In this blog post, we’ll walk you through deploying a solution to correlate specific AWS Security Hub findings from multiple AWS services that are related to a single AWS resource, which indicates an increased possibility that a security incident has happened.
AWS Security Hub ingests findings from multiple AWS services, including Amazon GuardDuty, Amazon Inspector, Amazon Macie, AWS Firewall Manager, AWS Identity and Access Management (IAM) Access Analyzer, and AWS Systems Manager Patch Manager. Findings from each service are normalized into the AWS Security Finding Format (ASFF), so that you can review findings in a standardized format and take action quickly. You can use AWS Security Hub to provide a single view of all security-related findings, where you can set up alerting, automatic remediation, and ingestion into third-party incident management systems for specific findings.
Although Security Hub can ingest a vast number of integrations and findings, it cannot create correlation rules like a Security Information and Event Management (SIEM) tool can. However, you can create such rules using EventBridge. It’s important to take a closer look when multiple AWS security services generate findings for a single resource, because this potentially indicates elevated risk. Depending on your environment, the initial number of findings in AWS Security Hub findings may be high, so you may need to prioritize which findings require immediate action. AWS Security Hub natively gives you the ability to filter findings by resource, account, and many other details. With the solution in this post, when one of these correlated sets of findings is detected, a new finding is created and pushed to AWS Security Hub by using the Security Hub BatchImportFindings API operation. You can then respond to these new security incident-oriented findings through ticketing, chat, or incident management systems.
This solution requires that you have AWS Security Hub enabled in your AWS account. In addition to AWS Security Hub, the following services must be enabled and integrated to AWS Security Hub:
- Amazon GuardDuty
- Amazon Macie
- Amazon Inspector
- Security Hub AWS Foundational Security Best Practices Standard
In this solution, you will use a combination of AWS Security Hub, Amazon EventBridge, AWS Lambda, and Amazon DynamoDB to ingest and correlate specific findings that indicate a higher likelihood of a security incident. Each correlation is focused on multiple specific AWS security service findings for a single AWS resource.
The following list shows the correlated findings that are detected by this solution. The Description section for each finding correlation provides context for that correlation, the Remediation section provides general recommendations for remediation, and the Prevention/Detection section provides guidance to either prevent or detect one or more findings within the correlation. With the code provided, you can also add more correlations than those listed here by modifying the Cloud Development Kit (CDK) code and AWS Lambda code. The Solution workflow section breaks down the flow of the solution. If you choose to implement automatic remediation, each finding correlation will be created with the following AWS Security Hub Finding Format (ASFF) fields:
These correlated findings are created as part of this solution:
- Any Amazon GuardDuty Backdoor findings and three critical common vulnerabilities and exposures (CVEs) from Amazon Inspector that are associated with the same Amazon Elastic Compute Cloud (Amazon EC2) instance.
- Description: Amazon Inspector has found at least three critical CVEs on the EC2 instance. CVEs indicate that the EC2 instance is currently vulnerable or exposed. The EC2 instance is also performing backdoor activities. The combination of these two findings is a stronger indication of an elevated security incident.
- Remediation: It’s recommended that you isolate the EC2 instance and follow standard protocol to triage the EC2 instance to verify if the instance has been compromised. If the instance has been compromised, follow your standard Incident Response process for post-instance compromise and forensics. Redeploy a backup of the EC2 instance by using an up-to-date hardened Amazon Machine Image (AMI) or apply all security-related patches to the redeployed EC2 instance.
- Prevention/Detection: To mitigate or prevent an Amazon EC2 instance from missing critical security updates, consider using Amazon Systems Manager Patch Manager to automate installing security-related patching for managed instances. Alternatively, you can provide developers up-to-date hardened Amazon Machine Images (AMI) by using Amazon EC2 Image Builder. For detection, you can set the AMI property called ‘DeprecationTime’ to indicate when the AMI will become outdated and respond accordingly.
- An Amazon Macie sensitive data finding and an Amazon GuardDuty S3 exfiltration finding for the same Amazon Simple Storage Service (Amazon S3) bucket.
