Detection rules › Splunk

Windows Excessive Service Stop Attempt

Status
production
Severity
medium
Group by
_time, computer_name, original_file_name, parent_process_name, process_name, user
Author
Teoderick Contreras, Splunk
Source
github.com/splunk/security_content

The following analytic detects multiple attempts to stop or delete services on a system using net.exe or sc.exe. It leverages Endpoint Detection and Response (EDR) telemetry, focusing on process names and command-line executions within a one-minute window. This activity is significant as it may indicate an adversary attempting to disable security or critical services to evade detection and further their objectives. If confirmed malicious, this could lead to the attacker gaining persistence, escalating privileges, or disrupting essential services, thereby compromising the system's security posture.

MITRE ATT&CK coverage

TacticTechniques
ImpactT1489 Service Stop

Event coverage

Rule body splunk

name: Windows Excessive Service Stop Attempt
id: 8f3a614f-6b98-4f7d-82dd-d0df38452a8b
version: 8
creation_date: '2021-05-07'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk
status: production
type: TTP
description: The following analytic detects multiple attempts to stop or delete services on a system using `net.exe` or `sc.exe`. It leverages Endpoint Detection and Response (EDR) telemetry, focusing on process names and command-line executions within a one-minute window. This activity is significant as it may indicate an adversary attempting to disable security or critical services to evade detection and further their objectives. If confirmed malicious, this could lead to the attacker gaining persistence, escalating privileges, or disrupting essential services, thereby compromising the system's security posture.
data_source:
    - Sysmon EventID 1
    - Windows Event Log Security 4688
    - CrowdStrike ProcessRollup2
search: |-
    | tstats `security_content_summariesonly` values(Processes.action) as action values(Processes.parent_process) as parent_process values(Processes.parent_process_exec) as parent_process_exec values(Processes.parent_process_guid) as parent_process_guid values(Processes.parent_process_id) as parent_process_id values(Processes.parent_process_path) as parent_process_path values(Processes.process) as process values(Processes.process_exec) as process_exec values(Processes.process_guid) as process_guid values(Processes.process_hash) as process_hash values(Processes.process_id) as process_id values(Processes.process_integrity_level) as process_integrity_level values(Processes.process_path) as process_path values(Processes.user) as user  values(Processes.user_id) as user_id values(Processes.vendor_product) as vendor_product count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
      WHERE (
            `process_net`
            OR
            `process_sc`
        )
        AND Processes.process="*stop*" OR Processes.process="*delete*"
      BY Processes.process_name Processes.original_file_name Processes.parent_process_name
         Processes.dest Processes.user _time
         span=1m
    | where count >=5
    | `drop_dm_object_name(Processes)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | `windows_excessive_service_stop_attempt_filter`
how_to_implement: The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the `Processes` node of the `Endpoint` data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
known_false_positives: No false positives have been identified at this time.
references:
    - https://thedfirreport.com/2020/04/20/sqlserver-or-the-miner-in-the-basement/
drilldown_searches:
    - name: View the detection results for - "$dest$"
      search: '%original_detection_search% | search  dest = "$dest$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$dest$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") | 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: An excessive amount of $process_name$ was executed on $dest$ attempting to disable services.
    entity:
        field: dest
        type: system
        score: 50
threat_objects:
    - field: process_name
      type: process_name
analytic_story:
    - XMRig
    - Ransomware
    - BlackByte Ransomware
asset_type: Endpoint
mitre_attack_id:
    - T1489
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/xmrig_miner/windows-sysmon.log
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly` values(Processes.action) as action values(Processes.parent_process) as parent_process values(Processes.parent_process_exec) as parent_process_exec values(Processes.parent_process_guid) as parent_process_guid values(Processes.parent_process_id) as parent_process_id values(Processes.parent_process_path) as parent_process_path values(Processes.process) as process values(Processes.process_exec) as process_exec values(Processes.process_guid) as process_guid values(Processes.process_hash) as process_hash values(Processes.process_id) as process_id values(Processes.process_integrity_level) as process_integrity_level values(Processes.process_path) as process_path values(Processes.user) as user  values(Processes.user_id) as user_id values(Processes.vendor_product) as vendor_product count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
  WHERE (
        `process_net`
        OR
        `process_sc`
    )
    AND Processes.process="*stop*" OR Processes.process="*delete*"
  BY Processes.process_name Processes.original_file_name Processes.parent_process_name
     Processes.dest Processes.user _time
     span=1m

Stage 2: where

| where count >=5

Stage 3: search

| `drop_dm_object_name(Processes)`

Stage 4: search

| `security_content_ctime(firstTime)`

Stage 5: search

| `security_content_ctime(lastTime)`

Stage 6: search

| `windows_excessive_service_stop_attempt_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
Processes.original_file_nameeq
  • "net1.exe" corpus 44 (sigma 19, splunk 19, elastic 6)
  • "sc.exe" corpus 26 (sigma 12, splunk 10, elastic 4)
Processes.processeq
  • "*delete*" corpus 23 (sigma 16, splunk 6, kusto 1)
  • "*stop*" corpus 7 (sigma 5, splunk 2)
Processes.process_nameeq
  • "net1.exe" corpus 35 (splunk 19, elastic 16)
  • "sc.exe" corpus 29 (splunk 15, elastic 14)
countge
  • 5 corpus 3 (splunk 3)