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Description

The following analytic detects a behavior where a process name consists only of a single letter that helps to detect potential threats earlier and mitigate the risks. This detection is important because it indicates the presence of malware or an attacker attempting to evade detection by using a process name that is difficult to identify or track so that he can carry out malicious activities such as data theft or ransomware attacks. False positives might occur since there might be legitimate uses of single-letter process names in your environment. Next steps include reviewing the process details and investigating any suspicious activity upon triage.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2020-12-08
  • Author: David Dorsey, Splunk
  • ID: a4214f0b-e01c-41bc-8cc4-d2b71e3056b4

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1204 User Execution Execution
T1204.002 Malicious File Execution
Kill Chain Phase
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE
1
2
3
4
5
6
7
8
9
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest, Processes.user, Processes.process, Processes.process_name 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(lastTime)` 
| `security_content_ctime(firstTime)` 
| eval process_name_length = len(process_name), endExe = if(substr(process_name, -4) == ".exe", 1, 0) 
| search process_name_length=5 AND endExe=1 
| table count, firstTime, lastTime, dest, user, process, process_name 
| `single_letter_process_on_endpoint_filter`

Macros

The SPL above uses the following Macros:

:information_source: single_letter_process_on_endpoint_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.process
  • Processes.process_name

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

Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
63.0 70 90 A suspicious process $process_name$ with single letter in host $dest$

:information_source: 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: 3