- Description: Amazon Macie has scanned an Amazon S3 bucket and found a possible match for sensitive data. Amazon GuardDuty has detected a possible exfiltration finding for the same Amazon S3 bucket. The combination of these findings indicates a higher risk security incident.
- Remediation: It’s recommended that you review the source IP and/or IAM principal that is making the S3 object reads against the S3 bucket. If the source IP and/or IAM principal is not authorized to access sensitive data within the S3 bucket, follow your standard Incident Response process for post-compromise plan for S3 exfiltration. For example, you can restrict an IAM principal’s permissions, revoke existing credentials or unauthorized sessions, restricting access via the Amazon S3 bucket policy, or using the Amazon S3 Block Public Access feature.
- Prevention/Detection: To mitigate or prevent exposure of sensitive data within Amazon S3, ensure the Amazon S3 buckets are using least-privilege bucket policies and are not publicly accessible. Alternatively, you can use the Amazon S3 Block Public Access feature. Review your AWS environment to make sure you are following Amazon S3 security best practices. For detection, you can use Amazon Config to track and auto-remediate Amazon S3 buckets that do not have logging and encryption enabled or publicly accessible.
- AWS Security Hub detects an EC2 instance with a public IP and unrestricted VPC Security Group; Amazon GuardDuty unusual network traffic behavior finding; and Amazon GuardDuty brute force finding.
- Description: AWS Security Hub has detected an EC2 instance that has a public IP address attached and a VPC Security Group that allows traffic for ports outside of ports 80 and 443. Amazon GuardDuty has also determined that the EC2 instance has multiple brute force attempts and is communicating with a remote host on an unusual port that the EC2 instance has not previously used for network communication. The correlation of these lower-severity findings indicates a higher-severity security incident.
- Remediation: It’s recommended that you isolate the EC2 instance and follow standard protocol to triage the EC2 instance to verify if the instance has been compromised. If the instance has been compromised, follow your standard Incident Response process for post-instance compromise and forensics.
- Prevention/Detection: To mitigate or prevent these events from occurring within your AWS environment, determine whether the EC2 instance requires a public-facing IP address and review the VPC Security Group(s) has only the required rules configured. Review your AWS environment to make sure you are following Amazon EC2 best practices. For detection, consider implementing AWS Firewall Manager to continuously audit and limit VPC Security Groups.
The solution workflow, shown in Figure 1, is as follows:
- Security Hub ingests findings from integrated AWS security services.
- An EventBridge rule is invoked based on Security Hub findings in GuardDuty, Macie, Amazon Inspector, and Security Hub security standards.
- The EventBridge rule invokes a Lambda function to store the Security Hub finding, which is passed via EventBridge, in a DynamoDB table for further analysis.
- After the new findings are stored in DynamoDB, another Lambda function is invoked by using Dynamo StreamSets and a time-to-live (TTL) set to delete finding entries that are older than 30 days.
- The second Lambda function looks at the resource associated with the new finding entry in the DynamoDB table. The Lambda function checks for specific Security Hub findings that are associated with the same resource.
You can deploy the solution through either the AWS Management Console or the AWS Cloud Development Kit (AWS CDK).
To deploy the solution by using the AWS Management Console
In your account, launch the AWS CloudFormation template by choosing the following Launch Stack button. It will take approximately 10 minutes for the CloudFormation stack to complete.
To deploy the solution by using the AWS CDK
You can find the latest code in the aws-security GitHub repository where you can also contribute to the sample code. The following commands show how to deploy the solution by using the AWS CDK. First, the CDK initializes your environment and uploads the AWS Lambda assets to Amazon S3. Then, you can deploy the solution to your account. For <INSERT_AWS_ACCOUNT>, specify the account number, and for <INSERT_REGION>, specify the AWS Region that you want the solution deployed to.
In this blog post, we walked through a solution to use AWS services, including Amazon EventBridge, AWS Lambda, and Amazon DynamoDB, to correlate AWS Security Hub findings from multiple different AWS security services. The solution provides a framework to prioritize specific sets of findings that indicate a higher likelihood that a security incident has occurred, so that you can prioritize and improve your security response.
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