Windows Increase in User Modification Activity

Status: production
Severity: medium
Group by: _time, signature, status, user
Author: Dean Luxton
Source: github.com/splunk/security_content

This analytic detects an increase in modifications to AD user objects. A large volume of changes to user objects can indicate potential security risks, such as unauthorized access attempts, impairing defences or establishing persistence. By monitoring AD logs for unusual modification patterns, this detection helps identify suspicious behavior that could compromise the integrity and security of the AD environment.

MITRE ATT&CK coverage

Tactic	Techniques
Persistence	`T1098` Account Manipulation
Privilege Escalation	`T1098` Account Manipulation
Defense Impairment	`T1685` Disable or Modify Tools

Event coverage

Provider	Event	Title
Security-Auditing	Event ID 4720	A user account was created.
Security-Auditing	Event ID 4722	A user account was enabled.
Security-Auditing	Event ID 4723	An attempt was made to change an account's password.
Security-Auditing	Event ID 4724	An attempt was made to reset an account's password.
Security-Auditing	Event ID 4725	A user account was disabled.
Security-Auditing	Event ID 4726	A user account was deleted.
Security-Auditing	Event ID 4728	A member was added to a security-enabled global group.
Security-Auditing	Event ID 4732	A member was added to a security-enabled local group.
Security-Auditing	Event ID 4733	A member was removed from a security-enabled local group.
Security-Auditing	Event ID 4738	A user account was changed.
Security-Auditing	Event ID 4743	A computer account was deleted.
Security-Auditing	Event ID 4780	The ACL was set on accounts which are members of administrators groups.

Rule body splunk

name: Windows Increase in User Modification Activity
id: 0995fca1-f346-432f-b0bf-a66d14e6b428
version: 9
creation_date: '2024-07-01'
modification_date: '2026-05-13'
author: Dean Luxton
status: production
type: TTP
description: This analytic detects an increase in modifications to AD user objects. A large volume of changes to user objects can indicate potential security risks, such as unauthorized access attempts, impairing defences or establishing persistence. By monitoring AD logs for unusual modification patterns, this detection helps identify suspicious behavior that could compromise the integrity and security of the AD environment.
data_source:
    - Windows Event Log Security 4720
search: |-
    `wineventlog_security` EventCode IN (4720,4722,4723,4724,4725,4726,4728,4732,4733,4738,4743,4780)
      | bucket span=5m _time
      | stats values(TargetDomainName) as TargetDomainName, values(user) as user, dc(user) as userCount, values(user_category) as user_category, values(src_user_category) as src_user_category, values(dest) as dest, values(dest_category) as dest_category
        BY _time, src_user, signature,
           status
      | eventstats avg(userCount) as comp_avg , stdev(userCount) as comp_std
        BY src_user, signature
      | eval upperBound=(comp_avg+comp_std*3)
      | eval isOutlier=if(userCount > 10 and userCount >= upperBound, 1, 0)
      | search isOutlier=1
      | stats values(TargetDomainName) as TargetDomainName, values(user) as user, dc(user) as userCount, values(user_category) as user_category, values(src_user_category) as src_user_category, values(dest) as dest, values(dest_category) as dest_category values(signature) as signature
        BY _time, src_user, status
      | `windows_increase_in_user_modification_activity_filter`
how_to_implement: Run this detection looking over a 7 day timeframe for best results.
known_false_positives: Genuine activity
references: []
drilldown_searches:
    - name: View the detection results for - "$src_user$"
      search: '%original_detection_search% | search  src_user = "$src_user$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$src_user$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$src_user$") | 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"
finding:
    title: Spike in User Modification actions performed by $src_user$
    entity:
        field: src_user
        type: user
        score: 50
analytic_story:
    - Sneaky Active Directory Persistence Tricks
asset_type: Endpoint
mitre_attack_id:
    - T1098
    - T1685
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: audit
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1098/account_manipulation/xml-windows-security.log
          source: XmlWinEventLog:Security
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: `search`

`wineventlog_security` EventCode IN (4720,4722,4723,4724,4725,4726,4728,4732,4733,4738,4743,4780)

Stage 2: `bucket`

| bucket span=5m _time

Stage 3: `stats`

| stats values(TargetDomainName) as TargetDomainName, values(user) as user, dc(user) as userCount, values(user_category) as user_category, values(src_user_category) as src_user_category, values(dest) as dest, values(dest_category) as dest_category
    BY _time, src_user, signature,
       status

Stage 4: `eventstats`

| eventstats avg(userCount) as comp_avg , stdev(userCount) as comp_std
    BY src_user, signature

Stage 5: `eval`

| eval upperBound=(comp_avg+comp_std*3)

Stage 6: `eval`

| eval isOutlier=if(userCount > 10 and userCount >= upperBound, 1, 0)

isOutlier =

ifuserCount > 10 AND userCount >= upperBound1

else0

Stage 7: `search`

| search isOutlier=1

Stage 8: `stats`

| stats values(TargetDomainName) as TargetDomainName, values(user) as user, dc(user) as userCount, values(user_category) as user_category, values(src_user_category) as src_user_category, values(dest) as dest, values(dest_category) as dest_category values(signature) as signature
    BY _time, src_user, status

Stage 9: `search`

| `windows_increase_in_user_modification_activity_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.

