This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

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The following analytic detects the use of certutil to download software, a behavior exhibited by the threat actor Flax Typhoon. This actor deploys a VPN connection by downloading an executable file for SoftEther VPN from their network infrastructure using one of several LOLBins, including certutil. The actor then uses the Service Control Manager (SCM) to create a Windows service that launches the VPN connection automatically when the system starts. This behavior allows the actor to monitor the availability of the compromised system and establish an RDP connection. This analytic identifies this behavior by monitoring for the use of certutil in conjunction with the downloading of software. This behavior is worth identifying for a SOC as it indicates a potential compromise of the system and the establishment of a persistent threat. If a true positive is found, it suggests an attacker has gained access to the environment and is attempting to maintain that access, potentially leading to further malicious activities such as data theft or ransomware attacks. Be aware of potential false positives - legitimate uses of certutil in your environment may cause benign activities to be flagged. Upon triage, review the command executed and look for concurrent processes to identify the attack source. This approach helps analysts detect potential threats earlier and mitigate the risks.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2023-08-25
  • Author: Michael Haag, Splunk
  • ID: dfc18a5a-946e-44ee-a373-c0f60d06e676




ID Technique Tactic
T1105 Ingress Tool Transfer Command And Control
Kill Chain Phase
  • Command and Control
  • DE.CM
  • CIS 10
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name IN ("sqlservr.exe", "sqlagent.exe", "sqlps.exe", "launchpad.exe", "sqldumper.exe") `process_certutil` (Processes.process=*urlcache* Processes.process=*split*) OR Processes.process=*urlcache* by Processes.dest Processes.user Processes.parent_process Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.original_file_name Processes.parent_process_id 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `windows_sql_spawning_certutil_filter`


The SPL above uses the following Macros:

:information_source: windows_sql_spawning_certutil_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • Processes.dest
  • Processes.user
  • Processes.parent_process
  • Processes.parent_process_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.original_file_name
  • Processes.parent_process_id

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

The occurrence of false positives should be minimal, given that the SQL agent does not typically download software using CertUtil.

Associated Analytic Story


Risk Score Impact Confidence Message
90.0 90 100 $process_name$ was launched on $dest$ by $user$. This behavior is uncommon with the SQL process identified.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.


Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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