Detection rules › Splunk
Linux DD File Overwrite
The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Impact | T1485 Data Destruction |
Rule body splunk
name: Linux DD File Overwrite
id: 9b6aae5e-8d85-11ec-b2ae-acde48001122
version: 10
creation_date: '2022-02-15'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk
status: production
type: TTP
description: The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
data_source:
- Sysmon for Linux EventID 1
search: |-
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name = "dd"
AND
Processes.process = "*of=*"
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)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `linux_dd_file_overwrite_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: Administrator or network operator can execute this command. Please update the filter macros to remove false positives.
references:
- https://gtfobins.github.io/gtfobins/dd/
- https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1485/T1485.md
drilldown_searches:
- name: View the detection results for - "$dest$"
search: '%original_detection_search% | search dest = "$dest$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$dest$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") | 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: A commandline $process$ executed on $dest$
entity:
field: dest
type: system
score: 50
analytic_story:
- Data Destruction
- Industroyer2
asset_type: Endpoint
mitre_attack_id:
- T1485
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/T1485/linux_dd_file_overwrite/sysmon_linux.log
source: Syslog:Linux-Sysmon/Operational
sourcetype: sysmon:linux
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_name = "dd"
AND
Processes.process = "*of=*"
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: search
| `security_content_ctime(firstTime)`
Stage 4: search
| `security_content_ctime(lastTime)`
Stage 5: search
| `linux_dd_file_overwrite_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 | eq |
|