Field	Kind	Values
`EventCode`	in	`4720` corpus 5 (kusto 3, splunk 2) `4722` corpus 2 (kusto 2) `4723` corpus 2 (splunk 1, kusto 1) `4724` `4725` corpus 2 (splunk 1, kusto 1) `4726` corpus 2 (splunk 1, kusto 1) `4728` corpus 3 (splunk 3) `4732` corpus 4 (splunk 3, kusto 1) `4733` `4738` corpus 6 (splunk 4, elastic 1, kusto 1) `4743` `4780`
`isOutlier`	eq	`1` corpus 28 (splunk 28)

`j` / `k`	Scroll down / up
`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
`/`	Focus search
`?`	Toggle this help
`↑` / `↓`	Navigate search results
`Enter`	Open highlighted result
`Esc`	Close results / dialog

`type:`	`events` / `rules` / `providers`
`vendor:`	`sigma` / `elastic` / `splunk` / `kusto` / `chronicle` (vendor name alone also works: `sigma:`, `kql:`, `secops:`…)
`tactic:`	TA-id, slug, or name: `credential_access`, `TA0006`
`technique:`	technique or sub-technique ID: `T1003`, `T1003.001` (alias `tech:`)
`severity:`	`critical` / `high` / `medium` / `low` / `informational` (alias `sev:`)
`risk_score`	Numeric comparison on the Elastic risk score (0 to 100): `risk_score>50`, `risk_score<=20`, `risk_score=99` (alias `risk`; Elastic rules only)
`stages:`	Rules with exactly N pipeline stages
`correlation:`	`single_event` / `sequence` / `alternatives` / `alternatives_cross_log` / `all_required` / `correlated`
`with:`	Co-occurrence event-id; stacks (`with:4624 with:4769`) to require all, while a comma list in one occurrence (`with:4624,4769`) is an either-or group. Implies multi-event
`like:`	Structural neighbors of a rule slug (equivalents + subsumption stricter / broader): `like:comsvcs_lsass_memory_dump-splunk-sysmon`
`groupby:`	Entity-grouping substring match against `group_by_keys`: `groupby:user`, `groupby:host`
`uses:`	Rules whose predicate tree touches the field (any kind, any value): `uses:CommandLine`
`excludes:`	Rules with top-level `not()` clauses on the field (FP whitelists): `excludes:ParentImage`
`field:` / `value:`	Predicate search; narrows rule cards to those with a matching leaf and drives the indicator tier. Unquoted = substring, wildcards allowed (`value:mimikatz`)
`indicator:`	Shorthand for `field:F value:V`: `indicator:Image=*\powershell.exe`
`kind:`	Filter by predicate kind. Narrows rule cards to those carrying a matching predicate leaf (`vendor:elastic kind:cidr_match`) and drives the indicator tier: `contains` / `starts_with` / `ends_with` / `regex` / `cidr` / `eq` / `in` … (operator aliases `op:`/`match:`)
`has:` / `no:`	`sample`, `field`, `notes`, `refs`, `trace`, `thirdparty`, `rule`, `pattern`, `timewindow`, `threshold`, `newterms`, `sigma`/`elastic`/`splunk`/`kusto`/`chronicle`
`-op:val`	Exclude matches; works on most operators but not `type:`/`like:`/`has:`/`no:` (use `no:<flag>` to exclude a rule flag): `tactic:execution -vendor:splunk`. Standalone `-kind:`/`-field:`/`-value:` drop every rule carrying a matching predicate leaf (`type:rules -kind:is_null`)
`field:"…"` / `value:"…"`	Quoted value = anchored exact match (also allows spaces): `value:"net user"`
`a,b`	Comma = OR inside one operator (`vendor:sigma,elastic`, `severity:high,critical`); repeating a facet merges the same way. `field:`/`value:` never split (literal commas)
`vendors:` / `stage:`	Singular and plural spellings fold to the canonical operator and value: `tactics:` = `tactic:`, `type:event` = `type:events`, `correlation:sequences` = `correlation:sequence`, `has:thresholds` = `has:threshold`
`"quoted phrase"`	Exact-match a multi-word phrase (free text)

Windows Increase in User Modification Activity

MITRE ATT&CK coverage

Event coverage

Rule body splunk

Stages and Predicates

Stage 1: `search`

Stage 2: `bucket`

Stage 3: `stats`

Stage 4: `eventstats`

Stage 5: `eval`

Stage 6: `eval`

Stage 7: `search`

Stage 8: `stats`

Stage 9: `search`

Indicators

Keyboard shortcuts

Search operators

Windows Increase in User Modification Activity

MITRE ATT&CK coverage

Event coverage

Rule body splunk

Stages and Predicates

Stage 1: search

Stage 2: bucket

Stage 3: stats

Stage 4: eventstats

Stage 5: eval

Stage 6: eval

Stage 7: search

Stage 8: stats

Stage 9: search

Indicators

Stage 1: `search`

Stage 2: `bucket`

Stage 3: `stats`

Stage 4: `eventstats`

Stage 5: `eval`

Stage 6: `eval`

Stage 7: `search`

Stage 8: `stats`

Stage 9: `search`