Detection rules › Splunk
Linux Decode Base64 to Shell
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.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Execution | T1059.004 Command and Scripting Interpreter: Unix Shell |
| Stealth | T1027 Obfuscated Files or Information |
Rule body splunk
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
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"
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
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1027/atomic_red_team/linux-sysmon.log
source: Syslog:Linux-Sysmon/Operational
sourcetype: sysmon:linux
test_type: unit
- name: True Positive Test - Cisco Isovalent
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/cisco_isovalent/cisco_isovalent.log
source: not_applicable
sourcetype: cisco:isovalent:processExec
test_type: unit
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
Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.
| Field | Kind | Values |
|---|---|---|
Processes.process | eq |
|
Processes.process_name | in |
|
decode_flag | is_not_null |