of their cloud environments. Outside of work, Shachar is an avid traveler and a skiing enthusiast.

Week in Review: Terraform in Service Catalog, AWS Supply Chain, Streaming Response in Lambda, and Amplify Library for Swift – April 10, 2023

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/week-in-review-terraform-in-service-catalog-aws-supply-chain-streaming-response-in-lambda-and-amplify-library-for-swift-april-10-2023/

The AWS Summit season has started. AWS Summits are free technical and business conferences happening in large cities across the planet. This week, we were happy to welcome our customers and partners in Sydney and Paris. In France, 9,973 customers and partners joined us for the day to meet and exchange ideas but also to attend one of the more than 145 technical breakout sessions and the keynote. This is the largest cloud computing event in France, and I can’t resist sharing a picture from the main room during the opening keynote.

AWS Summit Paris keynote

There are AWS Summits on all continents ; you can find the list and the links for registration here https://aws.amazon.com/events/summits. The next on my agenda are listed at the end of this post.

These two Summits did not slow down our services teams. I counted 44 new capabilities since last Monday. Here are the few that caught my attention.

Last Week on AWS

AWS Lambda response streaming – Response streaming is a new invocation pattern that lets functions progressively stream response payloads back to clients. You can use Lambda response payload streaming to send response data to callers as it becomes available. Response streaming also allows you to build functions that return larger payloads and perform long-running operations while reporting incremental progress (within the 15 minutes execution period). My colleague Julian wrote an incredibly detailed blog post to help you to get started.

AWS Supply Chain Now Generally Available – AWS Supply Chain is a cloud application that mitigates risk and lowers costs with unified data and built-in contextual collaboration. It connects to your existing enterprise resource planning (ERP) and supply chain management systems to bring you ML-powered actionable insights into your supply chain.

AWS Service Catalog Supports Terraform Templates – With AWS Service Catalog, you can create, govern, and manage a catalog of infrastructure as code (IaC) templates that are approved for use on AWS. You can now define AWS Service Catalog products and their resources using either AWS CloudFormation or Hashicorp Terraform and choose the tool that better aligns with your processes and expertise.

Amazon S3 enforces two security best practices and brings new visibility into object replication status – As announced on December 13, 2022, Amazon S3 is now deploying two new default bucket security settings by automatically enabling S3 Block Public Access and disabling S3 access control lists (ACLs) for all new S3 buckets. Amazon S3 also adds a new Amazon CloudWatch metric that can be used to diagnose and correct S3 Replication configuration issues more quickly. The OperationFailedReplication metric, available in both the Amazon S3 console and in Amazon CloudWatch, gives you per-minute visibility into the number of objects that did not replicate to the destination bucket for each of your replication rules.

AWS Security Hub launches four security best practices – AWS Security Hub has released 4 new controls for its National Institute of Standards and Technology (NIST) SP 800-53 Rev. 5 standard. These controls conduct fully-automatic security checks against Elastic Load Balancing (ELB), Amazon Elastic Kubernetes Service (Amazon EKS), Amazon Redshift, and Amazon Simple Storage Service (Amazon S3). To use these controls, you should first turn on the NIST standard.

AWS Cloud Operation Competency Partners – AWS Cloud Operations covers five fundamental solution areas: Cloud Governance, Cloud Financial Management, Monitoring and Observability, Compliance and Auditing, and Operations Management. The new competency enables customers to select validated AWS Partners who offer comprehensive solutions with an integrated approach across multiple areas.

Amplify Library for Swift on macOS – Amplify is an open-source, client-side library making it easier to access a cloud backend from your front-end application code. It provides language-specific constructs to abstract low-level details of the cloud API. It helps you to integrate services such as analytics, object storage, REST or GraphQL APIs, user authentication, geolocation and mapping, and push notifications. You can now write beautiful macOS applications that connect to the same cloud backend as their iOS counterparts.

X in Y Jeff started this section a while ago to list the expansion of new services and capabilities to additional Regions. I noticed 11 Regional expansions this week:

Upcoming AWS Events
And to finish this post, I recommend you check your calendars and sign up for these AWS-led events:

Dot Net Developer Day.Net Developer Day – .NET Enterprise Developer Day EMEA 2023 (April 25) is a free, one-day virtual conference providing enterprise developers with the most relevant information to swiftly and efficiently migrate and modernize their .NET applications and workloads on AWS.

AWS re:Inforce 2023 – Now register AWS re:Inforce, in Anaheim, California, June 13–14. AWS Chief Information Security Officer CJ Moses will share the latest innovations in cloud security and what AWS Security is focused on. The breakout sessions will provide real-world examples of how security is embedded into the way businesses operate. To learn more and get the limited discount code to register, see CJ’s blog post of Gain insights and knowledge at AWS re:Inforce 2023 in the AWS Security Blog.

AWS Global Summits – Check your calendars and sign up for the AWS Summit close to where you live or work: Seoul (May 3–4), Berlin and Singapore (May 4), Stockholm (May 11), Hong Kong (May 23), Amsterdam (June 1), London (June 7), Madrid (June 15), and Milano (June 22).

