Detection rules › Splunk

Linux Decode Base64 to Shell

Status
production
Severity
medium
Group by
IntegrityLevel, command_line, computer_name, event_action, original_file_name, parent_command_line, parent_process_guid, parent_process_id, parent_process_name, process_guid, process_hash, process_id, process_name, user, user_id, vendor_product
Author
Michael Haag, Splunk
Source
github.com/splunk/security_content

The following analytic detects the behavior of decoding base64-encoded data and passing it to a Linux shell. Additionally, it mitigates the potential damage and protects the organization's systems and data.The detection is made by searching for specific commands in the Splunk query, namely "base64 -d" and "base64 --decode", within the Endpoint.Processes data model. The analytic also includes a filter for Linux shells. The detection is important because it indicates the presence of malicious activity since Base64 encoding is commonly used to obfuscate malicious commands or payloads, and decoding it can be a step in running those commands. It suggests that an attacker is attempting to run malicious commands on a Linux system to gain unauthorized access, for data exfiltration, or perform other malicious actions.

Known false positives

  • False positives may be present based on legitimate software being utilized. Filter as needed.

MITRE ATT&CK coverage

Telemetry coverage

PlatformRecord / event type
LinuxEvent ID 1: Process Create

Rule body

name: Linux Decode Base64 to Shell
id: 637b603e-1799-40fd-bf87-47ecbd551b66
version: 14
creation_date: '2022-06-17'
modification_date: '2026-05-13'
author: Michael Haag, Splunk
status: production
type: TTP
description: The following analytic detects the behavior of decoding base64-encoded data and passing it to a Linux shell. Additionally, it mitigates the potential damage and protects the organization's systems and data.The detection is made by searching for specific commands in the Splunk query, namely "base64 -d" and "base64 --decode", within the Endpoint.Processes data model. The analytic also includes a filter for Linux shells. The detection is important because  it indicates the presence of malicious activity since Base64 encoding is commonly used to obfuscate malicious commands or payloads, and decoding it can be a step in running those commands. It suggests that an attacker is attempting to run malicious commands on a Linux system to gain unauthorized access, for data exfiltration, or perform other malicious actions.
data_source:
    - Sysmon for Linux EventID 1
    - Cisco Isovalent Process Exec
search: |-
    | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
    from datamodel=Endpoint.Processes where
    Processes.process="*|*"
    `linux_shells`
    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)`
    | rex field=process "base64\s+(?<decode_flag>-{1,2}d\w*)"
    | where isnotnull(decode_flag)
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | `linux_decode_base64_to_shell_filter`
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 may be present based on legitimate software being utilized. Filter as needed.
references:
    - 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
finding:
    title: An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ decoding base64 and passing it to a shell.
    entity:
        field: user
        type: user
        score: 50
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 50
          message: An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ decoding base64 and passing it to a shell.
threat_objects:
    - field: parent_process_name
      type: parent_process_name
    - field: process_name
      type: process_name
analytic_story:
    - Linux Living Off The Land
    - Cisco Isovalent Suspicious Activity
asset_type: Endpoint
mitre_attack_id:
    - T1027
    - T1059.004
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.process="*|*"
`linux_shells`
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

Stage 2: search

| `drop_dm_object_name(Processes)`

Stage 3: rex

| rex field=process "base64\s+(?<decode_flag>-{1,2}d\w*)"

Stage 4: where

| where isnotnull(decode_flag)

Stage 5: search

| `security_content_ctime(firstTime)`

Stage 6: search

| `security_content_ctime(lastTime)`

Stage 7: search

| `linux_decode_base64_to_shell_filter`

Indicators

These rows show field, operator, and value matches.

FieldKindValuesSearch
Processes.processeq
  • "*|*"
field:"CommandLine" kind:eq
Processes.process_namein
  • "bash"
  • "csh"
  • "dash"
  • "eshell"
  • "fish"
  • "ion"
  • "ksh"
  • "rbash"
  • "sh"
  • "tcsh"
  • "zsh"
field:"process_name" kind:in
decode_flagis_not_null
  • (no value, null check)
field:"decode_flag" kind:is_not_null