AWS Architecture Blog

Visualize AWS Security Hub Findings using Analytics and Business Intelligence Tools

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details.


To improve the security posture in your organization, you first must have a comprehensive view of your security, operations, and compliance data. AWS Security Hub gives you a thorough view of your security alerts and security posture across all your AWS accounts. This is shown as Security Hub findings, which are generated from different AWS services and partner products. Security Hub also provides the capability to filter, aggregate, and visualize these findings as Security Hub insights.

Organizations have additional requirements to centralize the Security Hub findings into their existing operational store. They also must connect the findings with other operational data. In this blog, we share two architecture design options, which collect Security Hub findings across Regions. You can make these findings searchable, and build multiple visualization dashboards using analytics and BI Tools in order to gain insights.

Some of the benefits of these architectures:

  • Ability to combine Security Hub findings across Regions and generate a single dashboard view
  • Ability to combine the various security and compliance data into a single centralized dashboard
  • Ability to correlate security and compliance findings with operational data. This can be AWS CloudTrail logs and customer logs for deeper analysis and insights
  • Ability to build a security and compliance scorecard across various dimensions. This is achieved by combining the Security Hub findings and AWS resource inventory generated using an enterprise-wide tagging strategy

Approach to visualize Security Hub findings in multi-account environments

There are four steps involved in this approach, as shown in Figure 1:

Figure 1. Steps involved in improving the visibility of AWS Security Hub findings

Figure 1. Steps involved in improving the visibility of AWS Security Hub findings

  1. Set up your AWS Security Hub administrator account. Designate one of the AWS accounts within your AWS Organizations to be a delegated administrator for Security Hub. This account can manage and receive and findings across member accounts.
  2. Enable AWS Security Hub in member accounts. Enable required security standards, AWS native service integration, and partner integrations in all the member accounts across your AWS Regions.
  3. Export and consolidate findings. For each Region you operate in, collect findings and consolidate across Regions by ingesting the findings to a centralized repository.
  4. Query and visualize insights. Query the findings from the centralized findings repository and build dashboards for visualizations.

Design option one: View Security Hub findings using AWS serverless analytics services

This option, shown in Figure 2, uses Amazon Athena, a serverless, interactive, query service that analyzes data in Amazon Simple Storage Service (S3) using standard SQL. AWS Glue, a serverless, data integration service discovers, prepares, and combines data for analytics, machine learning (ML), and application development is also used. Amazon QuickSight, a scalable, serverless, embeddable, ML-powered, business intelligence (BI) service is used to search and visualize Security Hub findings from multiple accounts and Regions.

Figure 2. Architecture to view Security Hub findings using AWS serverless analytics services

Figure 2. Architecture to view Security Hub findings using AWS serverless analytics services

Architecture overview

  • Designate an AWS account in your AWS Organization as a delegated administrator for Security Hub. This account will publish events to Amazon EventBridge for its own findings, in addition to findings received from member accounts.
  • Configure the EventBridge rule to deliver the Security Hub finding event type into Amazon Kinesis Data Firehose. If you are operating in multiple Regions set up an EventBridge rule and Kinesis Data Firehose in each of those Regions.
  • Set up Kinesis Data Firehose in multiple Regions to deliver data into a Single S3 bucket, which helps to consolidate findings across multiple Regions.
  • Partition the data in your S3-based by account number, Region, date, and other preferred parameters.
  • Use AWS Glue to crawl the S3 bucket and build the schema of the Security Hub findings. This is used by Amazon Athena to query the data. You can create a view in Athena to flatten some of the nested attributes in the Security Hub findings.
  • Build your Amazon QuickSight dashboard using the view created in Athena.

Figure 3 shows a sample dashboard created in QuickSight to view consolidated Security Hub findings across accounts and Regions.

Figure 3. Sample Security Hub findings dashboard created using Amazon QuickSight

Figure 3. Sample Security Hub findings dashboard created using Amazon QuickSight

Design option two: View Security Hub findings using a managed Amazon ES cluster and Kibana

This option, shown in Figure 4, uses a managed Amazon Elasticsearch Service cluster to ingest the findings, and Kibana to search and visualize the findings. Amazon Elasticsearch Service is a fully managed service that allows you to deploy, secure, and run Elasticsearch cost-effectively, and at scale.

Figure 4. Architecture to view Security Hub findings using Amazon ES cluster and Kibana

Figure 4. Architecture to view Security Hub findings using Amazon ES cluster and Kibana

Architecture overview

  • Similar to the previous design option, the Security Hub administrator account publishes events to Amazon EventBridge for findings.
  • Configure the EventBridge rule to deliver the Security Hub finding event type into Amazon Kinesis Data Firehose. If you are operating in multiple Regions, then you must set up an EventBridge rule and Kinesis Data Firehose in each of those Regions.
  • It’s recommended that you set up Kinesis Data Firehose in multiple Regions to deliver data into a central Amazon ES cluster. This serves as a single pane of glass for security findings across these different Regions.
  • Use Kibana, a popular open source visualization tool designed to work with Elasticsearch. You’ll be able to create visualizations and dashboards to analyze and share your findings.

Amazon ES can help you configure rules on the findings to send specialized alerts. When coupled with anomaly detection, Amazon ES can automatically detect anomalies in your findings data using unsupervised machine learning algorithm and alert you in near-real.

Figure 5 shows a sample dashboard created in Kibana to view consolidated Security Hub findings across accounts and Regions in an Elasticsearch cluster.

Figure 5. Sample Security Hub findings dashboard created in Kibana

Figure 5. Sample Security Hub findings dashboard created in Kibana

Conclusion

In this post, we showed you two architectural design options to collect AWS Security Hub findings across multiple AWS Regions in a multi-account AWS environment. These approaches allow you to connect the AWS Security Hub findings with other operational data. This makes it searchable, and will allow you to draw insights and achieve an improved organization-wide security posture. These options use AWS managed and serverless services, which are scalable and configurable for high availability and performance. Make your design choice based on your enterprise needs for search, analytics, and insights visualization options.

Further Reading:

Sujatha Kuppuraju

Sujatha Kuppuraju

Sujatha Kuppuraju is a Senior Solutions Architect at Amazon Web Services (AWS). She engages with customers to create innovative solutions that address customer business problems and accelerate the adoption of AWS services.

Muthu Pitchaimani

Muthu Pitchaimani

Muthu Pitchaimani is a Search Specialist. He helps build applications and solutions that need searching for large scale data. Muthu is based out of Austin, Texas.

Christopher Sharkey

Christopher Sharkey

Chris is an Analytics Specialist Solution Architect. He helps build and architect solutions with AWS analytics products. Chris is based out of Boston, MA.

Siva Rajamani

Siva Rajamani

Siva Rajamani is a Boston-based Enterprise Solutions Architect at AWS. He enjoys working closely with customers and supporting their digital transformation and AWS adoption journey. His core areas of focus are Serverless, Application Integration, and Security.