AWS Community Day – Join community-led conferences driven by AWS user group leaders close to your city: Lima (April 15), Helsinki (April 20), Chicago (June 15), Manila (June 29–30), and Munich (September 14). Recently, we have been bringing together AWS user groups from around the world into Meetup Pro accounts. Find your group and its meetups in your city!

You can browse all upcoming AWS-led in-person and virtual events, and developer-focused events such as AWS DevDay.

Stay Informed
That was my selection for this week! To better keep up with all of this news, don’t forget to check out the following resources:

That’s all for this week. Check back next Monday for another Week in Review!

— seb

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Prepare for consolidated controls view and consolidated control findings in AWS Security Hub

Post Syndicated from Priyanka Prakash original https://aws.amazon.com/blogs/security/prepare-for-consolidated-controls-view-and-consolidated-control-findings-in-aws-security-hub/

Currently, AWS Security Hub identifies controls and generates control findings in the context of security standards. Security Hub is aiming to release two new features in the first quarter of 2023 that will decouple controls from standards and streamline how you view and receive control findings.

The new features to be released are consolidated controls view and consolidated control findings. Consolidated controls view will provide you with a comprehensive view within the Security Hub console of your controls across security standards. This feature will also introduce a single unique identifier for each control across security standards.

Consolidated control findings will streamline your control findings. When this feature is turned on, Security Hub will produce a single finding for a security check even when a check is shared across multiple standards. This will reduce finding noise and help you focus on misconfigured resources in your AWS environment.

In this blog post, I’ll summarize the upcoming features, the benefit they bring to your organization, and how you can take advantage of them upon release.

Feature 1: Consolidated controls view

Currently, controls are identified, viewed, and managed in the context of individual security standards. In the Security Hub console, you first have to navigate to a specific standard to see a list of controls for that standard. Within the AWS Foundational Security Best Practices (FSBP) standard, Security Hub identifies controls by the impacted AWS service and a unique number (for example, IAM.1). For other standards, Security Hub includes the standard as part of the control identifier (for example, CIS 1.1 or PCI.AutoScaling.1).

After the release of consolidated controls view, you will be able to see a consolidated list of your controls from a new Controls page in the Security Hub console. Security Hub will also assign controls a consistent security control ID across standards. Following the current naming convention of the AWS FSBP standard, control IDs will include the relevant service and a unique number.

For example, the control AWS Config should be enabled is currently identified as Config.1 in the AWS FSBP standard, CIS 2.5 in the Center for Internet Security (CIS) AWS Foundations Benchmark v1.2.0, CIS 3.5 in the CIS AWS Foundations Benchmark v1.4.0, and PCI.Config.1 in the Payment Card Industry Data Security Standard (PCI DSS). After this release, this control will have a single identifier called Config.1 across standards. The single Controls page and consistent identifier will help you rapidly discover misconfigurations with minimal context-switching.

You’ll be able to enable a control for one or more enabled standards that include the control. You’ll also be able to disable a control for one or more enabled standards. As before, you can enable the standards that apply to your business case.

Changes to control finding fields and values after the release of consolidated controls view

After the release of consolidated controls view, note the following changes to control finding fields and values in the AWS Security Finding Format (ASFF).

ASFF field What changes after consolidated controls view release Example value before consolidated controls view release Example value after consolidated controls view release
Compliance.SecurityControlId A single control ID will apply across standards. ProductFields.ControlId will still provide the standards-based control ID. Not applicable (new field) EC2.2
Compliance.AssociatedStandards Will show the standards that a control is enabled for. Not applicable (new field) [{“StandardsId”: “aws-foundational-security-best-practices/v/1.0.0”}]
ProductFields.RecommendationUrl This field will no longer reference a standard. https://docs.aws.amazon.com/console/securityhub/PCI.EC2.2/remediation https://docs.aws.amazon.com/console/securityhub/EC2.2/remediation
Remediation.Recommendation.Text This field will no longer reference a standard. “For directions on how to fix this issue, please consult the AWS Security Hub PCI DSS documentation.” “For instructions on how to fix this issue, see the AWS Security Hub documentation for EC2.2.”
Remediation.Recommendation.Url This field will no longer reference a standard. https://docs.aws.amazon.com/console/securityhub/PCI.EC2.2/remediation https://docs.aws.amazon.com/console/securityhub/EC2.2/remediation

Feature 2: Consolidated control findings

Currently, multiple standards contain separate controls for the same security check. Security Hub generates a separate finding per standard for each related control that is evaluated by the same security check.

After release of the consolidated control findings feature, you’ll be able to unify control findings across standards and reduce finding noise. This, in turn, will help you more quickly investigate and remediate failed findings. When you turn on consolidated control findings, Security Hub will generate a single finding or finding update for each security check of a control, even if the check is shared across multiple standards.

For example, after you turn on the feature, you will receive a single finding for a security check of Config.1 even if you’ve enabled this control for the AWS FSBP standard, CIS AWS Foundations Benchmark v1.2.0, CIS AWS Foundations Benchmark v1.4.0, and PCI DSS. If you don’t turn on consolidated control findings, you will receive four separate findings for a security check of Config.1 if you’ve enabled this control for the AWS FSBP standard, CIS AWS Foundations Benchmark v1.2.0, CIS AWS Foundations Benchmark v1.4.0, and PCI DSS.

