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@@ -19,7 +19,7 @@ known_false_positives: Legitimate logon activity by authorized NTLM systems may
|
||||
references: []
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Endpoint
|
||||
automated_detection_testing: passed
|
||||
cis20:
|
||||
|
||||
@@ -36,7 +36,7 @@ tags:
|
||||
- DHS Report TA18-074A
|
||||
- HAFNIUM Group
|
||||
- DarkSide Ransomware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Endpoint
|
||||
automated_detection_testing: passed
|
||||
cis20:
|
||||
|
||||
@@ -33,7 +33,7 @@ tags:
|
||||
- DHS Report TA18-074A
|
||||
- HAFNIUM Group
|
||||
- DarkSide Ransomware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 90
|
||||
context:
|
||||
|
||||
@@ -8,7 +8,7 @@ datamodel:
|
||||
- Endpoint
|
||||
description: The following analytic identifies executable files (.exe or .dll) being
|
||||
written to Windows administrative SMB shares (Admin$, IPC$, C$). This represents
|
||||
suspicious behavior as its commonly user by tools like like PsExec/PaExec and others
|
||||
suspicious behavior as its commonly used by tools like like PsExec/PaExec and others
|
||||
to stage service binaries before creating and starting a Windows service on remote
|
||||
endpoints. Red Teams and adversaries alike may abuse administrative shares for lateral
|
||||
movement and remote code execution. The Trickbot malware family also implements
|
||||
@@ -31,7 +31,7 @@ references:
|
||||
- https://blog.whitehat.eu/2019/05/incident-trickbot-ryuk-2.html
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
- Trickbot
|
||||
automated_detection_testing: passed
|
||||
confidence: 100
|
||||
|
||||
@@ -36,7 +36,7 @@ references:
|
||||
- https://vk9-sec.com/impacket-remote-code-execution-rce-on-windows-from-linux/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 70
|
||||
context:
|
||||
|
||||
@@ -25,7 +25,7 @@ references:
|
||||
- https://docs.microsoft.com/en-us/powershell/module/microsoft.powershell.core/enter-pssession?view=powershell-7.2
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
confidence: 50
|
||||
context:
|
||||
- Source:Endpoint
|
||||
|
||||
@@ -23,7 +23,7 @@ references: []
|
||||
tags:
|
||||
analytic_story:
|
||||
- Hidden Cobra Malware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
- SamSam Ransomware
|
||||
product:
|
||||
- Splunk Phantom
|
||||
|
||||
@@ -40,7 +40,7 @@ references:
|
||||
- https://lolbas-project.github.io/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -0,0 +1,86 @@
|
||||
name: Possible Lateral Movement PowerShell Spawn
|
||||
id: cb909b3e-512b-11ec-aa31-3e22fbd008af
|
||||
version: 1
|
||||
date: '2021-11-29'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: TTP
|
||||
datamodel:
|
||||
- Endpoint
|
||||
description: The following analytic assists with identifying a PowerShell process
|
||||
spawned as a child or grand child process of commonly abused processes during lateral
|
||||
movement techniques including `services.exe`, `wmiprsve.exe`, `svchost.exe`, `wsmprovhost.exe`
|
||||
and `mmc.exe`. Legitimate Windows features such as the Service Control Manager,
|
||||
Windows Management Instrumentation, Task Scheduler, Windows Remote Management and
|
||||
the DCOM protocol can be abused to start a process on a remote endpoint. Looking
|
||||
for PowerShell spawned out of this processes may reveal a lateral movement attack.
|
||||
Red Teams and adversaries alike may abuse these services during a breach for lateral
|
||||
movement and remote code execution.
|
||||
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
|
||||
as lastTime from datamodel=Endpoint.Processes where (Processes.parent_process_name=wmiprvse.exe
|
||||
OR Processes.parent_process_name=services.exe OR Processes.parent_process_name=svchost.exe
|
||||
OR Processes.parent_process_name=wsmprovhost.exe OR Processes.parent_process_name=mmc.exe)
|
||||
(Processes.process_name=powershell.exe OR (Processes.process_name=cmd.exe AND Processes.process=*powershell.exe*)
|
||||
OR Processes.process_name=pwsh.exe OR (Processes.process_name=cmd.exe AND Processes.process=*pwsh.exe*))
|
||||
by Processes.dest Processes.user Processes.parent_process Processes.process_name
|
||||
Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)`
|
||||
| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `possible_lateral_movement_powershell_spawn_filter`'
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
logs with the process name, parent process, and command-line executions from your
|
||||
endpoints.
