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.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2024-05-28
- Author: Teoderick Contreras, Splunk
- ID: a3b3bc96-1c4f-4eba-8218-027cac739a48
Annotations
Kill Chain Phase
- Exploitation
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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| 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
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_password_managers_discovery_filter`
Macros
The SPL above uses the following Macros:
windows_password_managers_discovery_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.parent_process
- Processes.original_file_name
- Processes.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_path
- Processes.process_path
- Processes.parent_process_id
- Processes.parent_process_guid
- Processes.process_guid
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
unknown
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | a process with commandline $process$ that can retrieve information related to password manager databases 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.
Reference
- https://attack.mitre.org/techniques/T1555/005/
- https://github.com/carlospolop/PEASS-ng/tree/master/winPEAS
- https://www.microsoft.com/en-us/security/blog/2022/10/14/new-prestige-ransomware-impacts-organizations-in-ukraine-and-poland/
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: 2