AWS Exfiltration via Batch Service
This search looks for events where AWS Batch Service is used for creating a job that could potentially abuse the AWS Bucket Replication feature on S3 buckets. This AWS service can used to transfer data between different AWS S3 buckets and an attacker can leverage this to exfiltrate data by creating a malicious batch job.
- Type: TTP
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2023-04-24
- ID: 04455dd3-ced7-480f-b8e6-5469b99e98e2
Kill Chain Phase
- CIS 10
1 2 3 4 5 `cloudtrail` eventName = JobCreated | stats count min(_time) as firstTime max(_time) as lastTime values(serviceEventDetails.jobArn) as job_arn values(serviceEventDetails.status) as status by src_ip aws_account_id eventName errorCode userAgent | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `aws_exfiltration_via_datasync_task_filter`
The SPL above uses the following Macros:
aws_exfiltration_via_batch_service_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
You must install splunk AWS add on and Splunk App for AWS. This search works with AWS CloudTrail logs.
Known False Positives
It is possible that an AWS Administrator or a user has legitimately created this job for some tasks.
Associated Analytic Story
|64.0||80||80||AWS Batch Job is created on account id - $aws_account_id$ by user $user_arn$ from src_ip $src_ip$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Replay any dataset to Splunk Enterprise by using our
replay.py tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1