|
||||
known_false_positives: Legitimate applications may spawn PowerShell as a child process
|
||||
of the the identified processes. Filter as needed.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1021/003
|
||||
- https://attack.mitre.org/techniques/T1021/006/
|
||||
- https://attack.mitre.org/techniques/T1047/
|
||||
- https://attack.mitre.org/techniques/T1053.005/
|
||||
- https://attack.mitre.org/techniques/T1543/003/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
- Malicious PowerShell
|
||||
dataset:
|
||||
- https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1543.003/lateral_movement_powershell/windows-sysmon.log
|
||||
kill_chain_phases:
|
||||
- Lateral Movement
|
||||
- Malicious PowerShell
|
||||
mitre_attack_id:
|
||||
- T1021
|
||||
- T1021.003
|
||||
- T1021.006
|
||||
- T1047
|
||||
- T1053.005
|
||||
- T1543.003
|
||||
- T1059.001
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- Processes.dest
|
||||
- Processes.user
|
||||
- Processes.parent_process_name
|
||||
- Processes.parent_process
|
||||
- Processes.original_file_name
|
||||
- Processes.process_name
|
||||
- Processes.process
|
||||
- Processes.process_id
|
||||
- Processes.parent_process_path
|
||||
- Processes.process_path
|
||||
- Processes.parent_process_id
|
||||
security_domain: endpoint
|
||||
impact: 90
|
||||
confidence: 50
|
||||
risk_score: 45
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Lateral Movement
|
||||
message: A PowerShell process was spawned as a child process of typically abused
|
||||
processes on $dest$
|
||||
observable:
|
||||
- name: dest
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
automated_detection_testing: passed
|
||||
@@ -27,7 +27,7 @@ references:
|
||||
- https://www.cybereason.com/blog/dcom-lateral-movement-techniques
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 70
|
||||
context:
|
||||
|
||||
+1
-1
@@ -25,7 +25,7 @@ references:
|
||||
- https://www.cybereason.com/blog/dcom-lateral-movement-techniques
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 70
|
||||
context:
|
||||
|
||||
@@ -28,7 +28,7 @@ references:
|
||||
- https://pentestlab.blog/2018/05/15/lateral-movement-winrm/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 50
|
||||
context:
|
||||
|
||||
+1
-1
@@ -26,7 +26,7 @@ references:
|
||||
- https://pentestlab.blog/2018/05/15/lateral-movement-winrm/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 50
|
||||
context:
|
||||
|
||||
@@ -27,7 +27,7 @@ references:
|
||||
- https://attack.mitre.org/techniques/T1021/006/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -30,7 +30,7 @@ tags:
|
||||
analytic_story:
|
||||
- Ransomware
|
||||
- Suspicious WMI Use
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Endpoint
|
||||
automated_detection_testing: passed
|
||||
cis20:
|
||||
|
||||
@@ -27,7 +27,7 @@ references:
|
||||
- https://docs.microsoft.com/en-us/powershell/module/microsoft.powershell.management/invoke-wmimethod?view=powershell-5.1
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 70
|
||||
context:
|
||||
|
||||
+1
-1
@@ -25,7 +25,7 @@ references:
|
||||
- https://docs.microsoft.com/en-us/powershell/module/microsoft.powershell.management/invoke-wmimethod?view=powershell-5.1
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 70
|
||||
context:
|
||||
|
||||
@@ -29,7 +29,7 @@ references:
|
||||
- https://docs.microsoft.com/en-us/windows/win32/cimwin32prov/win32-scheduledjob?redirectedfrom=MSDN
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -26,7 +26,7 @@ references:
|
||||
- https://attack.mitre.org/techniques/T1053/005/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -27,7 +27,7 @@ known_false_positives: Administrators may create scheduled tasks on remote syste
|
||||
references: []
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
- NOBELIUM Group
|
||||
asset_type: Endpoint
|
||||
automated_detection_testing: passed
|
||||
|
||||
@@ -9,7 +9,7 @@ datamodel:
|
||||
description: The following analytic identifies `services.exe` spawning a LOLBAS execution
|
||||
process. When adversaries execute code on remote endpoints abusing the Service Control
|
||||
Manager and creating a remote malicious service, the executed command is spawned
|
||||
as a child processs of `services.exe`. The LOLBAS project documents Windows native
|
||||
as a child process of `services.exe`. The LOLBAS project documents Windows native
|
||||
binaries that can be abused by threat actors to perform tasks like executing malicious
|
||||
code. Looking for child processes of services.exe that are part of the LOLBAS project
|
||||
can help defenders identify lateral movement activity.
