ID | Technique | Tactic |
---|---|---|
T1555.005 | Password Managers | Credential Access |
Detection: Windows Password Managers Discovery
Description
The following analytic identifies command-line activity that searches for files related to password manager software, such as ".kdbx" and "credential". It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This activity is significant because attackers often target password manager databases to extract stored credentials, which can be used for further exploitation. If confirmed malicious, this behavior could lead to unauthorized access to sensitive information, enabling attackers to escalate privileges, move laterally, or exfiltrate critical data.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "*dir *" OR Processes.process = "*findstr*" AND Processes.process IN ( "*.kdbx*", "*credential*", "*key3.db*","*pass*", "*cred*", "*key4.db*", "*accessTokens*", "*access_tokens*", "*.htpasswd*", "*Ntds.dit*") by Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.process_guid Processes.parent_process_name Processes.parent_process Processes.parent_process_guid Processes.dest Processes.user
3| `drop_dm_object_name(Processes)`
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `windows_password_managers_discovery_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_password_managers_discovery_filter | search * |
windows_password_managers_discovery_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
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 | True |
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
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
a process with commandline $process$ that can retrieve information related to password manager databases in $dest$ | 25 | 50 | 50 |
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: 2