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 |
Detection: Detect SharpHound File Modifications
Description
The following analytic detects the creation of files typically associated with SharpHound, a reconnaissance tool used for gathering domain and trust data. It leverages file modification events from the Endpoint.Filesystem data model, focusing on default file naming patterns like *_BloodHound.zip
and various JSON files. This activity is significant as it indicates potential domain enumeration, which is a precursor to more targeted attacks. If confirmed malicious, an attacker could gain detailed insights into the domain structure, facilitating lateral movement and privilege escalation.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where Filesystem.file_name IN ("*bloodhound.zip", "*_computers.json", "*_gpos.json", "*_domains.json", "*_users.json", "*_groups.json", "*_ous.json", "*_containers.json") by Filesystem.file_create_time Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.dest Filesystem.user
3| `drop_dm_object_name(Filesystem)`
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `detect_sharphound_file_modifications_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Sysmon EventID 11 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational' |
N/A |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
detect_sharphound_file_modifications_filter | search * |
detect_sharphound_file_modifications_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
To successfully implement this search you need to be ingesting information on file modifications that include the name of the process, and file, responsible for the changes from your endpoints into the Endpoint
datamodel in the Filesystem
node.
Known False Positives
False positives should be limited as the analytic is specific to a filename with extension .zip. Filter as needed.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Potential SharpHound file modifications identified on $dest$ | 24 | 30 | 80 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
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: GitHub | Version: 4