--- title: "Osquery pack - ColdRoot detection" excerpt: "" categories: - Deprecated last_modified_at: 2019-01-29 toc: true toc_label: "" tags: - Splunk Enterprise - Splunk Enterprise Security - Splunk Cloud --- [Try in Splunk Security Cloud](https://www.splunk.com/en_us/products/cyber-security.html){: .btn .btn--success} #### Description This search looks for ColdRoot events from the osx-attacks osquery pack. - **Type**: [TTP](https://github.com/splunk/security_content/wiki/Detection-Analytic-Types) - **Product**: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud - **Last Updated**: 2019-01-29 - **Author**: Rico Valdez, Splunk - **ID**: a6fffe5e-05c3-4c04-badc-887607fbb8dc #### Annotations
ATT&CK
Kill Chain Phase
* Installation * Command & Control
NIST
* DE.DP * DE.CM * PR.PT
CIS20
* CIS 4 * CIS 8
CVE
#### Search ``` | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | bucket _time span=30s | stats count(path) by _time, host, user, path | `osquery_pack___coldroot_detection_filter` ``` #### Macros The SPL above uses the following Macros: > :information_source: > **osquery_pack_-_coldroot_detection_filter** is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL. #### Required field * _time #### How To Implement In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model #### Known False Positives There are no known false positives. #### Associated Analytic story * [ColdRoot MacOS RAT](/stories/coldroot_macos_rat) #### RBA | Risk Score | Impact | Confidence | Message | | ----------- | ----------- |--------------|--------------| | 25.0 | 50 | 50 | tbd | > :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](https://github.com/splunk/attack_data#using-replaypy) tool or the [UI](https://github.com/splunk/attack_data#using-ui). Alternatively you can replay a dataset into a [Splunk Attack Range](https://github.com/splunk/attack_range#replay-dumps-into-attack-range-splunk-server) [*source*](https://github.com/splunk/security_content/tree/develop/detections/deprecated/osquery_pack___coldroot_detection.yml) \| *version*: **1**