Changes to control finding fields and values after turning on consolidated control findings

If you turn on consolidated control findings, note the following changes to control finding fields and values in the ASFF. These changes are in addition to the changes previously described for consolidated controls view.

ASFF field What changes after consolidated controls view release Example value before consolidated controls view release Example value after consolidated controls view release
GeneratorId This field will no longer reference a standard. aws-foundational-security-best-practices/v/1.0.0/Config.1 security-control/Config.1
Title This field will no longer reference a standard. PCI.Config.1 AWS Config should be enabled {
Id This field will no longer reference a standard. arn:aws:securityhub:eu-central-1:123456789012:subscription/pci-dss/v/3.2.1/PCI.IAM.5/finding/ab6d6a26-a156-48f0-9403-115983e5a956 arn:aws:securityhub:eu-central-1:123456789012:security-control/iam.9/finding/ab6d6a26-a156-48f0-9403-115983e5a956
ProductFields.ControlId This field will be removed in favor of a single, standard-agnostic control ID. PCI.EC2.2 Removed. See Compliance.SecurityControlId instead.
ProductFields.RuleId This field will be removed in favor of a single, standard-agnostic control ID. 1.3 Removed. See Compliance.SecurityControlId instead.
Description This field will no longer reference a standard. This PCI DSS control checks whether AWS Config is enabled in the current account and region. This AWS control checks whether AWS Config is enabled in the current account and region.
Severity Security Hub will no longer use the Product field to describe the severity of a finding. “Severity”: {
“Product”: 90,
“Label”: “CRITICAL”,
“Normalized”: 90,
“Original”: “CRITICAL”
},		 “Severity”: {
“Label”: “CRITICAL”,
“Normalized”: 90,
“Original”: “CRITICAL”
},
Types This field will no longer reference a standard. [“Software and Configuration Checks/Industry and Regulatory Standards/PCI-DSS”] [“Software and Configuration Checks/Industry and Regulatory Standards”]
Compliance.RelatedRequirements This field will show related requirements across associated standards. [ “PCI DSS 10.5.2”,
“PCI DSS 11.5”]		 [ “PCI DSS v3.2.1/10.5.2”,
“PCI DSS v3.2.1/11.5”,
“CIS AWS Foundations Benchmark v1.2.0/2.5”]
CreatedAt Format will remain the same, but value will reset when you turn on consolidated control findings. 2022-05-05T08:18:13.138Z 2022-09-25T08:18:13.138Z
FirstObservedAt Format will remain the same, but value will reset when you turn on consolidated control findings. 2022-05-07T08:18:13.138Z 2022-09-28T08:18:13.138Z
ProductFields.RecommendationUrl This field will be replaced by Remediation.Recommendation.Url. https://docs.aws.amazon.com/console/securityhub/EC2.2/remediation Removed. See Remediation.Recommendation.Url instead.
ProductFields.StandardsArn This field will be replaced by Compliance.AssociatedStandards. arn:aws:securityhub:::standards/aws-foundational-security-best-practices/v/1.0.0 Removed. See Compliance.AssociatedStandards instead.
ProductFields.StandardsControlArn This field will be removed because Security Hub will generate one finding for a security check across standards. arn:aws:securityhub:us-east-1:123456789012:control/aws-foundational-security-best-practices/v/1.0.0/Config.1 Removed.
ProductFields.StandardsGuideArn This field will be replaced by Compliance.AssociatedStandards. arn:aws:securityhub:::ruleset/cis-aws-foundations-benchmark/v/1.2.0 Removed. See Compliance.AssociatedStandards instead.
ProductFields.StandardsGuideSubscriptionArn This field will be removed because Security Hub will generate one finding for a security check across standards. arn:aws:securityhub:us-east-2:123456789012:subscription/cis-aws-foundations-benchmark/v/1.2.0 Removed.
ProductFields.StandardsSubscriptionArn This field will be removed because Security Hub will generate one finding for a security check across standards. arn:aws:securityhub:us-east-1:123456789012:subscription/aws-foundational-security-best-practices/v/1.0.0 Removed.
ProductFields.aws/securityhub/FindingId This field will no longer reference a standard. arn:aws:securityhub:us-east-1::product/aws/securityhub/arn:aws:securityhub:us-east-1:123456789012:subscription/aws-foundational-security-best-practices/v/1.0.0/Config.1/finding/751c2173-7372-4e12-8656-a5210dfb1d67 arn:aws:securityhub:us-east-1::product/aws/securityhub/arn:aws:securityhub:us-east-1:123456789012:security-control/Config.1/finding/751c2173-7372-4e12-8656-a5210dfb1d67

New values for customer-provided finding fields after turning on consolidated control findings

When you turn on consolidated control findings, Security Hub will archive the existing findings and generate new findings. To view archived findings, you can visit the Findings page of the Security Hub console with the Record state filter set to ARCHIVED, or use the GetFindings API action. Updates you’ve made to the original finding fields in the Security Hub console or by using the BatchUpdateFindings API action will not be preserved in the new findings (if needed, you can recover this data by referring to the archived findings).

