Windows Common Abused Cmd Shell Risk Behavior

name: Windows Common Abused Cmd Shell Risk Behavior
id: e99fcc4f-c6b0-4443-aa2a-e3c85126ec9a
version: 8
date: '2026-02-25'
author: Teoderick Contreras, Splunk
status: production
type: Correlation
data_source: []
description: The following analytic identifies instances where four or more distinct detection analytics are associated with malicious command line behavior on a specific host. This detection leverages the Command Line Interface (CLI) data from various sources to identify suspicious activities. This behavior is significant as it often indicates attempts to execute malicious commands, access sensitive data, install backdoors, or perform other nefarious actions. If confirmed malicious, attackers could gain unauthorized control, exfiltrate information, escalate privileges, or launch further attacks within the network, leading to severe compromise.
search: |-
    | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as risk_score, count(All_Risk.calculated_risk_score) as risk_event_count, values(All_Risk.annotations.mitre_attack.mitre_tactic_id) as annotations.mitre_attack.mitre_tactic_id, dc(All_Risk.annotations.mitre_attack.mitre_tactic_id) as mitre_tactic_id_count, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count, values(All_Risk.tag) as tag, values(source) as source, dc(source) as source_count FROM datamodel=Risk.All_Risk
      WHERE source IN ("*Windows Cmdline Tool Execution From Non-Shell Process*", "*Windows System Network Config Discovery Display DNS*", "*Local Account Discovery With Wmic*", "*Windows Group Discovery Via Net*", "*Windows Create Local Administrator Account Via Net*", "*Windows User Discovery Via Net*", "*Icacls Deny Command*", "*ICACLS Grant Command*", "*Windows Proxy Via Netsh*", "*Processes launching netsh*", "*Disabling Firewall with Netsh*", "*Windows System Network Connections Discovery Netsh*", "*Network Connection Discovery With Arp*", "*Windows System Discovery Using ldap Nslookup*", "*Windows System Shutdown CommandLine*")
      BY All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic
    | `drop_dm_object_name(All_Risk)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | where source_count >= 4
    | `windows_common_abused_cmd_shell_risk_behavior_filter`
how_to_implement: Splunk Enterprise Security is required to utilize this correlation. In addition, modify the source_count value to your environment. In our testing, a count of 4 or 5 was decent in a lab, but the number may need to be increased base on internal testing. In addition, based on false positives, modify any analytics to be anomaly and lower or increase risk based on organization importance.
known_false_positives: False positives will be present based on many factors. Tune the correlation as needed to reduce too many triggers.
references:
    - https://www.splunk.com/en_us/blog/security/from-macros-to-no-macros-continuous-malware-improvements-by-qakbot.html
    - https://www.splunk.com/en_us/blog/security/dark-crystal-rat-agent-deep-dive.html
drilldown_searches:
    - name: View the detection results for - "$risk_object$"
      search: '%original_detection_search% | search  risk_object = "$risk_object$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$risk_object$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$risk_object$") starthoursago=168  | 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: $info_min_time$
      latest_offset: $info_max_time$
tags:
    analytic_story:
        - Azorult
        - Volt Typhoon
        - Sandworm Tools
        - Windows Post-Exploitation
        - FIN7
        - Qakbot
        - Netsh Abuse
        - DarkCrystal RAT
        - Windows Defense Evasion Tactics
        - CISA AA23-347A
        - Disabling Security Tools
        - Microsoft WSUS CVE-2025-59287
    asset_type: Endpoint
    mitre_attack_id:
        - T1222
        - T1049
        - T1033
        - T1529
        - T1016
        - T1059
    product:
        - Splunk Enterprise
        - Splunk Enterprise Security
        - Splunk Cloud
    security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059/risk_behavior/abused_commandline/risk_recon.log
          source: risk
          sourcetype: stash