Detection rules › Splunk

Malicious PowerShell Process - Encoded Command

Status
production
Group by
IntegrityLevel, command_line, computer_name, event_action, original_file_name, parent_command_line, parent_process_guid, parent_process_id, parent_process_name, process_guid, process_hash, process_id, process_name, user, user_id, vendor_product
Author
David Dorsey, Michael Haag, Splunk, SirDuckly, GitHub Community
Source
github.com/splunk/security_content

The following analytic detects the use of the EncodedCommand parameter in PowerShell processes. It leverages Endpoint Detection and Response (EDR) data to identify variations of the EncodedCommand parameter, including shortened forms and different command switch types. This activity can be significant because adversaries often use encoded commands to obfuscate malicious scripts, making detection harder. If confirmed malicious, this behavior could allow attackers to execute hidden code, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment. Review parallel events to determine legitimacy and tune based on known administrative scripts.

MITRE ATT&CK coverage

Event coverage

Rule body splunk

name: Malicious PowerShell Process - Encoded Command
id: c4db14d9-7909-48b4-a054-aa14d89dbb19
version: 21
creation_date: '2020-04-29'
modification_date: '2026-05-13'
author: David Dorsey, Michael Haag, Splunk, SirDuckly, GitHub Community
status: production
type: Hunting
description: |
    The following analytic detects the use of the EncodedCommand parameter in PowerShell processes.
    It leverages Endpoint Detection and Response (EDR) data to identify variations of the EncodedCommand parameter, including shortened forms and different command switch types.
    This activity can be significant because adversaries often use encoded commands to obfuscate malicious scripts, making detection harder.
    If confirmed malicious, this behavior could allow attackers to execute hidden code, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment.
    Review parallel events to determine legitimacy and tune based on known administrative scripts.
data_source:
    - Sysmon EventID 1
    - Windows Event Log Security 4688
    - CrowdStrike ProcessRollup2
search: |-
    | tstats `security_content_summariesonly`
      count min(_time) as firstTime
            max(_time) as lastTime
    from datamodel=Endpoint.Processes where
    `process_powershell`
    by Processes.action Processes.dest Processes.original_file_name
       Processes.parent_process Processes.parent_process_exec
       Processes.parent_process_guid Processes.parent_process_id
       Processes.parent_process_name Processes.parent_process_path
       Processes.process Processes.process_exec Processes.process_guid
       Processes.process_hash Processes.process_id
       Processes.process_integrity_level Processes.process_name
       Processes.process_path Processes.user
       Processes.user_id Processes.vendor_product
    | `drop_dm_object_name(Processes)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | where match(process,"(?i)(?:^|\\s)(?:/(?!/)|--?|–{1,2}|—{1,2}|―{1,2})(?:ec|encodedcommand|encodedcomman|encodedcomma|encodedcomm|encodedcom|encodedco|encodedc|encoded|encode|encod|enco|enc|en|e(?=\\s))\\s+['\\\"]?[A-Za-z0-9+/=]{5,}['\\\"]?")
    | `malicious_powershell_process___encoded_command_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: |
    False positives are expected from legitimate PowerShell scripts,
    system administrators, and applications. Filter as needed.
references:
    - https://regexr.com/662ov
    - https://github.com/redcanaryco/AtomicTestHarnesses/blob/master/Windows/TestHarnesses/T1059.001_PowerShell/OutPowerShellCommandLineParameter.ps1
    - https://ss64.com/ps/powershell.html
    - https://twitter.com/M_haggis/status/1440758396534214658?s=20
    - https://www.microsoft.com/security/blog/2022/01/15/destructive-malware-targeting-ukrainian-organizations/
    - https://www.microsoft.com/en-us/security/blog/2023/05/24/volt-typhoon-targets-us-critical-infrastructure-with-living-off-the-land-techniques/
analytic_story:
    - SolarWinds WHD RCE Post Exploitation
    - CISA AA22-320A
    - Hermetic Wiper
    - Sandworm Tools
    - Qakbot
    - Volt Typhoon
    - NOBELIUM Group
    - Data Destruction
    - Lumma Stealer
    - Malicious PowerShell
    - DarkCrystal RAT
    - WhisperGate
    - Crypto Stealer
    - Microsoft SharePoint Vulnerabilities
    - Scattered Spider
    - GhostRedirector IIS Module and Rungan Backdoor
    - Microsoft WSUS CVE-2025-59287
asset_type: Endpoint
mitre_attack_id:
    - T1027
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/attack_techniques/T1027/atomic_red_team/windows-sysmon.log
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly`
  count min(_time) as firstTime
        max(_time) as lastTime
from datamodel=Endpoint.Processes where
`process_powershell`
by Processes.action Processes.dest Processes.original_file_name
   Processes.parent_process Processes.parent_process_exec
   Processes.parent_process_guid Processes.parent_process_id
   Processes.parent_process_name Processes.parent_process_path
   Processes.process Processes.process_exec Processes.process_guid
   Processes.process_hash Processes.process_id
   Processes.process_integrity_level Processes.process_name
   Processes.process_path Processes.user
   Processes.user_id Processes.vendor_product

Stage 2: search

| `drop_dm_object_name(Processes)`

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: where

| where match(process,"(?i)(?:^|\\s)(?:/(?!/)|--?|–{1,2}|—{1,2}|―{1,2})(?:ec|encodedcommand|encodedcomman|encodedcomma|encodedcomm|encodedcom|encodedco|encodedc|encoded|encode|encod|enco|enc|en|e(?=\\s))\\s+['\\\"]?[A-Za-z0-9+/=]{5,}['\\\"]?")

Stage 6: search

| `malicious_powershell_process___encoded_command_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
  • "PowerShell.EXE" corpus 120 (sigma 84, splunk 30, elastic 6)
  • "powershell_ise.EXE" corpus 51 (splunk 30, sigma 18, elastic 3)
  • "pwsh.dll" corpus 112 (sigma 79, splunk 30, elastic 3)
Processes.process_nameeq
  • "powershell.exe" corpus 104 (elastic 60, splunk 44)
  • "powershell_ise.exe" corpus 50 (splunk 29, elastic 21)
  • "pwsh.exe" corpus 62 (elastic 33, splunk 29)
processmatch
  • "(?i)(?:^|\\s)(?:/(?!/)|--?|–{1,2}|—{1,2}|―{1,2})(?:ec|encodedcommand|encodedcomman|encodedcomma|encodedcomm|encodedcom|encodedco|encodedc|encoded|encode|encod|enco|enc|en|e(?=\\s))\\s+['\\\"]?[A-Za-z0-9+/=]{5,}['\\\"]?"