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Description

The following analytic detects the usage of the SharpHound binary by identifying its original filename, SharpHound.exe, and the process name. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process metadata and command-line executions. SharpHound is a tool used for Active Directory enumeration, often by attackers during the reconnaissance phase. If confirmed malicious, this activity could allow an attacker to map out the network, identify high-value targets, and plan further attacks, potentially leading to privilege escalation and lateral movement within the environment.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-14
  • Author: Michael Haag, Splunk
  • ID: dd04b29a-beed-11eb-87bc-acde48001122

Annotations

ATT&CK

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
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=sharphound.exe OR Processes.original_file_name=SharpHound.exe) by Processes.dest Processes.user Processes.parent_process_name Processes.original_file_name 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_usage_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_sharphound_usage_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.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.original_file_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_path
  • Processes.process_path
  • 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

False positives should be limited as this is specific to a file attribute not used by anything else. Filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
24.0 30 80 Potential SharpHound binary identified on $dest$

: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: 4