System Information Discovery Detection
Description
Detect system information discovery techniques used by attackers to understand configurations of the system to further exploit it.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-09-07
- Author: Patrick Bareiss, Splunk
- ID: 8e99f89e-ae58-4ebc-bf52-ae0b1a277e72
Annotations
Kill Chain Phase
- Actions on Objectives
NIST
- DE.CM
CIS20
- CIS 6
- CIS 8
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="*wmic* qfe*" OR Processes.process=*systeminfo* OR Processes.process=*hostname*) by Processes.user Processes.process_name Processes.process Processes.dest Processes.parent_process_name
| `drop_dm_object_name(Processes)`
| eventstats dc(process) as dc_processes_by_dest by dest
| where dc_processes_by_dest > 2
| stats values(process) as process min(firstTime) as firstTime max(lastTime) as lastTime by user, dest parent_process_name
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `system_information_discovery_detection_filter`
Macros
The SPL above uses the following Macros:
system_information_discovery_detection_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Supported Add-on (TA)
List of Splunk Add-on’s tested to work with the analytic.
Required fields
List of fields required to use this analytic.
- _time
- Processes.process
- Processes.user
- Processes.process_name
- Processes.dest
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.
Known False Positives
Administrators debugging servers
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
15.0 | 30 | 50 | Potential system information discovery behavior on $dest$ by $User$ |
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: 2