splunk-security_content/docs/_posts/2021-06-01-detect_sharphound_command-line_arguments.md

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Detect SharpHound Command-Line Arguments	Domain Account, Local Groups, Domain Trust Discovery, Local Account, Account Discovery, Domain Groups, Permission Groups Discovery	Endpoint	2021-06-01	true		Domain Account Discovery Local Groups Discovery Domain Trust Discovery Discovery Local Account Discovery Account Discovery Discovery Domain Groups Discovery Permission Groups Discovery Discovery Splunk Enterprise Splunk Enterprise Security Splunk Cloud Endpoint

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Description

The following analytic identifies common command-line arguments used by SharpHound -collectionMethod and invoke-bloodhound. Being the script is FOSS, function names may be modified, but these changes are dependent upon the operator. In most instances the defaults are used. This analytic works to identify the common command-line attributes used. It does not cover the entirety of every argument in order to avoid false positives.

• Type: TTP
• Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
• Datamodel: Endpoint
• Last Updated: 2021-06-01
• Author: Michael Haag, Splunk
• ID: a0bdd2f6-c2ff-11eb-b918-acde48001122

ATT&CK

ID	Technique	Tactic
T1087.002	Domain Account	Discovery

| T1069.001 | Local Groups | Discovery |

| T1482 | Domain Trust Discovery | Discovery |

| T1087.001 | Local Account | Discovery |

| T1087 | Account Discovery | Discovery |

| T1069.002 | Domain Groups | Discovery |

| T1069 | Permission Groups Discovery | Discovery |

Search

| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process IN ("*-collectionMethod*","*invoke-bloodhound*") by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `detect_sharphound_command_line_arguments_filter`

Associated Analytic Story

• Discovery Techniques
• Ransomware

How To Implement

To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint datamodel in the Processes node.

Required field

• _time
• Processes.dest
• Processes.user
• Processes.parent_process
• Processes.process_name
• Processes.process
• Processes.process_id
• Processes.parent_process_id

Kill Chain Phase

• Reconnaissance

Known False Positives

False positives should be limited as the arguments used are specific to SharpHound. Filter as needed or add more command-line arguments as needed.

RBA

Risk Score	Impact	Confidence	Message
24.0	30	80	Possible SharpHound command-Line arguments identified on dest

Reference

• https://attack.mitre.org/software/S0521/
• https://thedfirreport.com/?s=bloodhound
• https://github.com/BloodHoundAD/BloodHound/tree/master/Collectors
• https://github.com/BloodHoundAD/SharpHound3
• https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1059.001/T1059.001.md#atomic-test-2---run-bloodhound-from-local-disk

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

• https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059.001/sharphound/windows-sysmon.log

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