Note the following changes to customer-provided control finding fields when you turn on consolidated control findings.

Customer-provided ASFF field Description of change after turning on consolidated control findings
Confidence Will reset to empty state.
Criticality Will reset to empty state.
Note Will reset to empty state.
RelatedFindings Will reset to empty state.
Severity The default severity of the finding (matches the severity of the control).
Types Will reset to standard-agnostic value.
UserDefinedFields Will reset to empty state.
VerificationState Will reset to empty state.
Workflow New failed findings will have a default value of NEW. New passed findings will have a default value of RESOLVED.

How to turn consolidated control findings on and off

Follow these instructions to turn consolidated control findings on and off.

New accounts

If you enable Security Hub for an AWS account for the first time on or after the time when consolidated control findings is released, by default consolidated control findings will be turned on for your account. You can turn it off at any time. However, we recommend keeping it turned on to minimize finding noise.

If you use the Security Hub integration with AWS Organizations, consolidated control findings will be turned on for new member accounts if the administrator account has turned on the feature. If the administrator account has turned it off, it will be turned off for new subordinate AWS accounts (member accounts) as well.

Existing accounts

If your Security Hub account already existed before consolidated control findings is released, your account will have consolidated control findings turned off by default. You can turn it on at any time. We recommend turning it on to minimize finding noise. If you use AWS Organizations, consolidated control findings will be turned on or off for existing member accounts based on the settings of the administrator account.

To turn consolidated control findings on and off (Security Hub console)

  1. In the navigation pane, choose Settings.
  2. Choose the General tab.
  3. For Controls, turn on Consolidated control findings. Turn it off to receive multiple findings for each standard.
  4. Choose Save.

To turn consolidated control findings on and off (Security Hub API)

  • Run the UpdateSecurityHubConfiguration API action. Use the new ControlFindingGenerator attribute to change whether an account uses consolidated control findings:
    • To turn on consolidated control findings, set ControlFindingGenerator equal to SECURITY_CONTROL.
    • To turn it off, set ControlFindingGenerator equal to STANDARD_CONTROL.

To turn consolidated control findings on and off (AWS CLI)

  • In the AWS CLI, run the update-security-hub-configuration command. Use the new control-finding-generator attribute to change whether an account uses consolidated control findings:
    • To turn on consolidated control findings, set control-finding-generator equal to SECURITY_CONTROL.
    • To turn it off, set control-finding-generator equal to STANDARD_CONTROL.

API permissions for consolidated control findings

You’ll need AWS Identity and Access Management (IAM) permissions for the following new API operations in order for consolidated control findings to work as expected:

  • BatchGetSecurityControls – Returns account and Region-specific data about a batch of controls.
  • ListSecurityControlDefinitions – Returns information about controls that apply to a specified standard.
  • ListStandardsControlAssociations – Identifies whether a control is currently associated with or dissociated from each enabled standard.
  • BatchGetStandardsControlAssociations – For a batch of controls, identifies whether each control is currently associated with or dissociated from a specified standard.
  • BatchUpdateStandardsControlAssociations – Used to associate a control with enabled standards that include the control, or to dissociate a control from enabled standards. This is a batch substitute for the UpdateStandardsControl API action if an administrator doesn’t want to allow member accounts to associate or dissociate controls.
  • BatchGetControlEvaluations (private API) – Retrieves the enablement and compliance status of a control, the findings count for a control, and the overall security score for controls.

How to prepare for control finding field and value changes

If your workflows don’t rely on the specific format of any control finding fields, no action is required to prepare for the feature releases. We recommend that you immediately turn on consolidated control findings.

Consider waiting to turn on consolidated control findings if you currently rely on the Automated Security Response on AWS solution for predefined response and remediation actions. That solution does not yet support consolidated control findings. If you turn consolidated control findings on now, actions you deployed using the Automated Security Response solution will no longer work.

If you rely on the specific format of any control finding fields (for example, for custom automation), carefully review the upcoming finding field and value changes to ensure that your workflows will continue to function as intended. Note that the changes noted in the first table in this post might impact you if you rely on the specified control finding fields and values.

The changes noted in the second table and third table in this post will only impact you if you turn on consolidated control findings. For example, if you rely on ProductFields.ControlId, GeneratorId, or Title, you’ll be impacted if you turn on consolidated control findings. As another example, if you’ve created an Amazon CloudWatch Events rule that initiates an action for a specific control ID (such as invoking an AWS Lambda function if the control ID equals CIS 2.7), you’ll need to update the rule to use CloudTrail.2, the new Compliance.SecurityControlId field for that control.

If you’ve created custom insights by using the control finding fields or values that will change (see previous tables), we recommend updating those insights to use the new fields or values.

Conclusion

This post covered the control finding fields and values that will change in Security Hub after release of the consolidated controls view and consolidated control findings features. We recommend that you carefully review the changes and update your workflows to start using the new fields and values as soon as the features become available.

