Splunk User Enumeration Attempt
Description
On May 3rd, 2022, Splunk published a security advisory for username enumeration stemming from verbose login failure messages present on some REST endpoints. This detection will alert on attempted exploitation in patched versions of Splunk as well as actual exploitation in unpatched version of Splunk.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-04-29
- Author: Lou Stella, Splunk
- ID: 25625cb4-1c4d-4463-b0f9-7cb462699cde
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
- Installation
- Delivery
NIST
- DE.CM
CIS20
- CIS 10
CVE
ID | Summary | CVSS |
---|---|---|
CVE-2021-33845 | The Splunk Enterprise REST API allows enumeration of usernames via the lockout error message. The potential vulnerability impacts Splunk Enterprise instances before 8.1.7 when configured to repress verbose login errors. | 5.0 |
Search
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`splunkd_failed_auths`
| stats count(user) as auths by user, src
| where auths>5
| stats values(user) as "Users", sum(auths) as TotalFailedAuths by src
| `splunk_user_enumeration_attempt_filter`
Macros
The SPL above uses the following Macros:
splunk_user_enumeration_attempt_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.
- user
- src
- info
- action
How To Implement
This detection does not require you to ingest any new data. The detection does require the ability to search the _audit index. This detection may assist in efforts to find password spraying or brute force authorization attempts in addition to someone enumerating usernames.
Known False Positives
Automation executing authentication attempts against your Splunk infrastructure with outdated credentials may cause false positives.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
40.0 | 50 | 80 | $TotalFailedAuths$ failed authentication events to Splunk from $src$ detected. |
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
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: 1