|
||||
@@ -40,7 +40,7 @@ references:
|
||||
- https://lolbas-project.github.io/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -0,0 +1,67 @@
|
||||
name: Short Lived Scheduled Task
|
||||
id: 6fa31414-546e-11ec-adfa-acde48001122
|
||||
version: 1
|
||||
date: '2021-12-03'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: TTP
|
||||
datamodel: []
|
||||
description: The following analytic leverages Windows Security EventCode 4698, `A
|
||||
scheduled task was created` and Windows Security EventCode 4699, `A scheduled task
|
||||
was deleted` to identify scheduled tasks created and deleted in less than 30 seconds.
|
||||
This behavior may represent a lateral movement attack abusing the Task Scheduler
|
||||
to obtain code execution. Red Teams and adversaries alike may abuse the Task Scheduler
|
||||
for lateral movement and remote code execution.
|
||||
search: ' `wineventlog_security` EventCode=4698 OR EventCode=4699 | xmlkv Message
|
||||
| transaction Task_Name startswith=(EventCode=4698) endswith=(EventCode=4699) |
|
||||
eval short_lived=case((duration<30),"TRUE") | search short_lived = TRUE | table
|
||||
_time, ComputerName, Account_Name, Command, Task_Name, short_lived | `short_lived_scheduled_task_filter` '
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
Windows Security Event Logs with 4698 EventCode enabled. The Windows TA is also
|
||||
required.
|
||||
known_false_positives: Although uncommon, legitimate applications may create and delete
|
||||
a Scheduled Task within 30 seconds. Filter as needed.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1053/005/
|
||||
- https://docs.microsoft.com/en-us/windows/win32/taskschd/about-the-task-scheduler
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
dataset:
|
||||
- https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1053.005/lateral_movement/windows-security.log
|
||||
kill_chain_phases:
|
||||
- Lateral Movement
|
||||
mitre_attack_id:
|
||||
- T1053.005
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- dest
|
||||
- ComputerName
|
||||
- Account_Name
|
||||
- Task_Name
|
||||
- Description
|
||||
- Command
|
||||
security_domain: endpoint
|
||||
impact: 90
|
||||
confidence: 90
|
||||
risk_score: 81
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Execution
|
||||
- Stage:Persistence
|
||||
- Stage:Privilege Escalation
|
||||
- Stage:Lateral Movement
|
||||
message: A windows scheduled task was created and deleted in 30 seconds on $ComputerName$
|
||||
observable:
|
||||
- name: dest
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
- name: Command
|
||||
type: Command
|
||||
role:
|
||||
- Target
|
||||
automated_detection_testing: passed
|
||||
@@ -49,7 +49,7 @@ references:
|
||||
- https://www.offensive-security.com/metasploit-unleashed/psexec-pass-hash/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Windows
|
||||
cis20:
|
||||
- CIS 16
|
||||
|
||||
@@ -51,7 +51,7 @@ references:
|
||||
- https://www.offensive-security.com/metasploit-unleashed/psexec-pass-hash/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Windows
|
||||
cis20:
|
||||
- CIS 16
|
||||
|
||||
@@ -9,7 +9,7 @@ datamodel:
|
||||
description: The following analytic identifies `svchost.exe` spawning a LOLBAS execution
|
||||
process. When adversaries execute code on remote endpoints abusing the Task Scheduler
|
||||
and creating a malicious remote scheduled task, the executed command is spawned
|
||||
as a child processs of `svchost.exe`. The LOLBAS project documents Windows native
|
||||
as a child process of `svchost.exe`. The LOLBAS project documents Windows native
|
||||
binaries that can be abused by threat actors to perform tasks like executing malicious
|
||||
code. Looking for child processes of svchost.exe that are part of the LOLBAS project
|
||||
can help defenders identify lateral movement activity.