For more information about the upcoming changes, see the Security Hub user guide, which includes value changes for GeneratorId , control title changes, and sample control findings before and after the upcoming feature releases.

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

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Author

Priyanka Prakash

Priyanka is a technical writer for AWS Security Hub. She enjoys helping customers understand how to effectively monitor their environment and address security issues. Prior to joining AWS, Priyanka worked for a cloud monitoring startup. In her personal time, Priyanka enjoys cooking and hiking.

How to use Amazon Macie to preview sensitive data in S3 buckets

Post Syndicated from Koulick Ghosh original https://aws.amazon.com/blogs/security/how-to-use-amazon-macie-to-preview-sensitive-data-in-s3-buckets/

Security teams use Amazon Macie to discover and protect sensitive data, such as names, payment card data, and AWS credentials, in Amazon Simple Storage Service (Amazon S3). When Macie discovers sensitive data, these teams will want to see examples of the actual sensitive data found. Reviewing a sampling of the discovered data helps them quickly confirm that the object is truly sensitive according to their data protection and privacy policies.

In this post, we walk you through how your data security teams are able to use a new capability in Amazon Macie to retrieve up to 10 examples of sensitive data found in your S3 objects, so that you are able to confirm the nature of the data at a glance. Additionally, we will discuss how you are able to control who is able to use this capability, so that only authorized personnel have permissions to view these examples.

The challenge customers face

After a Macie sensitive data discovery job is run, security teams start their work. The security team will review the Macie findings to investigate the discovered sensitive data and decide what actions to take to protect such data. The findings provide details that include the severity of the finding, information on the affected S3 object, and a summary of the type, location, and amount of sensitive data found. However, Macie findings only contain pointers to data that Macie found in the object. In order to complete their investigation, customers in the past had to do additional work to extract the contents of a sensitive object, such as navigating to a different AWS account where the object is located, downloading and manually searching for keywords in a file editor, or writing and refining SQL queries by using Amazon S3 Select. The investigations are further slowed down when the object type is one that is not easily readable without additional tooling, such as big-data file types like Avro and Parquet. By using the Macie capability to retrieve sensitive data samples, you are able to review the discovered data and make decisions concerning the finding remediation.

Prerequisites

To implement the ability to retrieve and reveal samples of sensitive data, you’ll need the following prerequisites:

  • Enable Amazon Macie in your AWS account. For instructions, see Getting started with Amazon Macie.
  • Set your account as the delegated Macie administrator account and enable Macie in at least one member account by using AWS Organizations. In this post, we will refer to the delegated administrator account as Account A and the member account as Account B.
  • Configure Macie detailed classification results in Account A.

    Note: The detailed classification results contain a record for each Amazon S3 object that you configure the job to analyze, and include the location of up to 1,000 occurrences of each type of sensitive data that Macie found in an object. Macie uses the location information in the detailed classification results to retrieve the examples of sensitive data. The detailed classification results are stored in an S3 bucket of your choice. In this post, we will refer to this bucket as DOC-EXAMPLE-BUCKET1.

  • Create an S3 bucket that contains sensitive data in Account B. In this post, we will refer to this bucket as DOC-EXAMPLE-BUCKET2.

    Note: You should enable server-side encryption on this bucket by using customer managed AWS Key Management Service (AWS KMS) keys (a type of encryption known as SSE-KMS).

  • (Optional) Add sensitive data to DOC-EXAMPLE-BUCKET2. This post uses a sample dataset that contains fake sensitive data. You are able to download this sample dataset, unarchive the .zip folder, and follow these steps to upload the objects to S3. This is a synthetic dataset generated by AWS that we will use for the examples in this post. All data in this blog post has been artificially created by AWS for demonstration purposes and has not been collected from any individual person. Similarly, such data does not relate back to any individual person, nor is it intended to.
  • Create and run a sensitive data discovery job from Account A to analyze the contents of DOC-EXAMPLE-BUCKET2.
  • (Optional) Set up the AWS Command Line Interface (AWS CLI).

Configure Macie to retrieve and reveal examples of sensitive data

In this section, we’ll describe how to configure Macie so that you are able to retrieve and view examples of sensitive data from Macie findings.

To configure Macie (console)

  • In the AWS Management Console, in the Macie delegated administrator account (Account A), follow these steps from the Amazon Macie User Guide.

To configure Macie (AWS CLI)

  1. Confirm that you have Macie enabled. 
    	$ aws macie2 get-macie-session --query 'status'
	// The expected response is "ENABLED"

  2. Confirm that you have configured the detailed classification results bucket. 
    	$ aws macie2 get-classification-export-configuration

	// The expected response is:
	{
   	 "configuration": {
   		 	    "s3Destination": {
        		    "bucketName": " DOC-EXAMPLE-BUCKET1 ",
           			"kmsKeyArn": "arn:aws:kms:<YOUR-REGION>:<YOUR-ACCOUNT-ID>:key/<KEY-USED-TO-ENCRYPT-DOC-EXAMPLE-BUCKET1>"
     		  	 }
		}	
	}

  3. Create a new KMS key to encrypt the retrieved examples of sensitive data. Make sure that the key is created in the same AWS Region where you are operating Macie. 
    $ aws kms create-key
{
    "KeyMetadata": {
        "Origin": "AWS_KMS",
        "KeyId": "<YOUR-KEY-ID>",
        "Description": "",
        "KeyManager": "CUSTOMER",
        "Enabled": true,
        "KeySpec": "SYMMETRIC_DEFAULT",
        "CustomerMasterKeySpec": "SYMMETRIC_DEFAULT",
        "KeyUsage": "ENCRYPT_DECRYPT",
        "KeyState": "Enabled",
        "CreationDate": 1502910355.475,
        "Arn": "arn:aws:kms: <YOUR-AWS-REGION>:<AWS-ACCOUNT-A>:key/<YOUR-KEY-ID>",
        "AWSAccountId": "<AWS-ACCOUNT-A>",
        "MultiRegion": false
        "EncryptionAlgorithms": [
            "SYMMETRIC_DEFAULT"
        ],
    }
}

  4. Give this key the alias REVEAL-KMS-KEY. 
    $ aws kms CreateAlias
{
   "AliasName": " <REVEAL-KMS-KEY> ",
   "TargetKeyId": "<YOUR-KEY-ID>"
}

  5. Enable the feature in Macie and configure it to encrypt the data by using REVEAL-KMS-KEY. You do not specify a key policy for your new KMS key in this step. The key policy will be discussed later in the post. 
    $ aws macie2 update-reveal-configuration --configuration '{"status":"ENABLED","kmsKeyId":"alias/ <REVEAL-KMS-KEY> "}'

// The expected response is:
{
    "configuration": {
        "kmsKeyId": "arn:aws:kms:<YOUR-REGION>: <YOUR ACCOUNT ID>:key/<REVEAL-KMS-KEY>.",
        "status": "ENABLED"
    }
}

Control access to read sensitive data and protect data displayed in Macie

This new Macie capability uses the AWS Identity and Access Management (IAM) policies, S3 bucket policies, and AWS KMS key policies that you have defined in your accounts. This means that in order to see examples through the Macie console or by invoking the Macie API, the IAM principal needs to have read access to the S3 object and to decrypt the object if it is server-side encrypted. It’s important to note that Macie uses the IAM permissions of the AWS principal to locate, retrieve, and reveal the samples and does not use the Macie service-linked role to perform these tasks.

Using the setup discussed in the previous section, you will walk through how to control access to the ability to retrieve and reveal sensitive data examples. To recap, you created and ran a discovery job from the Amazon Macie delegated administrator account (Account A) to analyze the contents of DOC-EXAMPLE-BUCKET2 in a member account (Account B). You configured Macie to retrieve examples and to encrypt the examples of sensitive data with the REVEAL-KMS-KEY.

The next step is to create and use an IAM role that will be assumed by other users in Account A to retrieve and reveal examples of sensitive data discovered by Macie. In this post, we’ll refer to this role as MACIE-REVEAL-ROLE.

To apply the principle of least privilege and allow only authorized personnel to view the sensitive data samples, grant the following permissions so that Macie users who assume MACIE-REVEAL-ROLE will be able to successfully retrieve and reveal examples of sensitive data:

  • Step 1 – Update the IAM policy for MACIE-REVEAL-ROLE.
  • Step 2 – Update the KMS key policy for REVEAL-KMS-KEY.
  • Step 3 – Update the S3 bucket policy for DOC-EXAMPLE-BUCKET2 and the KMS key policy used for its server-side encryption in Account B.

After you grant these permissions, MACIE-REVEAL-ROLE is succcesfully able to retrieve and reveal examples of sensitive data in DOC-EXAMPLE-BUCKET2, as shown in Figure 1.

Figure 1: Macie runs the discovery job from the delegated administrator account in a member account, and MACIE-REVEAL-ROLE retrieves examples of sensitive data

Figure 1: Macie runs the discovery job from the delegated administrator account in a member account, and MACIE-REVEAL-ROLE retrieves examples of sensitive data

Step 1: Update the IAM policy

Provide the following required permissions to MACIE-REVEAL-ROLE:

  1. Allow GetObject from DOC-EXAMPLE-BUCKET2 in Account B.
  2. Allow decryption of DOC-EXAMPLE-BUCKET2 if it is server-side encrypted with a customer managed key (SSE-KMS).
  3. Allow GetObject from DOC-EXAMPLE-BUCKET1.
  4. Allow decryption of the Macie discovery results.
  5. Allow the necessary Macie actions to retrieve and reveal sensitive data examples.

