The following detection identifies the latest behavior utilized by different malware families (including TA551, AsyncRat, Redline and DCRAT). This detection identifies onenote Office Product spawning
mshta.exe. In malicious instances, the command-line of
mshta.exe will contain the
hta file locally, or a URL to the remote destination. In addition, Threat Research has released a detections identifying suspicious use of
mshta.exe. In this instance, we narrow our detection down to the Office suite as a parent process. During triage, review all file modifications. Capture and analyze any artifacts on disk. The Office Product, or
mshta.exe will have reached out to a remote destination, capture and block the IPs or domain. Review additional parallel processes for further activity.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2023-01-24
- Author: Teoderick Contreras, Splunk
- ID: 35aeb0e7-7de5-444a-ac45-24d6788796ec
Kill Chain Phase
- CIS 10
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name IN ("onenote.exe", "onenotem.exe") `process_mshta` by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_spearphishing_attachment_onenote_spawn_mshta_filter`
The SPL above uses the following Macros:
windows_spearphishing_attachment_onenote_spawn_mshta_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
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
No false positives known. Filter as needed.
Associated Analytic Story
|81.0||90||90||office parent process $parent_process_name$ will execute a suspicious child process $process_name$ with process id $process_id$ in host $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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