|
||||
@@ -39,7 +39,7 @@ references:
|
||||
- https://lolbas-project.github.io/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -28,7 +28,7 @@ references:
|
||||
tags:
|
||||
analytic_story:
|
||||
- Clop Ransomware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 80
|
||||
context:
|
||||
|
||||
@@ -26,7 +26,7 @@ references:
|
||||
- https://pentestlab.blog/2020/07/21/lateral-movement-services/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -28,7 +28,7 @@ references:
|
||||
- https://attack.mitre.org/techniques/T1543/003/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -26,7 +26,7 @@ references:
|
||||
- https://attack.mitre.org/techniques/T1543/003/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -47,7 +47,7 @@ tags:
|
||||
- Ransomware
|
||||
- Ryuk Ransomware
|
||||
- IcedID
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 100
|
||||
context:
|
||||
|
||||
@@ -8,7 +8,7 @@ datamodel:
|
||||
- Endpoint
|
||||
description: The following analytic identifies `wmiprsve.exe` spawning a LOLBAS execution
|
||||
process. When adversaries execute code on remote endpoints abusing Windows Management
|
||||
Instrumention (WMI), the executed command is spawned as a child processs of `wmiprvse.exe`.
|
||||
Instrumentation (WMI), the executed command is spawned as a child process of `wmiprvse.exe`.
|
||||
The LOLBAS project documents Windows native binaries that can be abused by threat
|
||||
actors to perform tasks like executing malicious code. Looking for child processes
|
||||
of wmiprvse.exe that are part of the LOLBAS project can help defenders identify
|
||||
@@ -40,7 +40,7 @@ references:
|
||||
- https://lolbas-project.github.io/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -40,7 +40,7 @@ references:
|
||||
- https://pentestlab.blog/2018/05/15/lateral-movement-winrm/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
automated_detection_testing: passed
|
||||
confidence: 60
|
||||
context:
|
||||
|
||||
@@ -0,0 +1,63 @@
|
||||
name: Randomly Generated Scheduled Task Name
|
||||
id: 9d22a780-5165-11ec-ad4f-3e22fbd008af
|
||||
version: 1
|
||||
date: '2021-11-29'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: Hunting
|
||||
datamodel:
|
||||
- Endpoint
|
||||
description: The following hunting analytic leverages Event ID 4698, `A scheduled task was created`,
|
||||
to identify the creation of a Scheduled Task with a suspicious, high entropy, Task Name. To achieve this,
|
||||
this analytic also leverages the `ut_shannon` function from the URL ToolBox Splunk application.
|
||||
Red teams and adversaries alike may abuse the Task Scheduler to create and start a remote Scheduled Task
|
||||
and obtain remote code execution. To achieve this goal, tools like Impacket or Crapmapexec,
|
||||
typically create a Scheduled Task with a random task name on the victim host. This hunting analytic may help
|
||||
defenders identify Scheduled Tasks created as part of a lateral movement attack. The entropy threshold `ut_shannon > 3`
|
||||
should be customized by users. The Command field can be used to determine if the task has malicious intent or not.
|
||||
search: ' `wineventlog_security` EventCode=4698 | xmlkv Message
|
||||
| lookup ut_shannon_lookup word as Task_Name
|
||||
| where ut_shannon > 3
|
||||
| table _time, dest, Task_Name, ut_shannon, Command, Author, Enabled, Hidden | `randomly_generated_scheduled_task_name_filter`'
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
Windows Security Event Logs with 4698 EventCode enabled. The Windows TA as well as the URL ToolBox application are also
|
||||
required.
|
||||
known_false_positives: Legitimate applications may use random Scheduled Task names.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1053/005/
|
||||
- https://splunkbase.splunk.com/app/2734/
|
||||
- https://en.wikipedia.org/wiki/Entropy_(information_theory)
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
kill_chain_phases:
|
||||
- Privilege Escalation
|
||||
- Lateral Movement
|
||||
- Persistence
|
||||
mitre_attack_id:
|
||||
- T1053
|
||||
- T1053.005
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- dest
|
||||
- Task_Name
|
||||
- Description
|
||||
- Command
|
||||
security_domain: endpoint
|
||||
impact: 90
|
||||
confidence: 50
|
||||
risk_score: 45
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Persistence
|
||||
- Stage:Lateral Movement
|
||||
message: 'A windows scheduled task with a suspicious task name was created on $dest$'
|
||||
observable:
|
||||
- name: dest
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
|
||||
@@ -0,0 +1,65 @@
|
||||
name: Randomly Generated Windows Service Name
|
||||
id: 2032a95a-5165-11ec-a2c3-3e22fbd008af
|
||||
version: 1
|
||||
date: '2021-11-29'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: Hunting
|
||||
datamodel:
|
||||
- Endpoint
|
||||
description: The following hunting analytic leverages Event ID 7045, `A new service was installed in the system`,
|
||||
to identify the installation of a Windows Service with a suspicious, high entropy, Service Name. To achieve this,
|
||||
this analytic also leverages the `ut_shannon` function from the URL ToolBox Splunk application.
