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Description

The following analytic detects multiple executions of Living off the Land (LOLbin) binaries on macOS within a short period. It leverages osquery to monitor process events and identifies commands such as "find", "crontab", "screencapture", "openssl", "curl", "wget", "killall", and "funzip". This activity is significant as LOLbins are often used by attackers to perform malicious actions while evading detection. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, or persist within the environment, posing a significant security risk.

  • Type: TTP

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2024-05-17
  • Author: Patrick Bareiss, Splunk
  • ID: 58d270fb-5b39-418e-a855-4b8ac046805e

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1059.004 Unix Shell Execution
T1059 Command and Scripting Interpreter Execution
Kill Chain Phase
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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`osquery_macro` name=es_process_events columns.cmdline IN ("find*", "crontab*", "screencapture*", "openssl*", "curl*", "wget*", "killall*", "funzip*") 
| rename columns.* as * 
| stats  min(_time) as firstTime max(_time) as lastTime values(cmdline) as cmdline, values(pid) as pid, values(parent) as parent, values(path) as path, values(signing_id) as signing_id,  dc(path) as dc_path by username host 
| rename username as user, cmdline as process, path as process_path, host as dest 
| where dc_path > 3 
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)` 
| `macos_lolbin_filter`

Macros

The SPL above uses the following Macros:

:information_source: macos_lolbin_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

None identified.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 Multiplle LOLbin are executed on host $dest$ by user $user$

:information_source: 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: 3