Detection: Ping Sleep Batch Command

Updated Date: 2024-05-30 ID: ce058d6c-79f2-11ec-b476-acde48001122 Author: Teoderick Contreras, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies the execution of ping sleep batch commands. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process command-line details. This activity is significant as it indicates an attempt to delay malicious code execution, potentially evading detection or sandbox analysis. If confirmed malicious, this technique allows attackers to bypass security measures, making it harder to detect and analyze their activities, thereby increasing the risk of prolonged unauthorized access and potential data exfiltration.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_ping` (Processes.parent_process = "*ping*" Processes.parent_process = *-n* Processes.parent_process="* Nul*"Processes.parent_process="*>*") OR (Processes.process = "*ping*" Processes.process = *-n* Processes.process="* Nul*"Processes.process="*>*") by Processes.parent_process_name Processes.parent_process Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.process_guid Processes.user Processes.dest 
3| `drop_dm_object_name("Processes")` 
4| `security_content_ctime(firstTime)` 
5|`security_content_ctime(lastTime)` 
6| `ping_sleep_batch_command_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
process_ping (Processes.process_name=ping.exe OR Processes.original_file_name=ping.exe)
ping_sleep_batch_command_filter search *
ping_sleep_batch_command_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1497 Virtualization/Sandbox Evasion Defense Evasion
T1497.003 Time Based Evasion Discovery
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
Darkhotel

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 True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

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

Administrator or network operator may execute this command. Please update the filter macros to remove false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
suspicious $process$ commandline run in $dest$ 36 60 60
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog

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: 2