:warning: WARNING THIS IS A EXPERIMENTAL analytic

We have not been able to test, simulate, or build datasets for this object. Use at your own risk. This analytic is NOT supported.

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Description

The following hunting analytic leverages Event ID 4624, An account was successfully logged on, to identify an unusual number of remote authentication attempts coming from one source. An endpoint authenticating to a large number of remote endpoints could represent malicious behavior like lateral movement, malware staging, reconnaissance, etc.
The detection calculates the standard deviation for each host and leverages the 3-sigma statistical rule to identify an unusual high number of authentication events. To customize this analytic, users can try different combinations of the bucket span time, the calculation of the upperBound field as well as the Outlier calculation. This logic can be used for real time security monitoring as well as threat hunting exercises.\

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

  • Last Updated: 2021-12-01
  • Author: Mauricio Velazco, Splunk
  • ID: acb5dc74-5324-11ec-a36d-acde48001122

Annotations

ATT&CK
ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Initial Access, Persistence, Privilege Escalation
Kill Chain Phase
  • Reconnaissance
NIST
CIS20
CVE
1
2
3
4
5
6
7
8
 `wineventlog_security` EventCode=4624 Logon_Type=3 Account_Name!="*$" 
| eval Source_Account = mvindex(Account_Name, 1) 
| bucket span=2m _time 
| stats dc(ComputerName) AS unique_targets values(ComputerName) as target_hosts by _time, Source_Network_Address, Source_Account 
| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Source_Network_Address, Source_Account 
| eval upperBound=(comp_avg+comp_std*3) 
| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0) 
| `unusual_number_of_remote_endpoint_authentication_events_filter`

Macros

The SPL above uses the following Macros:

:information_source: unusual_number_of_remote_endpoint_authentication_events_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required field

  • _time
  • EventCode
  • Logon_Type
  • Caller_Process_Name
  • Security_ID
  • Account_Name
  • ComputerName

How To Implement

To successfully implement this search, you need to be ingesting Windows Event Logs from domain controllers aas 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

RBA

Risk Score Impact Confidence Message
42.0 70 60  

:information_source: 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

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