Name:Curl Execution with Percent Encoded URL id:9a8d5516-4c5e-11ef-9d42-acde48001122 version:4 date:2026-04-28 author:Nasreddine Bencherchali, Splunk status:production type:Anomaly Description:The following analytic detects the execution of the curl utility where the command line includes percent-encoded characters and explicit file output options (such as -o or --output).
It leverages process execution telemetry from Endpoint Detection and Response (EDR) data sources to identify curl commands that may be using URL encoding to obfuscate download locations or payload paths.
This behavior is notable because percent-encoded URLs are commonly used by adversaries to evade simple string-based detections, hide malicious infrastructure, or bypass network security controls.
When combined with file download behavior, this activity may indicate malware staging, payload retrieval, or secondary tool deployment.
Analysts should review the decoded URL, destination host, parent process, and downloaded file to determine whether the activity is authorized or malicious.
The analytic calculates the number of percent (%) characters in the curl command line and triggers when a threshold of three or more is met, indicating potential URL encoding.
Adjust the threshold as needed based on your environment and tuning requirements.
Data_source:
-CrowdStrike ProcessRollup2
-Sysmon EventID 1
-Sysmon for Linux EventID 1
-Windows Event Log Security 4688
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where ( Processes.process_name IN ("curl.exe", "curl") OR Processes.original_file_name="curl.exe" ) Processes.process IN ( "* --output *", "* -o *" ) Processes.process IN ("*%*") by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
``` Count the number of % characters in the process command line. Change this threshold based on your environment and tuning needs. ``` | eval percent_count = mvcount(split(process, "%")) - 1 | where percent_count >= 3
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:No false positives have been identified at this time.
References: -https://github.com/nasbench/Misc-Research/blob/main/LOLBINs/Curl.md -https://attack.mitre.org/techniques/T1027/ -https://attack.mitre.org/techniques/T1105/ -https://curl.se/docs/manpage.html 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 ("$user$", "$dest$") | 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' tags: analytic_story: - 'Compromised Windows Host' - 'Ingress Tool Transfer' - 'Living Off The Land' asset_type:Endpoint mitre_attack_id: - 'T1027' - 'T1105' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint
