Name:Windows Potential Cloudflared Tunnel Execution id:2e29b58e-0f5a-42fc-b435-0fdce8862831 version:2 date:None author:Raven Tait, Splunk status:production type:Anomaly Description:This analytic detects command-line arguments associated with the cloudflared client used to create Cloudflare tunnels.
Cloudflared is functionally very similar to ngrok, an ingress-as-a-service tool.
Cloudflared reaches out to the Cloudflare Edge Servers, creating an outbound connection over HTTPS(HTTP2/QUIC), where the tunnel's controller makes services or private networks accessible. Data_source:
-Sysmon EventID 1
-Windows Event Log Security 4688
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
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. known_false_positives:Some legitimate use cases include authorized DevOps or IT teams using Cloudflared for secure remote access and network management. Filter alerts based on approved usage and trusted users. References: -https://www.guidepointsecurity.com/blog/tunnel-vision-cloudflared-abused-in-the-wild/ -https://github.com/cloudflare/cloudflared -https://www-bleepingcomputer-com.cdn.ampproject.org/c/s/www.bleepingcomputer.com/news/security/hackers-increasingly-abuse-cloudflare-tunnels-for-stealthy-connections/amp/ drilldown_searches: earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View the detection results for - "$user$" and "$dest$"' search:'%original_detection_search% | search user = "$user$" dest = "$dest$"' name:'View risk events for the last 7 days for - "$user$" and "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") | 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)`' earliest_offset:'7d' latest_offset:'0' analytic_story:['Reverse Network Proxy']