Detection: Splunk Information Disclosure on Account Login

Updated Date: 2024-07-01 ID: 2bae5d19-6d1b-4db0-82ab-0af5ac5f836c Author: Rod Soto Type: Hunting Product: Splunk Enterprise Security

Description

This is a composed hunting search that looks for possible user enumeration attempts when SAML is enabled on a Splunk instance by capturing different responses from server.

1`splunkd` component=UiAuth status=failure action=login TcpChannelThread 
2| stats count min(_time) as firstTime max(_time) as lastTime by user status action clientip 
3| `security_content_ctime(firstTime)` 
4| `security_content_ctime(lastTime)` 
5| `splunk_information_disclosure_on_account_login_filter`

Data Source

Name Platform Sourcetype Source Supported App
Splunk Splunk icon Splunk 'splunkd_ui_access' 'splunkd_ui_access.log' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
splunk_information_disclosure_on_account_login_filter search *
splunk_information_disclosure_on_account_login_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1087 Account Discovery Discovery
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
FIN13

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Risk Event False
This configuration file applies to all detections of type hunting.

Implementation

Requires access to internal indexes _internal.

Known False Positives

This is a hunting search and requires operator to search for large number of login failures from several users indicating possible user enumeration attempts. May capture genuine login failures.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Possible user enumeration attack against $clientip$ 5 10 50
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset /opt/splunk/var/log/splunk/splunkd.log splunkd
Integration ✅ Passing Dataset /opt/splunk/var/log/splunk/splunkd.log splunkd

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: GitHub | Version: 1