Detection rules › Splunk
Windows Unusual NTLM Authentication Users By Source
The following analytic detects when an unusual number of NTLM authentications is attempted by the same source. This activity generally results when an attacker attempts to brute force, password spray, or otherwise authenticate to a domain joined Windows device using an NTLM based process/attack. This same activity may also generate a large number of EventID 4776 events in as well.
Known false positives
- Vulnerability scanners, print servers, and applications that deal with non-domain joined authentications. Recommend adjusting the upperBound_unique eval for tailoring the correlation to your environment, running with a 24hr search window will smooth out some statistical noise.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Credential Access |
Telemetry coverage
Rule body
name: Windows Unusual NTLM Authentication Users By Source
id: 80fcc4d4-fd90-488e-b55a-4e7190ae6ce2
version: 10
creation_date: '2024-03-16'
modification_date: '2026-05-13'
author: Steven Dick
status: production
type: Anomaly
description: The following analytic detects when an unusual number of NTLM authentications is attempted by the same source. This activity generally results when an attacker attempts to brute force, password spray, or otherwise authenticate to a domain joined Windows device using an NTLM based process/attack. This same activity may also generate a large number of EventID 4776 events in as well.
data_source:
- NTLM Operational 8004
- NTLM Operational 8005
- NTLM Operational 8006
search: |
`ntlm_audit`
EventCode = 8004
SChannelName=*
WorkstationName=*
```CIM alignment, remove leading \\ from some auth attempts```
| eval src = replace(WorkstationName,"\\\\","")
| eval dest = SChannelName, user = UserName
``` Remove NTLM auths to self, improves accuracy for certain applications```
| where SChannelName!=src
| stats count min(_time) as firstTime
max(_time) as lastTime
dc(eval(upper(user))) as unique_count by src
| eventstats avg(unique_count) as unique_avg
stdev(unique_count) as unique_std
``` adjust formula for sensitivity```
| eval upperBound_unique=(1+unique_avg+unique_std*3)
| eval isOutlier=CASE(unique_count > upperBound_unique, 1, true(), 0)
| where isOutlier==1
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_unusual_ntlm_authentication_users_by_source_filter`
how_to_implement: The following analytic requires that NTLM Operational logs to be imported from the environment Domain Controllers. This requires configuration of specific auditing settings, see Microsoft references for further guidance. This analytic is specific to EventID 8004~8006.
known_false_positives: Vulnerability scanners, print servers, and applications that deal with non-domain joined authentications. Recommend adjusting the upperBound_unique eval for tailoring the correlation to your environment, running with a 24hr search window will smooth out some statistical noise.
references:
- https://attack.mitre.org/techniques/T1110/003/
- https://techcommunity.microsoft.com/t5/ask-the-directory-services-team/ntlm-blocking-and-you-application-analysis-and-auditing/ba-p/397191
- https://techcommunity.microsoft.com/t5/microsoft-defender-for-identity/enriched-ntlm-authentication-data-using-windows-event-8004/m-p/871827
- https://www.varonis.com/blog/investigate-ntlm-brute-force
- https://learn.microsoft.com/en-us/openspecs/windows_protocols/ms-nrpc/4d1235e3-2c96-4e9f-a147-3cb338a0d09f
intermediate_findings:
entities:
- field: src
type: system
score: 20
message: The device [$src$] attempted $count$ NTLM authentications using $unique_count$ user accounts.
analytic_story:
- Active Directory Password Spraying
asset_type: Endpoint
mitre_attack_id:
- T1110.003
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
category: endpoint
security_domain: endpoint
Stages and Predicates
Stage 1: search
`ntlm_audit`
EventCode = 8004
SChannelName=*
WorkstationName=*
Stage 2: eval
| eval src = replace(WorkstationName,"\\\\","")
Stage 3: eval
| eval dest = SChannelName, user = UserName
Stage 4: where
| where SChannelName!=src
Stage 5: stats
| stats count min(_time) as firstTime
max(_time) as lastTime
dc(eval(upper(user))) as unique_count by src
Stage 6: eventstats
| eventstats avg(unique_count) as unique_avg
stdev(unique_count) as unique_std
Stage 7: eval
| eval upperBound_unique=(1+unique_avg+unique_std*3)
Stage 8: eval
| eval isOutlier=CASE(unique_count > upperBound_unique, 1, true(), 0)
isOutlier =if
unique_count > upperBound_unique1else
0Stage 9: where
| where isOutlier==1
Stage 10: search
| `security_content_ctime(firstTime)`
Stage 11: search
| `security_content_ctime(lastTime)`
Stage 12: search
| `windows_unusual_ntlm_authentication_users_by_source_filter`
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
EventCode | eq |
| field:"EventID" kind:eq value:"8004" |
SChannelName | cross_field_compare |
| field:"SChannelName" kind:cross_field_compare value:"src" |
SChannelName | eq |
| field:"SChannelName" kind:eq value:"*" |
WorkstationName | eq |
| field:"WorkstationName" kind:eq value:"*" |
isOutlier | eq |
| field:"isOutlier" kind:eq value:"1" |
sourcetype | eq |
| field:"sourcetype" kind:eq value:"XmlWinEventLog:Microsoft-Windows-NTLM/Operational" |