Splunk User Enumeration Attempt

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Description

The following analytic identifies attempts to enumerate usernames in Splunk by detecting multiple failed authentication attempts from the same source. It leverages data from the _audit index, specifically focusing on failed authentication events. This activity is significant for a SOC because it can indicate an attacker trying to discover valid usernames, which is a precursor to more targeted attacks like password spraying or brute force attempts. If confirmed malicious, this activity could lead to unauthorized access, compromising the security of the Splunk environment and potentially exposing sensitive data.

• Type: TTP

• Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

• Last Updated: 2024-05-21
• Author: Lou Stella, Splunk
• ID: 25625cb4-1c4d-4463-b0f9-7cb462699cde

Annotations

ATT&CK

ATT&CK

ID	Technique	Tactic
T1078	Valid Accounts	Defense Evasion, Persistence, Privilege Escalation, Initial Access

Kill Chain Phase

• Exploitation
• Installation
• Delivery

NIST

• DE.CM

CIS20

• CIS 10

CVE

Search

 `splunkd_failed_auths` 
| stats count(user) as auths by user, src 
| where auths>5 
| stats values(user) as user, sum(auths) as TotalFailedAuths by src 
| `splunk_user_enumeration_attempt_filter`

Macros

The SPL above uses the following Macros:

• splunkd_failed_auths

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Automation executing authentication attempts against your Splunk infrastructure with outdated credentials may cause false positives.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

• Splunk Vulnerabilities

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

• https://www.splunk.com/en_us/product-security/announcements/svd-2022-0502.html

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