ID | Technique | Tactic |
---|
Detection: Suspicious File Write
DEPRECATED DETECTION
This detection has been marked as deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported. If you have any questions or concerns, please reach out to us at research@splunk.com.
Description
The search looks for files created with names that have been linked to malicious activity.
Search
1
2| tstats `security_content_summariesonly` count values(Filesystem.action) as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest
3| `security_content_ctime(lastTime)`
4| `security_content_ctime(firstTime)`
5| `drop_dm_object_name(Filesystem)`
6| `suspicious_writes`
7| `suspicious_file_write_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Sysmon EventID 11 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational' |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
suspicious_file_write_filter | search * |
suspicious_file_write_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 Risk Event | False |
Implementation
You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response product, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor.
Known False Positives
It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
tbd | 25 | 50 | 50 |
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | Not Applicable | N/A | N/A | N/A |
Unit | ❌ Failing | N/A | N/A |
N/A |
Integration | ❌ Failing | N/A | N/A |
N/A |
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: 5