Name:File Download or Read to Pipe Execution id:26f86252-1549-45e1-a212-eb26840e86bc version:2 date:2025-11-25 author:Michael Haag, Nasreddine Bencherchali, Splunk, DipsyTipsy status:production type:TTP Description:The following analytic detects the use of download or file reading utilities from Windows, Linux or MacOS to download or read the contents of a file from a remote or local source and pipe it directly to a shell for execution.
This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions.
This activity is significant as it is commonly associated with malicious actions like coinminers and exploits such as CVE-2021-44228 in Log4j.
If confirmed malicious, this behavior could allow attackers to execute arbitrary code, potentially leading to system compromise and unauthorized access to sensitive data.
Data_source:
-Sysmon EventID 1
-Sysmon for Linux EventID 1
-Windows Event Log Security 4688
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
from datamodel=Endpoint.Processes where
``` This aims to cover download utilities and file reading ones ```
( ``` Linux / MacOS ``` Processes.process IN ( "*bash*", "*csh*", "*dash*", "*fish*", "*ksh*", "*rbash*", "*tcsh*", "*zsh*" ) OR ``` Because the "sh" string can overlap and is a short atom we treat it in a special case ``` Processes.process IN ( "*|sh" "* sh*" ) OR ``` Windows ``` Processes.process IN ("*IEX*", "*Invoke-Expression*") )
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:False positives should be limited, however filtering may be required.
References: -https://gist.github.com/nathanqthai/01808c569903f41a52e7e7b575caa890 -https://github.com/MHaggis/notes/blob/master/utilities/warp_pipe_tester.py -https://www.huntress.com/blog/rapid-response-critical-rce-vulnerability-is-affecting-java -https://www.lunasec.io/docs/blog/log4j-zero-day/ -https://securelist.com/bad-magic-apt/109087/ drilldown_searches: name:'View the detection results for - "$user$" and "$dest$"' search:'%original_detection_search% | search user = "$user$" dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$user$" and "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") 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)`' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'Compromised Windows Host' - 'Ingress Tool Transfer' - 'Linux Living Off The Land' - 'Log4Shell CVE-2021-44228' - 'NPM Supply Chain Compromise' asset_type:Endpoint cve: - 'CVE-2021-44228' mitre_attack_id: - 'T1105' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint