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detections/endpoint/cmd_carry_out_string_command_parameter.yml

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name: CMD Carry Out String Command Parameter
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id: 54a6ed00-3256-11ec-b031-acde48001122
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version: 14
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date: '2025-08-07'
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version: 15
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date: '2025-08-22'
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author: Teoderick Contreras, Bhavin Patel, Splunk
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status: production
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type: Hunting
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description: The following analytic detects the use of `cmd.exe /c` to execute commands,
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a technique often employed by adversaries and malware to run batch commands or invoke
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other shells like PowerShell. This detection leverages data from Endpoint Detection
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and Response (EDR) agents, focusing on command-line executions and process metadata.
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Monitoring this activity is crucial as it can indicate script-based attacks or unauthorized
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command execution. If confirmed malicious, this behavior could lead to unauthorized
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code execution, privilege escalation, or persistence within the environment.
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description: The following analytic detects the use of `cmd.exe /c` to execute
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commands, a technique often employed by adversaries and malware to run batch
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commands or invoke other shells like PowerShell. This detection leverages data
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from Endpoint Detection and Response (EDR) agents, focusing on command-line
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executions and process metadata. Monitoring this activity is crucial as it can
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indicate script-based attacks or unauthorized command execution. If confirmed
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malicious, this behavior could lead to unauthorized code execution, privilege
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escalation, or persistence within the environment.
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data_source:
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- Sysmon EventID 1
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- Windows Event Log Security 4688
@@ -25,17 +26,18 @@ search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_
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Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path
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Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)`
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| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `cmd_carry_out_string_command_parameter_filter`'
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how_to_implement: The detection is based on data that originates from Endpoint Detection
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and Response (EDR) agents. These agents are designed to provide security-related
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telemetry from the endpoints where the agent is installed. To implement this search,
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you must ingest logs that contain the process GUID, process name, and parent process.
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Additionally, you must ingest complete command-line executions. These logs must
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be processed using the appropriate Splunk Technology Add-ons that are specific to
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the EDR product. The logs must also be mapped to the `Processes` node of the `Endpoint`
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data model. Use the Splunk Common Information Model (CIM) to normalize the field
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names and speed up the data modeling process.
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known_false_positives: False positives may be high based on legitimate scripted code
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in any environment. Filter as needed.
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how_to_implement: The detection is based on data that originates from Endpoint
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Detection and Response (EDR) agents. These agents are designed to provide
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security-related telemetry from the endpoints where the agent is installed. To
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implement this search, you must ingest logs that contain the process GUID,
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process name, and parent process. Additionally, you must ingest complete
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command-line executions. These logs must be processed using the appropriate
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Splunk Technology Add-ons that are specific to the EDR product. The logs must
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also be mapped to the `Processes` node of the `Endpoint` data model. Use the
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Splunk Common Information Model (CIM) to normalize the field names and speed
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up the data modeling process.
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known_false_positives: False positives may be high based on legitimate scripted
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code in any environment. Filter as needed.
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references:
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- https://thedfirreport.com/2021/10/18/icedid-to-xinglocker-ransomware-in-24-hours/
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- https://www.microsoft.com/security/blog/2022/01/15/destructive-malware-targeting-ukrainian-organizations/
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- RedLine Stealer
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- Log4Shell CVE-2021-44228
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- Interlock Rat
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- 0bj3ctivity Stealer
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asset_type: Endpoint
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cve:
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- CVE-2021-44228
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/icedid/cmd_carry_str_param/sysmon.log
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- data:
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https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/icedid/cmd_carry_str_param/sysmon.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: XmlWinEventLog
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name: Download Files Using Telegram
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id: 58194e28-ae5e-11eb-8912-acde48001122
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version: 7
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date: '2025-05-02'
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version: 8
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date: '2025-08-22'
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author: Teoderick Contreras, Splunk
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status: production
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type: TTP
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description:
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The following analytic detects suspicious file downloads by the Telegram
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application on a Windows system. It leverages Sysmon EventCode 15 to identify instances
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where Telegram.exe creates files with a Zone.Identifier, indicating a download.
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This activity is significant as it may indicate an adversary using Telegram to download
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malicious tools, such as network scanners, for further exploitation. If confirmed
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malicious, this behavior could lead to network mapping, lateral movement, and potential
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compromise of additional systems within the network.
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description: The following analytic detects suspicious file downloads by the
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Telegram application on a Windows system. It leverages Sysmon EventCode 15 to
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identify instances where Telegram.exe creates files with a Zone.Identifier,
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indicating a download. This activity is significant as it may indicate an
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adversary using Telegram to download malicious tools, such as network
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scanners, for further exploitation. If confirmed malicious, this behavior
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could lead to network mapping, lateral movement, and potential compromise of
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additional systems within the network.
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data_source:
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- Sysmon EventID 15
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search:
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'`sysmon` EventCode= 15 process_name = "telegram.exe" TargetFilename = "*:Zone.Identifier"
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- Sysmon EventID 15
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search: '`sysmon` EventCode= 15 process_name = "telegram.exe" TargetFilename = "*:Zone.Identifier"
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| stats count min(_time) as firstTime max(_time) as lastTime by dest dvc file_hash
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file_name file_path process_exec process_guid process_id process_name process_path
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signature signature_id user_id vendor_product Contents Image | `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)` | `download_files_using_telegram_filter`'
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how_to_implement:
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To successfully implement this search, you need to be ingesting
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logs with the process name and TargetFilename from your endpoints or Events that
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monitor filestream events which is happened when process download something. (EventCode
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15) If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon
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TA.
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known_false_positives:
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normal download of file in telegram app. (if it was a common
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app in network)
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how_to_implement: To successfully implement this search, you need to be
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ingesting logs with the process name and TargetFilename from your endpoints or
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Events that monitor filestream events which is happened when process download
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something. (EventCode 15) If you are using Sysmon, you must have at least
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version 6.0.4 of the Sysmon TA.
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known_false_positives: normal download of file in telegram app. (if it was a
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common app in network)
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references:
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- https://thedfirreport.com/2020/04/20/sqlserver-or-the-miner-in-the-basement/
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- https://thedfirreport.com/2020/04/20/sqlserver-or-the-miner-in-the-basement/
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drilldown_searches:
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- name: View the detection results for - "$dest$"
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search: '%original_detection_search% | search dest = "$dest$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$dest$"
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search:
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'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$")
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starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime
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values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories)
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as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic)
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as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View the detection results for - "$dest$"
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search: '%original_detection_search% | search dest = "$dest$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$dest$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$")
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starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime
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values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories)
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as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic)
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as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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rba:
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message: Suspicious files were downloaded with the Telegram application on $dest$
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message: Suspicious files were downloaded with the Telegram application on
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$dest$
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risk_objects:
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- field: dest
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type: system
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score: 49
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- field: dest
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type: system
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score: 49
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threat_objects: []
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tags:
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analytic_story:
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- Phemedrone Stealer
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- Crypto Stealer
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- Snake Keylogger
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- XMRig
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- Water Gamayun
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- Phemedrone Stealer
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- Crypto Stealer
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- Snake Keylogger
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- XMRig
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- Water Gamayun
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- 0bj3ctivity Stealer
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asset_type: Endpoint
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mitre_attack_id:
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- T1105
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- T1105
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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security_domain: endpoint
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/minergate/windows-sysmon.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: XmlWinEventLog
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- name: True Positive Test
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attack_data:
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- data:
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https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/minergate/windows-sysmon.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: XmlWinEventLog

