Connect Microsoft Sentinel to Amazon Web Services to ingest AWS service log data
Use the Amazon Web Services (AWS) connectors to pull AWS service logs into Microsoft Sentinel. These connectors work by granting Microsoft Sentinel access to your AWS resource logs. Setting up the connector establishes a trust relationship between Amazon Web Services and Microsoft Sentinel. This is accomplished on AWS by creating a role that gives permission to Microsoft Sentinel to access your AWS logs.
This connector is available in two versions: the legacy connector for CloudTrail management and data logs, and the new version that can ingest logs from the following AWS services by pulling them from an S3 bucket:
- Amazon Virtual Private Cloud (VPC) - VPC Flow Logs
- Amazon GuardDuty - Findings
- AWS CloudTrail - Management and data events
- AWS CloudWatch - CloudWatch logs
This article explains how to configure the new AWS S3 connector. The process of setting it up has two parts: the AWS side and the Microsoft Sentinel side.
Make sure that the logs from your selected AWS service use the format accepted by Microsoft Sentinel:
- Amazon VPC: .csv file in GZIP format with headers; delimiter: space.
- Amazon GuardDuty: json-line and GZIP formats.
- AWS CloudTrail: .json file in a GZIP format.
- CloudWatch: .csv file in a GZIP format without a header. If you need to convert your logs to this format, you can use this CloudWatch lambda function.
Connect the S3 connector
In your AWS environment:
Configure your AWS service(s) to send logs to an S3 bucket.
Create a Simple Queue Service (SQS) queue to provide notification.
Create an assumed role to grant permissions to your Microsoft Sentinel account (external ID) to access your AWS resources.
Attach the appropriate IAM permissions policies to grant Microsoft Sentinel access to the appropriate resources (S3 bucket, SQS).
In Microsoft Sentinel:
- Enable and configure the AWS S3 Connector in the Microsoft Sentinel portal. See the instructions below.
Each side's process produces information used by the other side. This sharing creates secure communication.
We have made available, in our GitHub repository, a script that automates the AWS side of this process. See the instructions for automatic setup later in this document.
This graphic and the following text show how the parts of this connector solution interact.
AWS services are configured to send their logs to S3 (Simple Storage Service) storage buckets.
The S3 bucket sends notification messages to the SQS (Simple Queue Service) message queue whenever it receives new logs.
The Microsoft Sentinel AWS S3 connector polls the SQS queue at regular, frequent intervals. If there is a message in the queue, it will contain the path to the log files.
The connector reads the message with the path, then fetches the files from the S3 bucket.
To connect to the SQS queue and the S3 bucket, Microsoft Sentinel uses AWS credentials and connection information embedded in the AWS S3 connector's configuration. The AWS credentials are configured with a role and a permissions policy giving them access to those resources. Similarly, the Microsoft Sentinel workspace ID is embedded in the AWS configuration, so there is in effect two-way authentication.
You must have write permission on your Microsoft Sentinel workspace.
To simplify the onboarding process, Microsoft Sentinel has provided a PowerShell script to automate the setup of the AWS side of the connector - the required AWS resources, credentials, and permissions.
The script takes the following actions:
Creates an IAM assumed role with the minimal necessary permissions, to grant Microsoft Sentinel access to your logs in a given S3 bucket and SQS queue.
Enables specified AWS services to send logs to that S3 bucket, and notification messages to that SQS queue.
If necessary, creates that S3 bucket and that SQS queue for this purpose.
Configures any necessary IAM permissions policies and applies them to the IAM role created above.
You must have PowerShell and the AWS CLI on your machine.
To run the script to set up the connector, use the following steps:
From the Microsoft Sentinel navigation menu, select Data connectors.
Select Amazon Web Services S3 from the data connectors gallery, and in the details pane, select Open connector page.
In the Configuration section, under 1. Set up your AWS environment, expand Setup with PowerShell script (recommended).
Follow the on-screen instructions to download and extract the AWS S3 Setup Script (link downloads a zip file containing the main setup script and helper scripts) from the connector page.
Before running the script, run the
aws configurecommand from your PowerShell command line, and enter the relevant information as prompted. See AWS Command Line Interface | Configuration basics for details.
Now run the script. Copy the command from the connector page (under "Run script to set up the environment") and paste it in your command line.
The script will prompt you to enter your Workspace ID. This ID appears on the connector page. Copy it and paste it at the prompt of the script.
