Detection: Windows DiskCryptor Usage

Updated Date: 2024-08-15 ID: d56fe0c8-4650-11ec-a8fa-acde48001122 Author: Michael Haag, Splunk Type: Hunting Product: Splunk Enterprise Security

Description

The following analytic detects the execution of DiskCryptor, identified by the process names "dcrypt.exe" or "dcinst.exe". This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names. DiskCryptor is significant because adversaries use it to manually encrypt disks during an operation, potentially leading to data inaccessibility. If confirmed malicious, this activity could result in complete disk encryption, causing data loss and operational disruption. Immediate investigation is required to mitigate potential ransomware attacks.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name="dcrypt.exe" OR Processes.original_file_name=dcinst.exe) by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `windows_diskcryptor_usage_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
CrowdStrike ProcessRollup2	N/A	`'crowdstrike:events:sensor'`	`'crowdstrike'`	N/A

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
windows_diskcryptor_usage_filter	`search *`

windows_diskcryptor_usage_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1486	Data Encrypted for Impact	Impact

KillChainPhase.ACTIONS_ON_OBJECTIVES

NistCategory.DE_AE

Cis18Value.CIS_10

APT38

APT41

Akira

FIN7

FIN8

Indrik Spider

Magic Hound

Sandworm Team

Scattered Spider

TA505

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`0 * * * *`
Earliest Time	`-70m@m`
Latest Time	`-10m@m`
Schedule Window	`auto`
Creates Risk Event	False

This configuration file applies to all detections of type hunting.

Implementation

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

It is possible false positives may be present based on the internal name dcinst.exe, filter as needed. It may be worthy to alert on the service name.

Associated Analytic Story

Ransomware

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ attempting to encrypt disks.	35	70	50

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	✅ Passing	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`XmlWinEventLog:Microsoft-Windows-Sysmon/Operational`	`xmlwineventlog`
Integration	✅ Passing	Dataset	`XmlWinEventLog:Microsoft-Windows-Sysmon/Operational`	`xmlwineventlog`

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: GitHub | Version: 3