ID | Technique | Tactic |
---|---|---|
T1087 | Account Discovery | Discovery |
Detection: Splunk Information Disclosure on Account Login
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.
Search
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 |
---|---|---|---|
Splunk | Splunk | 'splunkd_ui_access' |
'splunkd_ui_access.log' |
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
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
Aquatic Panda
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