Excessive Usage Of Cacls App

SPLUNK detection rule by Teoderick Contreras, Splunk · Apache-2.0

The following analytic identifies excessive usage of `cacls.exe`, `xcacls.exe`, or `icacls.exe` to change file or folder permissions. It looks for 10 or more execution of the aforementioned processes in the span of 1 minute. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it may indicate an adversary attempting to restrict access to malware components or artifacts on a compromised system. If confirmed malicious, this behavior could prevent users from deleting or accessing critical files, aiding in the persistence and concealment of malicious activities.

name: Excessive Usage Of Cacls App
id: 0bdf6092-af17-11eb-939a-acde48001122
version: 13
creation_date: '2021-05-07'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk
status: production
type: Anomaly
description: |
    The following analytic identifies excessive usage of `cacls.exe`, `xcacls.exe`,
    or `icacls.exe` to change file or folder permissions.
    It looks for 10 or more execution of the aforementioned processes in the span of 1 minute.
    It leverages data from Endpoint Detection and Response (EDR) agents,
    focusing on process names and command-line executions.
    This activity is significant as it may indicate an adversary attempting
    to restrict access to malware components or artifacts on a compromised system.
    If confirmed malicious, this behavior could prevent users from deleting or accessing
    critical files, aiding in the persistence and concealment of malicious activities.
data_source:
    - Sysmon EventID 1
    - Windows Event Log Security 4688
    - CrowdStrike ProcessRollup2
search: |
    | tstats `security_content_summariesonly`
      min(_time) as firstTime
      max(_time) as lastTime
      values(Processes.dest) as dest
      values(Processes.user) as user
      values(Processes.action) as action
      values(Processes.original_file_name) as original_file_name
      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_name) as process_name
      values(Processes.process_path) as process_path
      values(Processes.user_id) as user_id
      values(Processes.vendor_product) as vendor_product count
    from datamodel=Endpoint.Processes where
    Processes.process_name IN( "icacls.exe", "cacls.exe", "xcacls.exe")
    by Processes.parent_process_name Processes.parent_process Processes.dest Processes.user _time span=1m
    | where count >=10
    | `drop_dm_object_name(Processes)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | `excessive_usage_of_cacls_app_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: Administrators or administrative scripts may use this application. Filter as needed.
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"
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 20
          message: An excessive amount of $process_name$ was executed on $dest$ attempting to modify permissions.
threat_objects:
    - field: process_name
      type: process_name
analytic_story:
    - Azorult
    - Windows Post-Exploitation
    - Prestige Ransomware
    - XMRig
    - Crypto Stealer
    - Defense Evasion or Unauthorized Access Via SDDL Tampering
asset_type: Endpoint
mitre_attack_id:
    - T1222
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

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Format & documentation suggestions

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