The following analytic identifies a process that loads the credui.dll module. This legitimate module is typically abused by adversaries, threat actors and red teamers to create a credential UI prompt dialog box to lure users for possible credential theft or can be used to dump the credentials of a targeted host. This hunting query is a good pivot to check why the process loaded this dll and if it is a legitimate file. This hunting query may hit false positive for a third party application that uses a credential login UI for user login.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-08-24
- Author: Teoderick Contreras, Splunk
- ID: 406c21d6-6c75-4e9f-9ca9-48049a1dd90e
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 `sysmon` EventCode=7 (ImageLoaded = "*\\credui.dll" AND OriginalFileName = "credui.dll") OR (ImageLoaded = "*\\wincredui.dll" AND OriginalFileName = "wincredui.dll") AND NOT(Image IN("*\\windows\\explorer.exe", "*\\windows\\system32\\*", "*\\windows\\sysWow64\\*", "*:\\program files*")) | stats count min(_time) as firstTime max(_time) as lastTime by Image ImageLoaded OriginalFileName Computer EventCode Signed ProcessId ProcessGuid | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_input_capture_using_credential_ui_dll_filter`
The SPL above uses the following Macros:
windows_input_capture_using_credential_ui_dll_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
The latest Sysmon TA 3.0 https://splunkbase.splunk.com/app/5709 will add the ImageLoaded name to the process_name field, allowing this query to work. Use as an example and implement for other products.
Known False Positives
this module can be loaded by a third party application. Filter is needed.
Associated Analytic Story
|9.0||30||30||a process $Image$ loaded $ImageLoaded$ in $Computer$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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