|
||||
Red teams and adversaries alike may abuse the Service Control Manager to create and start a remote Windows Service
|
||||
and obtain remote code execution. To achieve this goal, some tools like Metasploit, Cobalt Strike and Impacket,
|
||||
typically create a Windows Service with a random service name on the victim host. This hunting analytic may help
|
||||
defenders identify Windows Services installed as part of a lateral movement attack. The entropy threshold `ut_shannon > 3`
|
||||
should be customized by users. The Service_File_Name field can be used to determine if the Windows Service has malicious intent or not.
|
||||
search: ' `wineventlog_system` EventCode=7045
|
||||
| lookup ut_shannon_lookup word as Service_Name
|
||||
| where ut_shannon > 3
|
||||
| table EventCode ComputerName Service_Name ut_shannon Service_Start_Type Service_Type Service_File_Name | `randomly_generated_windows_service_name_filter` '
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
logs with the Service name, Service File Name Service Start type, and Service Type
|
||||
from your endpoints. The Windows TA as well as the URL ToolBox application are also
|
||||
required.
|
||||
known_false_positives: Legitimate applications may use random Windows Service names.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1543/003/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
kill_chain_phases:
|
||||
- Privilege Escalation
|
||||
- Lateral Movement
|
||||
mitre_attack_id:
|
||||
- T1543
|
||||
- T1543.003
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- EventCode
|
||||
- ComputerName
|
||||
- Service_File_Name
|
||||
- Service_Type
|
||||
- Service_Name
|
||||
- Service_Start_Type
|
||||
security_domain: endpoint
|
||||
impact: 90
|
||||
confidence: 50
|
||||
risk_score: 45
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Lateral Movement
|
||||
message: A Windows Service with a suspicious service name was installed on $ComputerName$
|
||||
observable:
|
||||
- name: Service_File_Name
|
||||
type: Other
|
||||
role:
|
||||
- Other
|
||||
- name: ComputerName
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
@@ -28,7 +28,7 @@ references: []
|
||||
tags:
|
||||
analytic_story:
|
||||
- Hidden Cobra Malware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Endpoint
|
||||
cis20:
|
||||
- CIS 3
|
||||
|
||||
+70
@@ -0,0 +1,70 @@
|
||||
name: Unusual Number of Computer Service Tickets Requested
|
||||
id: ac3b81c0-52f4-11ec-ac44-acde48001122
|
||||
version: 1
|
||||
date: '2021-12-01'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: Hunting
|
||||
datamodel:
|
||||
- Endpoint
|
||||
description: The following hunting analytic leverages Event ID 4769, `A Kerberos service ticket was requested`,
|
||||
to identify an unusual number of computer service ticket requests from one source. When a domain joined endpoint connects
|
||||
to a remote endpoint, it first will request a Kerberos Ticket with the computer name as the Service Name. An endpoint
|
||||
requesting a large number of computer service tickets for different endpoints could represent malicious behavior like
|
||||
lateral movement, malware staging, reconnaissance, etc.\
|
||||
|
||||
The detection calculates the standard deviation for each host and leverages the
|
||||
3-sigma statistical rule to identify an unusual number of service requests. To customize this
|
||||
analytic, users can try different combinations of the `bucket` span time, the
|
||||
calculation of the `upperBound` field as well as the Outlier calculation.
|
||||
This logic can be used for real time security monitoring as well as threat hunting exercises.\
|
||||
|
||||
search: ' `wineventlog_security` EventCode=4769 Service_Name="*$" Account_Name!="*$*"
|
||||
| bucket span=2m _time
|
||||
| stats dc(Service_Name) AS unique_targets values(Service_Name) as host_targets by _time, Client_Address, Account_Name
|
||||
| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Client_Address, Account_Name
|
||||
| eval upperBound=(comp_avg+comp_std*3)
|
||||
| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0)
|
||||
| `unusual_number_of_computer_service_tickets_requested_filter`'
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
Domain Controller and Kerberos events. The Advanced Security Audit policy setting
|
||||
`Audit Kerberos Authentication Service` within `Account Logon` needs to be enabled.