detections/endpoint/malicious_powershell_process___execution_policy_bypass.yml

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name: Malicious PowerShell Process - Execution Policy Bypass
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id: 9be56c82-b1cc-4318-87eb-d138afaaca39
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version: '14'
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date: '2025-05-06'
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version: 15
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date: '2025-08-22'
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author: Rico Valdez, Mauricio Velazco, Splunk
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status: production
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type: Anomaly
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description: The following analytic detects PowerShell processes initiated with parameters
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that bypass the local execution policy for scripts. It leverages data from Endpoint
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Detection and Response (EDR) agents, focusing on command-line executions containing
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specific flags like "-ex" or "bypass." This activity is significant because bypassing
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execution policies is a common tactic used by attackers to run malicious scripts
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undetected. If confirmed malicious, this could allow an attacker to execute arbitrary
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code, potentially leading to further system compromise, data exfiltration, or persistent
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access within the environment.
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description: The following analytic detects PowerShell processes initiated with
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parameters that bypass the local execution policy for scripts. It leverages
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data from Endpoint Detection and Response (EDR) agents, focusing on
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command-line executions containing specific flags like "-ex" or "bypass." This
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activity is significant because bypassing execution policies is a common
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tactic used by attackers to run malicious scripts undetected. If confirmed
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malicious, this could allow an attacker to execute arbitrary code, potentially
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leading to further system compromise, data exfiltration, or persistent access
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within the environment.
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data_source:
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- Sysmon EventID 1
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- Windows Event Log Security 4688
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Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product
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| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
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| `malicious_powershell_process___execution_policy_bypass_filter`'
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how_to_implement: The detection is based on data that originates from Endpoint Detection
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and Response (EDR) agents. These agents are designed to provide security-related
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telemetry from the endpoints where the agent is installed. To implement this search,
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you must ingest logs that contain the process GUID, process name, and parent process.
35-
Additionally, you must ingest complete command-line executions. These logs must
36-
be processed using the appropriate Splunk Technology Add-ons that are specific to
37-
the EDR product. The logs must also be mapped to the `Processes` node of the `Endpoint`
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data model. Use the Splunk Common Information Model (CIM) to normalize the field
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names and speed up the data modeling process.
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known_false_positives: There may be legitimate reasons to bypass the PowerShell execution
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policy. The PowerShell script being run with this parameter should be validated
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to ensure that it is legitimate.
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how_to_implement: The detection is based on data that originates from Endpoint
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Detection and Response (EDR) agents. These agents are designed to provide
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security-related telemetry from the endpoints where the agent is installed. To
35+
implement this search, you must ingest logs that contain the process GUID,
36+
process name, and parent process. Additionally, you must ingest complete
37+
command-line executions. These logs must be processed using the appropriate
38+
Splunk Technology Add-ons that are specific to the EDR product. The logs must
39+
also be mapped to the `Processes` node of the `Endpoint` data model. Use the
40+
Splunk Common Information Model (CIM) to normalize the field names and speed
41+
up the data modeling process.
42+
known_false_positives: There may be legitimate reasons to bypass the PowerShell
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execution policy. The PowerShell script being run with this parameter should
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be validated to ensure that it is legitimate.
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references:
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- https://www.microsoft.com/en-us/security/blog/2023/05/24/volt-typhoon-targets-us-critical-infrastructure-with-living-off-the-land-techniques/
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drilldown_searches:
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- Salt Typhoon
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- XWorm
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- DarkCrystal RAT
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- 0bj3ctivity Stealer
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asset_type: Endpoint
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mitre_attack_id:
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- T1059.001
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059.001/encoded_powershell/windows-sysmon.log
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- data:
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https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059.001/encoded_powershell/windows-sysmon.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: XmlWinEventLog

