AWS UpdateLoginProfile
Description
This search looks for AWS CloudTrail events where a user A who has already permission to update login profile, makes an API call to update login profile for another user B . Attackers have been know to use this technique for Privilege Escalation in case new victim(user B) has more permissions than old victim(user B)
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-03-03
- Author: Bhavin Patel, Splunk
- ID: 2a9b80d3-6a40-4115-11ad-212bf3d0d111
Annotations
ATT&CK
Kill Chain Phase
- Installation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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`cloudtrail` eventName = UpdateLoginProfile userAgent !=console.amazonaws.com errorCode = success
| eval match=if(match(userIdentity.userName,requestParameters.userName), 1,0)
| search match=0
| stats count min(_time) as firstTime max(_time) as lastTime by requestParameters.userName src eventName eventSource aws_account_id errorCode userAgent eventID awsRegion userIdentity.userName user_arn
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `aws_updateloginprofile_filter`
Macros
The SPL above uses the following Macros:
aws_updateloginprofile_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- eventName
- userAgent
- errorCode
- requestParameters.userName
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
While this search has no known false positives, it is possible that an AWS admin has legitimately created keys for another user.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
30.0 | 50 | 60 | From IP address $sourceIPAddress$, user agent $userAgent$ has trigged an event $eventName$ for updating the existing login profile, potentially giving user $user_arn$ more access privilleges |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
- https://bishopfox.com/blog/privilege-escalation-in-aws
- https://rhinosecuritylabs.com/aws/aws-privilege-escalation-methods-mitigation-part-2/
Test Dataset
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: 3