|
||||
known_false_positives: An single endpoint requesting a large number of computer service tickets
|
||||
is not common behavior. Possible false positive scenarios include but are not limited
|
||||
to vulnerability scanners, administration systeams and missconfigured systems.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1078/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
kill_chain_phases:
|
||||
- Reconnaissance
|
||||
- Exploitation
|
||||
- Lateral Movement
|
||||
mitre_attack_id:
|
||||
- T1078
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- EventCode
|
||||
- Ticket_Options
|
||||
- Ticket_Encryption_Type
|
||||
- dest
|
||||
- service
|
||||
- service_id
|
||||
security_domain: endpoint
|
||||
impact: 70
|
||||
confidence: 60
|
||||
risk_score: 42
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Lateral Movement
|
||||
message:
|
||||
observable:
|
||||
- name: Client_Address
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
|
||||
+70
@@ -0,0 +1,70 @@
|
||||
name: Unusual Number of Remote Endpoint Authentication Events
|
||||
id: acb5dc74-5324-11ec-a36d-acde48001122
|
||||
version: 1
|
||||
date: '2021-12-01'
|
||||
author: Mauricio Velazco, Splunk
|
||||
type: Hunting
|
||||
datamodel:
|
||||
- Endpoint
|
||||
description: The following hunting analytic leverages Event ID 4624, `An account was successfully logged on`,
|
||||
to identify an unusual number of remote authentication attempts coming from one source. An endpoint
|
||||
authenticating to a large number of remote endpoints could represent malicious behavior like
|
||||
lateral movement, malware staging, reconnaissance, etc.\
|
||||
|
||||
The detection calculates the standard deviation for each host and leverages the
|
||||
3-sigma statistical rule to identify an unusual high number of authentication events. To customize this
|
||||
analytic, users can try different combinations of the `bucket` span time, the
|
||||
calculation of the `upperBound` field as well as the Outlier calculation.
|
||||
This logic can be used for real time security monitoring as well as threat hunting exercises.\
|
||||
|
||||
search: ' `wineventlog_security` EventCode=4624 Logon_Type=3 Account_Name!="*$"
|
||||
| eval Source_Account = mvindex(Account_Name, 1)
|
||||
| bucket span=2m _time
|
||||
| stats dc(ComputerName) AS unique_targets values(ComputerName) as target_hosts by _time, Source_Network_Address, Source_Account
|
||||
| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Source_Network_Address, Source_Account
|
||||
| eval upperBound=(comp_avg+comp_std*3)
|
||||
| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0)
|
||||
`unusual_number_of_remote_endpoint_authentication_events_filter`'
|
||||
how_to_implement: To successfully implement this search, you need to be ingesting
|
||||
Windows Event Logs from domain controllers aas well as member servers and workstations.
|
||||
The Advanced Security Audit policy setting `Audit Logon` within `Logon/Logoff` needs
|
||||
to be enabled.
|
||||
known_false_positives: An single endpoint authenticating to a large number of hosts
|
||||
is not common behavior. Possible false positive scenarios include but are not limited
|
||||
to vulnerability scanners, jump servers and missconfigured systems.
|
||||
references:
|
||||
- https://attack.mitre.org/techniques/T1078/
|
||||
tags:
|
||||
analytic_story:
|
||||
- Active Directory Lateral Movement
|
||||
kill_chain_phases:
|
||||
- Reconnaissance
|
||||
- Lateral Movement
|
||||
mitre_attack_id:
|
||||
- T1078
|
||||
product:
|
||||
- Splunk Enterprise
|
||||
- Splunk Enterprise Security
|
||||
- Splunk Cloud
|
||||
required_fields:
|
||||
- _time
|
||||
- EventCode
|
||||
- Logon_Type
|
||||
- Caller_Process_Name
|
||||
- Security_ID
|
||||
- Account_Name
|
||||
- ComputerName
|
||||
security_domain: endpoint
|
||||
impact: 70
|
||||
confidence: 60
|
||||
risk_score: 42
|
||||
context:
|
||||
- Source:Endpoint
|
||||
- Stage:Reconnaissance
|
||||
- Stage:Lateral Movement
|
||||
message:
|
||||
observable:
|
||||
- name: ComputerName
|
||||
type: Endpoint
|
||||
role:
|
||||
- Victim
|
||||
@@ -32,7 +32,7 @@ tags:
|
||||
- SamSam Ransomware
|
||||
- Ryuk Ransomware
|
||||
- Hidden Cobra Malware
|
||||
- Lateral Movement
|
||||
- Active Directory Lateral Movement
|
||||
asset_type: Endpoint
|
||||
cis20:
|
||||
- CIS 3
|
||||
|
||||
@@ -1,19 +1,20 @@
|
||||
name: Lateral Movement
|
||||
name: Active Directory Lateral Movement
|
||||
id: 399d65dc-1f08-499b-a259-aad9051f38ad
|
||||
version: 2
|
||||
date: '2021-11-23'
|
||||
version: 3
|
||||
date: '2021-12-09'
|
||||
author: David Dorsey, Mauricio Velazco Splunk
|
||||
description: Detect and investigate tactics, techniques, and procedures around how
|
||||
attackers move laterally within the enterprise. Because lateral movement can expose
|
||||
the adversary to detection, it should be an important focus for security analysts.