detections/endpoint/non_firefox_process_access_firefox_profile_dir.yml

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name: Non Firefox Process Access Firefox Profile Dir
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id: e6fc13b0-1609-11ec-b533-acde48001122
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version: 11
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date: '2025-07-16'
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version: 12
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date: '2025-08-22'
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author: Teoderick Contreras, Splunk
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status: production
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type: Anomaly
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description: The following analytic detects non-Firefox processes accessing the Firefox
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profile directory, which contains sensitive user data such as login credentials,
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browsing history, and cookies. It leverages Windows Security Event logs, specifically
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event code 4663, to monitor access attempts. This activity is significant because
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it may indicate attempts by malware, such as RATs or trojans, to harvest user information.
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If confirmed malicious, this behavior could lead to data exfiltration, unauthorized
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access to user accounts, and further compromise of the affected system.
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description: The following analytic detects non-Firefox processes accessing the
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Firefox profile directory, which contains sensitive user data such as login
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credentials, browsing history, and cookies. It leverages Windows Security
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Event logs, specifically event code 4663, to monitor access attempts. This
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activity is significant because it may indicate attempts by malware, such as
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RATs or trojans, to harvest user information. If confirmed malicious, this
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behavior could lead to data exfiltration, unauthorized access to user
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accounts, and further compromise of the affected system.
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data_source:
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- Windows Event Log Security 4663
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search: '`wineventlog_security` EventCode=4663 NOT (ProcessName IN ("*\\firefox.exe",
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"*\\explorer.exe", "*sql*")) ObjectName="*\\AppData\\Roaming\\Mozilla\\Firefox\\Profiles*"
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| stats count min(_time) as firstTime max(_time) as lastTime by ObjectName ObjectType
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ProcessName AccessMask EventCode dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
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| `non_firefox_process_access_firefox_profile_dir_filter`'
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how_to_implement: To successfully implement this search, you must ingest Windows Security
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Event logs and track event code 4663. For 4663, enable "Audit Object Access" in
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Group Policy. Then check the two boxes listed for both "Success" and "Failure."
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known_false_positives: other browser not listed related to firefox may catch by this
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rule.
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how_to_implement: To successfully implement this search, you must ingest Windows
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Security Event logs and track event code 4663. For 4663, enable "Audit Object
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Access" in Group Policy. Then check the two boxes listed for both "Success"
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and "Failure."
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known_false_positives: other browser not listed related to firefox may catch by
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this rule.
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references: []
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drilldown_searches:
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- name: View the detection results for - "$dest$"
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- FIN7
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- Snake Keylogger
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- China-Nexus Threat Activity
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- 0bj3ctivity Stealer
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asset_type: Endpoint
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mitre_attack_id:
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- T1555.003
@@ -76,6 +79,7 @@ tags:
7679
tests:
7780
- name: True Positive Test
7881
attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1555/non_chrome_process_accessing_chrome_default_dir/windows-xml.log
82+
- data:
83+
https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1555/non_chrome_process_accessing_chrome_default_dir/windows-xml.log
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source: XmlWinEventLog:Security
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sourcetype: XmlWinEventLog

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