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Description

The following analytic is designed to detect potential security threats involving the misuse of system trust. It works by detecting events where a process attempts to add a certificate to the untrusted certificate store, an action often associated with disabling security tools. The analytic uses Sysmon Event ID 1 data source, particularly focusing on process activities and command-line arguments related to 'certutil -addstore'. It's essential to ingest data that records process activity and logs containing process names and command lines for its effective operation. Be aware, sometimes administrators might legitimately perform this action. The analytic's value lies in detecting isolated or unexpected instances, indicative of potential malicious activities. Cybersecurity analysts should understand the importance of trust mechanisms and their subversion in system security.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2021-09-16
  • Author: Patrick Bareiss, Rico Valdez, Splunk
  • ID: 6bc5243e-ef36-45dc-9b12-f4a6be131159

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1553.004 Install Root Certificate Defense Evasion
T1553 Subvert Trust Controls Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


1
2
3
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6



| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where `process_certutil` (Processes.process=*-addstore*) by Processes.dest Processes.user Processes.parent_process Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
| `drop_dm_object_name("Processes")` 
| `security_content_ctime(firstTime)` 
|`security_content_ctime(lastTime)` 
| `attempt_to_add_certificate_to_untrusted_store_filter`

Macros

The SPL above uses the following Macros:

:information_source: attempt_to_add_certificate_to_untrusted_store_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
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.process_name
  • Processes.process
  • Processes.parent_process
  • Processes.process_id
  • Processes.parent_process_id

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

There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
35.0 70 50 An instance of $parent_process_name$ spawning $process_name$ was identified attempting to add a certificate to the store on endpoint $dest$ 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: 7