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P4T12ICK
78 lines
3.3 KiB
YAML
78 lines
3.3 KiB
YAML
name: Detect Exchange Web Shell
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id: 8c14eeee-2af1-4a4b-bda8-228da0f4862a
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version: 2
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date: '2021-03-09'
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author: Michael Haag, Shannon Davis, Splunk
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type: TTP
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datamodel:
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- Endpoint
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description: 'The following query identifies suspicious .aspx created in 3 paths identified
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by Microsoft as known drop locations for Exchange exploitation related to HAFNIUM
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group. Paths include: `\HttpProxy\owa\auth\`, `\inetpub\wwwroot\aspnet_client\`,
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and `\HttpProxy\OAB\`. Upon triage, the suspicious .aspx file will likely look obvious
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on the surface. inspect the contents for script code inside. Identify additional
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log sources, IIS included, to review source and other potential exploitation.'
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search: '| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes
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where Processes.process_name=System by _time span=1h Processes.process_id Processes.process_name
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Processes.dest | `drop_dm_object_name(Processes)` | join process_guid, _time [|
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tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
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as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path IN ("*\\HttpProxy\\owa\\auth\\*",
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"*\\inetpub\\wwwroot\\aspnet_client\\*", "*\\HttpProxy\\OAB\\*") Filesystem.file_name="*.aspx"
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by _time span=1h Filesystem.dest Filesystem.file_create_time Filesystem.file_name
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Filesystem.file_path | `drop_dm_object_name(Filesystem)` | fields _time dest file_create_time
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file_name file_path process_name process_path process] | dedup file_create_time
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| table dest file_create_time, file_name, file_path, process_name | `detect_exchange_web_shell_filter`'
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how_to_implement: To successfully implement this search you need to be ingesting information
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on process that include the name of the process responsible for the changes from
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your endpoints into the `Endpoint` datamodel in the `Processes` node and `Filesystem`
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node.
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known_false_positives: The query is structured in a way that `action` (read, create)
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is not defined. Review the results of this query, filter, and tune as necessary.
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It may be necessary to generate this query specific to your endpoint product.
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references:
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- https://raw.githubusercontent.com/Azure/Azure-Sentinel/master/Sample%20Data/Feeds/MSTICIoCs-ExchangeServerVulnerabilitiesDisclosedMarch2021.csv
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tags:
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analytic_story:
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- HAFNIUM Group
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automated_detection_testing: passed
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confidence: 90
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context:
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- Source:Endpoint
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- Stage:Exploitation
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dataset:
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- https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1505.003/windows-sysmon_proxylogon.log
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impact: 90
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kill_chain_phases:
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- Exploitation
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message: A file - $file_name$ was written to disk that is related to IIS exploitation
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previously performed by HAFNIUM. Review further file modifications on endpoint
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$dest$ by user $user$.
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mitre_attack_id:
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- T1505.003
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observable:
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- name: user
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type: User
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role:
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- Victim
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- name: dest
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type: Hostname
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role:
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- Victim
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- name: file_name
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type: File Name
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role:
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- Victim
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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required_fields:
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- _time
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- Filesystem.file_path
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- Filesystem.process_id
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- Filesystem.file_name
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- Filesystem.file_hash
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- Filesystem.user
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risk_score: 81
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security_domain: endpoint
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