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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>
72 lines
4.6 KiB
YAML
72 lines
4.6 KiB
YAML
name: Linux Ngrok Reverse Proxy Usage
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id: bc84d574-708c-467d-b78a-4c1e20171f97
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version: 9
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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: Anomaly
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description: The following analytic detects the use of Ngrok on a Linux operating system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments associated with Ngrok. This activity is significant because Ngrok can be used by adversaries to establish reverse proxies, potentially bypassing network defenses. If confirmed malicious, this could allow attackers to create persistent, unauthorized access channels, facilitating data exfiltration or further exploitation of the compromised system.
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data_source:
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- Sysmon for Linux EventID 1
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search: |-
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
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WHERE Processes.process_name=ngrok Processes.process IN ("*start*", "*--config*","*http*","*authtoken*", "*http*", "*tcp*")
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BY Processes.action Processes.dest Processes.original_file_name
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Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
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Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
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Processes.process Processes.process_exec Processes.process_guid
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Processes.process_hash Processes.process_id Processes.process_integrity_level
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Processes.process_name Processes.process_path Processes.user
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Processes.user_id Processes.vendor_product
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| `drop_dm_object_name(Processes)`
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| `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)`
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| `linux_ngrok_reverse_proxy_usage_filter`
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how_to_implement: 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.
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known_false_positives: False positives may be present if Ngrok is an authorized utility. Filter as needed.
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references:
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- https://ngrok.com
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- https://www.cisa.gov/uscert/sites/default/files/publications/aa22-320a_joint_csa_iranian_government-sponsored_apt_actors_compromise_federal%20network_deploy_crypto%20miner_credential_harvester.pdf
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drilldown_searches:
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- name: View the detection results for - "$user$" and "$dest$"
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search: '%original_detection_search% | search user = "$user$" dest = "$dest$"'
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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 - "$user$" and "$dest$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") 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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rba:
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message: A reverse proxy was identified spawning from $parent_process_name$ - $process_name$ on endpoint $dest$ by user $user$.
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risk_objects:
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- field: user
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type: user
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score: 50
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- field: dest
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type: system
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score: 50
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threat_objects:
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- field: parent_process_name
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type: parent_process_name
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- field: process_name
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type: process_name
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tags:
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analytic_story:
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- Reverse Network Proxy
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asset_type: Endpoint
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mitre_attack_id:
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- T1572
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- T1090
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- T1102
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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: endpoint
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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/T1572/ngrok/ngrok_linux-sysmon.log
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source: Syslog:Linux-Sysmon/Operational
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sourcetype: sysmon:linux
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