This analytic is to detect a suspicious modification of the active setup registry for persistence and privilege escalation. This technique was seen in several malware (poisonIvy), adware and APT to gain persistence to the compromised machine upon boot up. This TTP is a good indicator to further check the process id that do the modification since modification of this registry is not commonly done. check the legitimacy of the file and process involve in this rules to check if it is a valid setup installer that creating or modifying this registry.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-01-26
- Author: Teoderick Contreras, Splunk
- ID: f64579c0-203f-11ec-abcc-acde48001122
Kill Chain Phase
1 2 3 4 5 6 7 8 9 10 11 | tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry where Registry.registry_value_name= "StubPath" Registry.registry_path = "*\\SOFTWARE\\Microsoft\\Active Setup\\Installed Components*" by _time span=1h Registry.dest Registry.user Registry.registry_path Registry.registry_value_name Registry.registry_value_data Registry.process_guid | `drop_dm_object_name(Registry)` |rename process_guid as proc_guid |join proc_guid, _time [ | tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes by _time span=1h Processes.process_id Processes.process_name Processes.process Processes.dest Processes.parent_process_name Processes.parent_process Processes.process_guid | `drop_dm_object_name(Processes)` |rename process_guid as proc_guid | fields _time dest user parent_process_name parent_process process_name process_path process proc_guid registry_path registry_value_name registry_value_data] | table _time dest user parent_process_name parent_process process_name process_path process proc_guid registry_path registry_value_name registry_value_data | `active_setup_registry_autostart_filter`
The SPL above uses the following Macros:
active_setup_registry_autostart_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response product, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.
Known False Positives
Active setup installer may add or modify this registry.
Associated Analytic Story
|64.0||80||80||modified/added/deleted registry entry $Registry.registry_path$ in $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 2