Windows PowerSploit GPP Discovery
Description
The following analytic identifies the use of the Get-GPPPassword PowerShell commandlet employed to search for unsecured credentials Group Policy Preferences (GPP). GPP are tools that allow administrators to create domain policies with embedded credentials. These policies allow administrators to set local accounts. These group policies are stored in SYSVOL on a domain controller. This means that any domain user can view the SYSVOL share and decrypt the password (using the AES key that has been made public). While Microsoft released a patch that impedes Administrators to create unsecure credentials, existing Group Policy Preferences files with passwords are not removed from SYSVOL.
- Type: TTP
-
Product: Splunk Behavioral Analytics
- Last Updated: 2023-05-02
- Author: Mauricio Velazco, Splunk
- ID: fdef746e-71fb-41ce-8ab2-b4a5a6b50ca2
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
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$main = from source
| eval timestamp = time
| eval metadata_uid = metadata.uid
| eval device_hostname = device.hostname
| eval process_file = process.file
| eval process_file_path = process_file.path
| eval process_uid = process.uid
| eval process_cmd_line = process.cmd_line
| eval actor_user = actor.user
| eval actor_user_uid = actor_user.uid
| where match(process_cmd_line, /(?i)get-gpppassword/)=true --finding_report--
Macros
The SPL above uses the following Macros:
windows_powersploit_gpp_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.
- device.hostname
- process.file.path
- process.uid
- process.cmd_line
- actor.user.uid
How To Implement
To successfully implement this analytic, you will need to enable PowerShell Script Block Logging on some or all endpoints. Additional setup here https://docs.splunk.com/Documentation/UBA/5.0.4.1/GetDataIn/AddPowerShell#Configure_module_logging_for_PowerShell.
Known False Positives
Unknown
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
56.0 | 70 | 80 | Commandlets leveraged to discover GPP credentials were executed on $Computer$ |
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/T1552/006/
- https://pentestlab.blog/2017/03/20/group-policy-preferences/
- https://adsecurity.org/?p=2288
- https://www.hackingarticles.in/credential-dumping-group-policy-preferences-gpp/
- https://adsecurity.org/?p=2288
- https://support.microsoft.com/en-us/topic/ms14-025-vulnerability-in-group-policy-preferences-could-allow-elevation-of-privilege-may-13-2014-60734e15-af79-26ca-ea53-8cd617073c30
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: 4