Linux Ingress Tool Transfer with Curl
Description
The following analytic detects the use of the curl command with specific switches (-O, -sO, -ksO, –output) commonly used to download remote scripts or binaries. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant as it may indicate an attempt to download and execute potentially malicious files, often used in initial stages of an attack. If confirmed malicious, this could lead to unauthorized code execution, enabling attackers to compromise the system further.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2024-08-14
- Author: Michael Haag, Splunk
- ID: 8c1de57d-abc1-4b41-a727-a7a8fc5e0857
Annotations
Kill Chain Phase
- Command and Control
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=curl by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| where match(process, "(?i)(-O
|-sO
|-ksO
|--output)")
| `linux_ingress_tool_transfer_with_curl_filter`
Macros
The SPL above uses the following Macros:
linux_ingress_tool_transfer_with_curl_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- Processes.dest
- Processes.user
- Processes.parent_process_name
- Processes.parent_process
- Processes.original_file_name
- Processes.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_path
- Processes.process_path
- Processes.parent_process_id
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 will be present. Tune and then change type to TTP.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
12.0 | 40 | 30 | An instance of $process_name$ was identified on endpoint $dest$ by user $user$ to download a remote file. Review activity for further details. |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
- https://gtfobins.github.io/gtfobins/curl/
- https://curl.se/docs/manpage.html#-I
- https://gtfobins.github.io/gtfobins/curl/
- https://github.com/rapid7/metasploit-framework/search?q=curl
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 3