|
||||
attackers move laterally within an Active Directory environment. Since lateral movement
|
||||
is often a necessary step in a breach, it is important for cyber defenders to deploy
|
||||
detection coverage.
|
||||
narrative: "Once attackers gain a foothold within an enterprise, they will seek to\
|
||||
\ expand their accesses and leverage techniques that facilitate lateral movement.\
|
||||
\ Attackers will often spend quite a bit of time and effort moving laterally. Because\
|
||||
\ lateral movement renders an attacker the most vulnerable to detection, it's an\
|
||||
\ excellent focus for detection and investigation.\\\nIndications of lateral movement\
|
||||
\ can include the abuse of system utilities (such as `psexec.exe`), unauthorized\
|
||||
\ use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash,\
|
||||
\ or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting\
|
||||
\ in an Active Directory network can include the abuse of system utilities (such as `psexec.exe`), unauthorized\
|
||||
\ use of remote desktop services, `file/admin$` shares, WMI, PowerShell, Service Control Manager,\
|
||||
\ the DCOM protocol, WinRM or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting\
|
||||
\ lateral movement techniques and look for suspicious activity in and around high-value\
|
||||
\ strategic network assets, such as Active Directory, which are often considered\
|
||||
\ the primary target or \"crown jewels\" to a persistent threat actor.\\\nAn adversary\
|
||||
@@ -32,9 +33,9 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek
|
||||
\ for all processes to ensure that the attackers did not install unauthorized software."
|
||||
references:
|
||||
- https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html
|
||||
- https://www.youtube.com/watch?v=hVTkkkM9XDg
|
||||
- http://www.irongeek.com/i.php?page=videos/derbycon7/t405-hunting-lateral-movement-for-fun-and-profit-mauricio-velazco
|
||||
tags:
|
||||
analytic_story: Lateral Movement
|
||||
analytic_story: Active Directory Lateral Movement
|
||||
category:
|
||||
- Adversary Tactics
|
||||
product:
|
||||
@@ -0,0 +1,12 @@
|
||||
name: Possible Lateral Movement PowerShell Spawn Unit Test
|
||||
tests:
|
||||
- name: Possible Lateral Movement PowerShell Spawn
|
||||
file: endpoint/possible_lateral_movement_powershell_spawn.yml
|
||||
pass_condition: '| stats count | where count > 0'
|
||||
earliest_time: '-24h'
|
||||
latest_time: 'now'
|
||||
attack_data:
|
||||
- file_name: windows-sysmon.log
|
||||
data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1543.003/lateral_movement_powershell/windows-sysmon.log
|
||||
source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
|
||||
sourcetype: xmlwineventlog
|
||||
@@ -0,0 +1,12 @@
|
||||
name: Short Lived Scheduled Task Unit Test
|
||||
tests:
|
||||
- name: Short Lived Scheduled Task
|
||||
file: endpoint/short_lived_scheduled_task.yml
|
||||
pass_condition: '| stats count | where count > 0'
|
||||
earliest_time: '-24h'
|
||||
latest_time: 'now'
|
||||
attack_data:
|
||||
- file_name: windows-security.log
|
||||
data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1053.005/lateral_movement/windows-security.log
|
||||
source: WinEventLog:Security
|
||||
sourcetype: WinEventLog
|
||||
Reference in New Issue
Block a user