Branch was auto-updated.

This commit is contained in:
Bhavin Patel
2021-12-09 09:06:14 -08:00
committed by GitHub
41 changed files with 492 additions and 46 deletions
@@ -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:
@@ -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:
@@ -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:
@@ -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
@@ -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
@@ -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