MacOS plutil
Description
Detect usage of plutil to modify plist files. Adversaries can modiy plist files to executed binaries or add command line arguments. Plist files in auto-run locations are executed upon user logon or system startup.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-05-26
- Author: Patrick Bareiss, Splunk
- ID: c11f2b57-92c1-4cd2-b46c-064eafb833ac
Annotations
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
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`osquery` name=es_process_events columns.path=/usr/bin/plutil
| rename columns.* as *
| stats count min(_time) as firstTime max(_time) as lastTime by username host cmdline pid path parent signing_id
| rename username as User, cmdline as process, path as process_path
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `macos_plutil_filter`
Macros
The SPL above uses the following Macros:
macos_plutil_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
- columns.cmdline
- columns.pid
- columns.parent
- columns.path
- columns.signing_id
- columns.username
- host
How To Implement
This detection uses osquery and endpoint security on MacOS. Follow the link in references, which describes how to setup process auditing in MacOS with endpoint security and osquery.
Known False Positives
Administrators using plutil to change plist files.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | plutil are executed on $host$ from $user$ |
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
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: 2