Detection: Windows PaperCut NG Spawn Shell

Updated Date: 2024-08-15 ID: a602d9a2-aaea-45f8-bf0f-d851168d61ca Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects instances where the PaperCut NG application (pc-app.exe) spawns a Windows shell, such as cmd.exe or PowerShell. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process creation events where the parent process is pc-app.exe. This activity is significant as it may indicate an attacker attempting to gain unauthorized access or execute malicious commands on the system. If confirmed malicious, this could lead to unauthorized code execution, privilege escalation, or further compromise of the affected environment.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=pc-app.exe `process_cmd` OR `process_powershell` OR Processes.process_name=java.exe by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `windows_papercut_ng_spawn_shell_filter`

Data Source

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

Macros Used

Name Value
process_cmd (Processes.process_name=cmd.exe OR Processes.original_file_name=Cmd.Exe)
windows_papercut_ng_spawn_shell_filter search *
windows_papercut_ng_spawn_shell_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
T1059 Command and Scripting Interpreter Execution
T1190 Exploit Public-Facing Application Initial Access
T1133 External Remote Services Initial Access
KillChainPhase.DELIVERY
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
APT19
APT32
APT37
APT39
Dragonfly
FIN5
FIN6
FIN7
Fox Kitten
Ke3chang
OilRig
Stealth Falcon
Whitefly
Windigo
APT28
APT29
APT39
APT41
APT5
Axiom
BackdoorDiplomacy
BlackTech
Blue Mockingbird
Cinnamon Tempest
Dragonfly
Earth Lusca
FIN13
FIN7
Fox Kitten
GALLIUM
GOLD SOUTHFIELD
HAFNIUM
Ke3chang
Kimsuky
Magic Hound
Moses Staff
MuddyWater
Rocke
Sandworm Team
Threat Group-3390
ToddyCat
Volatile Cedar
Volt Typhoon
menuPass
APT18
APT28
APT29
APT41
Akira
Chimera
Dragonfly
FIN13
FIN5
GALLIUM
GOLD SOUTHFIELD
Ke3chang
Kimsuky
LAPSUS$
Leviathan
OilRig
Sandworm Team
Scattered Spider
TeamTNT
Threat Group-3390
Wizard Spider

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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

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

False positives may be present, but most likely not. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
The PaperCut NG application has spawned a shell $process_name$ on endpoint $dest$ by $user$. 90 100 90
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: 3