Excessive Usage Of Net App
Description
This analytic identifies excessive usage of net.exe
or net1.exe
within a bucket of time (1 minute). This behavior was seen in a Monero incident where the adversary attempts to create many users, delete and disable users as part of its malicious behavior.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2023-06-13
- Author: Teoderick Contreras, Splunk
- ID: 45e52536-ae42-11eb-b5c6-acde48001122
Annotations
Kill Chain Phase
- Actions On Objectives
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_net` by Processes.process_name Processes.parent_process_name Processes.original_file_name Processes.dest Processes.user _time span=1m
| where count >=10
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `excessive_usage_of_net_app_filter`
Macros
The SPL above uses the following Macros:
excessive_usage_of_net_app_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
unknown. Filter as needed. Modify the time span as needed.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
28.0 | 40 | 70 | Excessive usage of net1.exe or net.exe within 1m, with command line $process$ has been detected 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