Linux Obfuscated Files or Information Base64 Decode
Description
The following analytic identifies the use of base64 decode on Linux being utilized to deobfuscate a file. Identify the source of the file and determine if legitimate. Review parallel processes for further behavior before and after.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-07-27
- Author: Michael Haag, Splunk
- ID: 303b38b2-c03f-44e2-8f41-4594606fcfc7
Annotations
Kill Chain Phase
- Delivery
- Exploitation
NIST
- DE.CM
CIS20
- CIS 3
- CIS 5
- CIS 16
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 IN ("*base64 -d*","*base64 --decode*") 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)`
| `linux_obfuscated_files_or_information_base64_decode_filter`
Macros
The SPL above uses the following Macros:
linux_obfuscated_files_or_information_base64_decode_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
To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint
datamodel in the Processes
node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.
Known False Positives
False positives may be present and will require some tuning based on processes. Filter as needed.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
15.0 | 30 | 50 | An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ decoding base64. |
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://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1027/T1027.md#atomic-test-1—decode-base64-data-into-script
- https://redcanary.com/blog/lateral-movement-with-secure-shell/
- https://linux.die.net/man/1/base64
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: 1