Detection: Unusual Number of Remote Endpoint Authentication Events

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Description

The following analytic identifies an unusual number of remote authentication attempts from a single source by leveraging Windows Event ID 4624, which logs successful account logons. It uses statistical analysis, specifically the 3-sigma rule, to detect deviations from normal behavior. This activity is significant for a SOC as it may indicate lateral movement, malware staging, or reconnaissance. If confirmed malicious, this behavior could allow an attacker to move laterally within the network, escalate privileges, or gather information for further attacks.

1`wineventlog_security` EventCode=4624 Logon_Type=3 Account_Name!="*$" 
2| eval Source_Account = mvindex(Account_Name, 1) 
3| bucket span=2m _time 
4| stats dc(ComputerName) AS unique_targets values(ComputerName) as target_hosts by _time, Source_Network_Address, Source_Account 
5| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Source_Network_Address, Source_Account 
6| eval upperBound=(comp_avg+comp_std*3) 
7| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0) 
8| `unusual_number_of_remote_endpoint_authentication_events_filter`

Data Source

Name Platform Sourcetype Source
Windows Event Log Security 4624 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security'

Macros Used

Name Value
wineventlog_security eventtype=wineventlog_security OR Channel=security OR source=XmlWinEventLog:Security
unusual_number_of_remote_endpoint_authentication_events_filter search *
unusual_number_of_remote_endpoint_authentication_events_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
T1078 Valid Accounts Defense Evasion
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT18
APT28
APT29
APT33
APT39
APT41
Akira
Axiom
Carbanak
Chimera
Cinnamon Tempest
Dragonfly
FIN10
FIN4
FIN5
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
INC Ransom
Indrik Spider
Ke3chang
LAPSUS$
Lazarus Group
Leviathan
OilRig
POLONIUM
PittyTiger
Play
Sandworm Team
Silence
Silent Librarian
Star Blizzard
Suckfly
Threat Group-3390
Volt Typhoon
Wizard Spider
menuPass

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

To successfully implement this search, you need to be ingesting Windows Event Logs from domain controllers as well as member servers and workstations. The Advanced Security Audit policy setting Audit Logon within Logon/Logoff needs to be enabled.

Known False Positives

An single endpoint authenticating to a large number of hosts is not common behavior. Possible false positive scenarios include but are not limited to vulnerability scanners, jump servers and missconfigured systems.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Unusual number of remote authentication events from $Source_Network_Address$ 42 70 60
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 Not Applicable N/A N/A N/A
Unit ❌ Failing N/A N/A N/A
Integration ❌ Failing N/A N/A N/A

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: 4