To set up the required permissions

  • Use the following commands to provide the permissions. Make sure to replace the placeholders with your own data. 
    {
    "Version": "2012-10-17",
    "Statement": [
	{
            "Sid": "AllowGetFromCompanyDataBucket",
            "Effect": "Allow",
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::<DOC-EXAMPLE-BUCKET2>/*"
        },
        {
            "Sid": "AllowKMSDecryptForCompanyDataBucket",
            "Effect": "Allow",
            "Action": [
                "kms:Decrypt"
            ],
            "Resource": "arn:aws:kms:<AWS-Region>:<AWS-Account-B>:key/<KEY-USED-TO-ENCRYPT-DOC-EXAMPLE-BUCKET2>"
        },
        {
            "Sid": "AllowGetObjectfromMacieResultsBucket",
            "Effect": "Allow",
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::<DOC-EXAMPLE-BUCKET1>/*"
        },
	{
            "Sid": "AllowKMSDecryptForMacieRoleDiscoveryBucket",
            "Effect": "Allow",
            "Action": [
                "kms:Decrypt"
            ],
            "Resource": "arn:aws:kms:<AWS-REGION>:<AWS-ACCOUNT-A>:key/<KEY-USED-TO-ENCRYPT-DOC-EXAMPLE-BUCKET1>"
        },
	{
            "Sid": "AllowActionsRetrieveAndReveal",
            "Effect": "Allow",
            "Action": [
                "macie2:GetMacieSession",
                "macie2:GetFindings",
                "macie2:GetSensitiveDataOccurrencesAvailability",
                "macie2:GetSensitiveDataOccurrences",
                "macie2:ListFindingsFilters",
                "macie2:GetBucketStatistics",
                "macie2:ListMembers",
                "macie2:ListFindings",
                "macie2:GetFindingStatistics",
                "macie2:GetAdministratorAccount",
                "macie2:GetClassificationExportConfiguration",
                "macie2:GetRevealConfiguration",
                "macie2:DescribeBuckets"
            ],
            "Resource": "*” 
        }
    ]
}

Step 2: Update the KMS key policy

Next, update the KMS key policy that is used to encrypt sensitive data samples that you retrieve and reveal in your delegated administrator account.

To update the key policy

  • Allow the MACIE-REVEAL-ROLE access to the KMS key that you created for protecting the retrieved sensitive data, using the following commands. Make sure to replace the placeholders with your own data. 
    	{
            "Sid": "AllowMacieRoleDecrypt",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam:<AWS-REGION>:<AWS-ACCOUNT-A>:role/<MACIE-REVEAL-ROLE>"
            },
            "Action": [
                "kms:Decrypt",
                "kms:DescribeKey",
                "kms:GenerateDataKey"
            ],
            "Resource": "arn:aws:kms:<AWS-REGION>:<AWS-ACCOUNT-A>:key/<REVEAL-KMS-KEY>"
        }

Step 3: Update the bucket policy of the S3 bucket

Finally, update the bucket policy of the S3 bucket in member accounts, and update the key policy of the key used for SSE-KMS.

To update the S3 bucket policy and KMS key policy

  1. Use the following commands to update key policy for the KMS key used for server-side encryption of the DOC-EXAMPLE-BUCKET2 bucket in Account B. 
    	{
            "Sid": "AllowMacieRoleDecrypt”
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam:<AWS-REGION>:<AWS-ACCOUNT-A>:role/<MACIE-REVEAL-ROLE>"
            },
            "Action": "kms:Decrypt",
            "Resource": "arn:aws:kms:<AWS-REGION>:<AWS-ACCOUNT-B>:key/<KEY-USED-TO-ENCRYPT-DOC-EXAMPLE-BUCKET2>"
  }

  2. Use the following commands to update the bucket policy of DOC-EXAMPLE-BUCKET2 to allow cross-account access for MACIE-REVEAL-ROLE to get objects from this bucket. 
    {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowMacieRoleGet",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam::<AWS-ACCOUNT-A>:role/<MACIE-REVEAL-ROLE>"
            },
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::<DOC-EXAMPLE-BUCKET2>/*"
        }
    ]
}

Retrieve and reveal sensitive data samples

Now that you’ve put in place the necessary permissions, users who assume MACIE-REVEAL-ROLE will be able to conveniently retrieve and reveal sensitive data samples.

To retrieve and reveal sensitive data samples

  1. In the Macie console, in the left navigation pane, choose Findings, and select a specific finding. Under Sensitive Data, choose Review.
    Figure 2: The finding details panel

    Figure 2: The finding details panel

  2. On the Reveal sensitive data page, choose Reveal samples.
    Figure 3: The Reveal sensitive data page

    Figure 3: The Reveal sensitive data page

  3. Under Sensitive data, you will be able to view up to 10 examples of the sensitive data found by Amazon Macie.
    Figure 4: Examples of sensitive data revealed in the Amazon Macie console

    Figure 4: Examples of sensitive data revealed in the Amazon Macie console

You are able to find additional information on setting up the Macie Reveal function in the Amazon Macie User Guide.

Conclusion

In this post, we showed how you are to retrieve and review examples of sensitive data that were found in Amazon S3 using Amazon Macie. This capability will make it easier for your data protection teams to review the sensitive contents found in S3 buckets across the accounts in your AWS environment. With this information, security teams are able to quickly take remediation actions, such as updating the configuration of sensitive buckets, quarantining files with sensitive information, or sending a notification to the owner of the account where the sensitive data resides. In certain cases, you are able to add the examples to an allow list in Macie if you don’t want Macie to report those as sensitive data (for example, corporate addresses or sample data that is used for testing).

The following are links to additional resources that you will be able to use to expand your knowledge of Amazon Macie capabilities and features:

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 Amazon Macie re:Post.

