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Nasreddine Bencherchali
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* Add YAML formatting and validation infrastructure - Add yamlfmt configuration (.yamlfmt) with 4-space indent, LF line endings - Add yamllint configuration (.yamllint) for syntax validation (detections/ only) - Add pre-commit hook for automatic YAML formatting - Add CI validation script with unified error output - Add GitHub Actions workflow for PR validation - Add documentation for setup and usage - Support custom yamlfmt binary path via --yamlfmt-path flag * comment yaml check from pre-commit * apply yamlfmt * Update yaml-validation.yml * Update yaml-validation.yml * application folder search formatting * cloud folder search formatting * web folder search formatting * network folder search formatting * endpoint folder search formatting * resolve first conflict * apply formatting * remove additional pipe * Update README.md * update versions * restore and update formatting (#3920) --------- Co-authored-by: Bhavin Patel <bhavin.j.patel91@gmail.com>
58 lines
4.4 KiB
YAML
58 lines
4.4 KiB
YAML
name: ProxyShell ProxyNotShell Behavior Detected
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id: c32fab32-6aaf-492d-bfaf-acbed8e50cdf
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version: 8
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date: '2026-02-25'
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author: Michael Haag, Splunk
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status: production
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type: Correlation
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description: The following analytic identifies potential exploitation of Windows Exchange servers via ProxyShell or ProxyNotShell vulnerabilities, followed by post-exploitation activities such as running nltest, Cobalt Strike, Mimikatz, and adding new users. It leverages data from multiple analytic stories, requiring at least five distinct sources to trigger, thus reducing noise. This activity is significant as it indicates a high likelihood of an active compromise, potentially leading to unauthorized access, privilege escalation, and persistent threats within the environment. If confirmed malicious, attackers could gain control over the Exchange server, exfiltrate data, and maintain long-term access.
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data_source: []
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search: |-
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| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as risk_score, count(All_Risk.calculated_risk_score) as risk_event_count, values(All_Risk.annotations.mitre_attack.mitre_tactic_id) as annotations.mitre_attack.mitre_tactic_id, dc(All_Risk.annotations.mitre_attack.mitre_tactic_id) as mitre_tactic_id_count, values(All_Risk.analyticstories) as analyticstories values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count, values(All_Risk.tag) as tag, values(source) as source, dc(source) as source_count dc(All_Risk.analyticstories) as dc_analyticstories FROM datamodel=Risk.All_Risk
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WHERE All_Risk.analyticstories IN ("ProxyNotShell","ProxyShell")
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OR
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(All_Risk.analyticstories IN ("ProxyNotShell","ProxyShell")
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AND
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All_Risk.analyticstories="Cobalt Strike") All_Risk.risk_object_type="system"
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BY _time span=1h All_Risk.risk_object
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All_Risk.risk_object_type
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| `drop_dm_object_name(All_Risk)`
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| `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)`
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| where source_count >=5
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| `proxyshell_proxynotshell_behavior_detected_filter`
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how_to_implement: To implement this correlation, you will need to enable ProxyShell, ProxyNotShell and Cobalt Strike analytic stories (the anaytics themselves) and ensure proper data is being collected for Web and Endpoint datamodels. Run the correlation rule seperately to validate it is not triggering too much or generating incorrectly. Validate by running ProxyShell POC code and Cobalt Strike behavior.
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known_false_positives: False positives will be limited, however tune or modify the query as needed.
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references:
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- https://www.gteltsc.vn/blog/warning-new-attack-campaign-utilized-a-new-0day-rce-vulnerability-on-microsoft-exchange-server-12715.html
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- https://msrc-blog.microsoft.com/2022/09/29/customer-guidance-for-reported-zero-day-vulnerabilities-in-microsoft-exchange-server/
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drilldown_searches:
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- name: View the detection results for - "$risk_object$"
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search: '%original_detection_search% | search risk_object = "$risk_object$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$risk_object$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$risk_object$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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tags:
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analytic_story:
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- ProxyShell
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- ProxyNotShell
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- Seashell Blizzard
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asset_type: Web Server
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mitre_attack_id:
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- T1190
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- T1133
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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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security_domain: network
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1190/proxyshell/proxyshell-risk.log
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source: proxyshell
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sourcetype: stash
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