When the script finishes running, copy the Role ARN and the SQS URL from the script's output (see example in first screenshot below) and paste them in their respective fields in the connector page under 2. Add connection (see second screenshot below).
Select a data type from the Destination table drop-down list. This tells the connector which AWS service's logs this connection is being established to collect, and into which Log Analytics table it will store the ingested data. Then select Add connection.
The script may take up to 30 minutes to finish running.
Microsoft recommends using the automatic setup script to deploy this connector. If for whatever reason you do not want to take advantage of this convenience, follow the steps below to set up the connector manually.
You must have an S3 bucket to which you will ship the logs from your AWS services - VPC, GuardDuty, CloudTrail, or CloudWatch.
- Create an S3 storage bucket in AWS.
You must have an SQS message queue to which the S3 bucket will publish notifications.
- Create a standard Simple Queue Service (SQS) queue in AWS.
The manual setup consists of the following steps:
- Create an AWS assumed role and grant access to the AWS Sentinel account
- Configure an AWS service to export logs to an S3 bucket
- Create a Simple Queue Service (SQS) in AWS
- Enable SQS notification
- Apply IAM permissions policies
Create an AWS assumed role and grant access to the AWS Sentinel account
In Microsoft Sentinel, select Data connectors and then select the Amazon Web Services S3 line in the table and in the AWS pane to the right, select Open connector page.
Under Configuration, copy the External ID (Workspace ID) and paste it aside.
In your AWS management console, under Security, Identity & Compliance, select IAM.
Choose Roles and select Create role.
Choose Another AWS account. In the Account ID field, enter the number 197857026523 (you can copy and paste it from here). This number is Microsoft Sentinel's service account ID for AWS. It tells AWS that the account using this role is a Microsoft Sentinel user.
Select the Require External ID check box, and then enter the External ID (Workspace ID) that you copied from the AWS connector page in the Microsoft Sentinel portal and pasted aside. Then select Next.
Enter a Role name.
Add Permissions and enter a Tag (optional). Then select Create Role.
Apply IAM permissions policies. For information on these and additional policies that should be applied for ingesting the different types of AWS service logs, see the AWS S3 connector permissions policies page in our GitHub repo.
In the Roles list, select the new role you created.
Copy the Role ARN and paste it aside.
In the AWS SQS dashboard, select the SQS queue you created, and copy the URL of the queue.
In the AWS S3 connector page in the Microsoft Sentinel portal, under 2. Add connection:
- Paste the IAM role ARN you copied two steps ago into the Role ARN field.
- Paste the URL of the SQS queue you copied in the last step into the SQS URL field.
- Select a data type from the Destination table drop-down list. This tells the connector which AWS service's logs this connection is being established to collect, and into which Log Analytics table it will store the ingested data.
- Select Add connection.
Configure an AWS service to export logs to an S3 bucket
Publish a VPC flow log to an S3 bucket.
If you choose to customize the log's format, you must include the start attribute, as it maps to the TimeGenerated field in the Log Analytics workspace. Otherwise, the TimeGenerated field will be populated with the event's ingested time, which doesn't accurately describe the log event.
Export your GuardDuty findings to an S3 bucket.
The TimeGenerated field is populated with the finding's Update at value.
AWS CloudTrail trails are stored in S3 buckets by default.
Create a Simple Queue Service (SQS) in AWS
If you haven't yet created an SQS queue, do so now.
Enable SQS notification
Configure your S3 bucket to send notifications to your SQS queue.
Apply IAM permissions policies
Permissions policies that must be applied to the Microsoft Sentinel role you created include the following:
For information on these and additional policies that should be applied for ingesting the different types of AWS service logs, see the AWS S3 connector permissions policies page in our GitHub repo.
Known issues and troubleshooting
Different types of logs can be stored in the same S3 bucket, but should not be stored in the same path.
Each SQS queue should point to one type of message, so if you want to ingest GuardDuty findings and VPC flow logs, you should set up separate queues for each type.
Similarly, a single SQS queue can serve only one path in an S3 bucket, so if for any reason you are storing logs in multiple paths, each path requires its own dedicated SQS queue.
Learn how to troubleshoot Amazon Web Services S3 connector issues.
In this document, you learned how to connect to AWS resources to ingest their logs into Microsoft Sentinel. To learn more about Microsoft Sentinel, see the following articles:
- Learn how to get visibility into your data, and potential threats.
- Get started detecting threats with Microsoft Sentinel.
- Use workbooks to monitor your data.
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