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Description

This detection targets behaviors observed in post exploit kits like Meterpreter and Koadic that are run in memory. We have observed that these tools must invoke an excessive number of taskhost.exe and taskhostex.exe processes to complete various actions (discovery, lateral movement, etc.). It is extremely uncommon in the course of normal operations to see so many distinct taskhost and taskhostex processes running concurrently in a short time frame.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2021-06-07
  • Author: Michael Hart
  • ID: f443dac2-c7cf-11eb-ab51-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1059 Command and Scripting Interpreter Execution
Kill Chain Phase
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` values(Processes.process_id) as process_ids  min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes WHERE Processes.process_name = "taskhost.exe" OR Processes.process_name = "taskhostex.exe" BY Processes.dest Processes.process_name _time span=1h 
| `drop_dm_object_name(Processes)` 
| eval pid_count=mvcount(process_ids) 
| eval taskhost_count_=if(process_name == "taskhost.exe", pid_count, 0) 
| eval taskhostex_count_=if(process_name == "taskhostex.exe", pid_count, 0) 
| stats sum(taskhost_count_) as taskhost_count, sum(taskhostex_count_) as taskhostex_count by _time, dest, firstTime, lastTime 
| where taskhost_count > 10 and taskhostex_count > 10 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `excessive_number_of_taskhost_processes_filter`

Macros

The SPL above uses the following Macros:

:information_source: excessive_number_of_taskhost_processes_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.

  • _time
  • Processes.process_id
  • Processes.process_name
  • Processes.dest
  • Processes.user

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, administrative actions or certain applications may run many instances of taskhost and taskhostex concurrently. Filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
56.0 80 70 An excessive amount of $process_name$ was executed on $dest$ indicative of suspicious behavior.

: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.

Reference

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

source | version: 1