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Koulick Ghosh

Koulick Ghosh

Koulick is a Senior Product Manager in AWS Security based in Seattle, WA. He loves speaking with customers on how AWS Security services can help make them more secure. In his free-time, he enjoys playing the guitar, reading, and exploring the Pacific Northwest.

Author

Michael Ingoldby

Michael is a Senior Security Solutions Architect at AWS based in Frisco, Texas. He provides guidance and helps customers to implement AWS native security services. Michael has been working in the security domain since 2006. When he is not working, he enjoys spending time outdoors.

Robert Wu

Robert Wu

Robert is the Software Development Engineer for AWS Macie, working on enabling customers with more sensitive data discovery capabilities. In his free time, he enjoys exploring and contributing to various open-source projects to widen his domain knowledge.

New for AWS Control Tower – Comprehensive Controls Management (Preview)

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/new-for-aws-control-tower-comprehensive-controls-management-preview/

Today, customers in regulated industries face the challenge of defining and enforcing controls needed to meet compliance and security requirements while empowering engineers to make their design choices. In addition to addressing risk, reliability, performance, and resiliency requirements, organizations may also need to comply with frameworks and standards such as PCI DSS and NIST 800-53.

Building controls that account for service relationships and their dependencies is time-consuming and expensive. Sometimes customers restrict engineering access to AWS services and features until their cloud architects identify risks and implement their own controls.

To make that easier, today we are launching comprehensive controls management in AWS Control Tower. You can use it to apply managed preventative, detective, and proactive controls to accounts and organizational units (OUs) by service, control objective, or compliance framework. AWS Control Tower does the mapping between them on your behalf, saving time and effort.

With this new capability, you can now also use AWS Control Tower to turn on AWS Security Hub detective controls across all accounts in an OU. In this way, Security Hub controls are enabled in every AWS Region that AWS Control Tower governs.

Let’s see how this works in practice.

Using AWS Control Tower Comprehensive Controls Management
In the AWS Control Tower console, there is a new Controls library section. There, I choose All controls. There are now more than three hundred controls available. For each control, I see which AWS service it is related to, the control objective this control is part of, the implementation (such as AWS Config rule or AWS CloudFormation Guard rule), the behavior (preventive, detective, or proactive), and the frameworks it maps to (such as NIST 800-53 or PCI DSS).

Console screenshot.

In the Find controls search box, I look for a preventive control called CT.CLOUDFORMATION.PR.1. This control uses a service control policy (SCP) to protect controls that use CloudFormation hooks and is required by the control that I want to turn on next. Then, I choose Enable control.

Console screenshot.

Then, I select the OU for which I want to enable this control.

Console screenshot.

Now that I have set up this control, let’s see how controls are presented in the console in categories. I choose Categories in the navigation pane. There, I can browse controls grouped as Frameworks, Services, and Control objectives. By default, the Frameworks tab is selected.

Console screenshot.

I select a framework (for example, PCI DSS version 3.2.1) to see all the related controls and control objectives. To implement a control, I can select the control from the list and choose Enable control.

Console screenshot.

I can also manage controls by AWS service. When I select the Services tab, I see a list of AWS services and the related control objectives and controls.

Console screenshot.

I choose Amazon DynamoDB to see the controls that I can turn on for this service.

Console screenshot.

I select the Control objectives tab. When I need to assess a control objective, this is where I have access to the list of related controls to turn on.

Console screenshot.

I choose Encrypt data at rest to see and search through the available controls for that control objective. I can also check which services are covered in this specific case. I type RDS in the search bar to find the controls related to Amazon Relational Database Service (RDS) for this control objective.

I choose CT.RDS.PR.16 – Require an Amazon RDS database cluster to have encryption at rest configured and then Enable control.

Console screenshot.

I select the OU for which I want to enable the control for, and I proceed. All the AWS accounts in this organization’s OU will have this control enabled in all the Regions that AWS Control Tower governs.

Console screenshot.

After a few minutes, the AWS Control Tower setup is updated. Now, the accounts in this OU have proactive control CT.RDS.PR.16 turned on. When an account in this OU deploys a CloudFormation stack, any Amazon RDS database cluster has to have encryption at rest configured. Because this control is proactive, it’ll be checked by a CloudFormation hook before the deployment starts. This saves a lot of time compared to a detective control that would find the issue only when the CloudFormation deployment is in progress or has terminated. This also improves my security posture by preventing something that’s not allowed as opposed to reacting to it after the fact.

Availability and Pricing
Comprehensive controls management is available in preview today in all AWS Regions where AWS Control Tower is offered. These enhanced control capabilities reduce the time it takes you to vet AWS services from months or weeks to minutes. They help you use AWS by undertaking the heavy burden of defining, mapping, and managing the controls required to meet the most common control objectives and regulations.

There is no additional charge to use these new capabilities during the preview. However, when you set up AWS Control Tower, you will begin to incur costs for AWS services configured to set up your landing zone and mandatory controls. For more information, see AWS Control Tower pricing.

Simplify how you implement compliance and security requirements with AWS Control Tower.

— Danilo