Detection rules › Splunk

Windows Unusual Count Of Users Fail To Auth Wth ExplicitCredentials

Status
production
Severity
low
Group by
_time, computer_name, user
Author
Mauricio Velazco, Splunk
Source
github.com/splunk/security_content

The following analytic identifies a source user failing to authenticate with multiple users using explicit credentials on a host. It leverages Windows Event Code 4648 and calculates the standard deviation for each host, using the 3-sigma rule to detect anomalies. This behavior is significant as it may indicate a Password Spraying attack, where an adversary attempts to gain initial access or elevate privileges. If confirmed malicious, this activity could lead to unauthorized access, privilege escalation, or further compromise of the Active Directory environment.

MITRE ATT&CK coverage

TacticTechniques
Credential AccessT1110.003 Brute Force: Password Spraying

Event coverage

Rule body splunk

name: Windows Unusual Count Of Users Fail To Auth Wth ExplicitCredentials
id: 14f414cf-3080-4b9b-aaf6-55a4ce947b93
version: 12
creation_date: '2021-04-14'
modification_date: '2026-05-13'
author: Mauricio Velazco, Splunk
status: production
type: Anomaly
description: The following analytic identifies a source user failing to authenticate with multiple users using explicit credentials on a host. It leverages Windows Event Code 4648 and calculates the standard deviation for each host, using the 3-sigma rule to detect anomalies. This behavior is significant as it may indicate a Password Spraying attack, where an adversary attempts to gain initial access or elevate privileges. If confirmed malicious, this activity could lead to unauthorized access, privilege escalation, or further compromise of the Active Directory environment.
data_source:
    - Windows Event Log Security 4648
search: |-
    `wineventlog_security` EventCode=4648 Caller_User_Name!=*$ Target_User_Name!=*$
      | bucket span=5m _time
      | stats dc(Target_User_Name) AS unique_accounts values(Target_User_Name) as user values(dest) as dest values(src_ip) as src_ip
        BY _time, Computer, Caller_User_Name
      | eventstats avg(unique_accounts) as comp_avg , stdev(unique_accounts) as comp_std
        BY Computer
      | eval upperBound=(comp_avg+comp_std*3)
      | eval isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0)
      | search isOutlier=1
      | `windows_unusual_count_of_users_fail_to_auth_wth_explicitcredentials_filter`
how_to_implement: 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: A source user failing attempting to authenticate multiple users on a host is not a common behavior for regular systems. Some applications, however, may exhibit this behavior in which case sets of users hosts can be added to an allow list. Possible false positive scenarios include systems where several users connect to like Mail servers, identity providers, remote desktop services, Citrix, etc.
references:
    - https://attack.mitre.org/techniques/T1110/003/
    - https://docs.microsoft.com/en-us/windows/security/threat-protection/auditing/event-4648
    - https://docs.microsoft.com/en-us/windows/security/threat-protection/auditing/basic-audit-logon-events
drilldown_searches:
    - name: View the detection results for - "$user$"
      search: '%original_detection_search% | search  user = "$user$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$user$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: user
          type: user
          score: 20
          message: Potential password spraying attack from $Computer$
        - field: Computer
          type: system
          score: 20
          message: Potential password spraying attack from $Computer$
analytic_story:
    - Active Directory Password Spraying
    - Insider Threat
    - Volt Typhoon
asset_type: Endpoint
mitre_attack_id:
    - T1110.003
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint
tests:
    - attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1110.003/purplesharp_explicit_credential_spray_xml/windows-security.log
          source: XmlWinEventLog:Security
          sourcetype: XmlWinEventLog
      name: True Positive Test
      test_type: unit

Stages and Predicates

Stage 1: search

`wineventlog_security` EventCode=4648 Caller_User_Name!=*$ Target_User_Name!=*$

Stage 2: bucket

| bucket span=5m _time

Stage 3: stats

| stats dc(Target_User_Name) AS unique_accounts values(Target_User_Name) as user values(dest) as dest values(src_ip) as src_ip
    BY _time, Computer, Caller_User_Name

Stage 4: eventstats

| eventstats avg(unique_accounts) as comp_avg , stdev(unique_accounts) as comp_std
    BY Computer

Stage 5: eval

| eval upperBound=(comp_avg+comp_std*3)

Stage 6: eval

| eval isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0)
isOutlier =
ifunique_accounts > 10 AND unique_accounts >= upperBound1
else0

Stage 7: search

| search isOutlier=1

Stage 8: search

| `windows_unusual_count_of_users_fail_to_auth_wth_explicitcredentials_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
Caller_User_Namene
  • *$ corpus 3 (splunk 3)
EventCodeeq
  • 4648 corpus 5 (splunk 5)
Target_User_Namene
  • *$ corpus 2 (splunk 2)
isOutliereq
  • 1 corpus 28 (splunk 28)