Unsigned Image Loaded by LSASS

THIS IS A DEPRECATED DETECTION

This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.

Try in Splunk Security Cloud

Description

This search detects loading of unsigned images by LSASS. Deprecated because too noisy.

• Type: TTP

• Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

• Last Updated: 2019-12-06
• Author: Patrick Bareiss, Splunk
• ID: 56ef054c-76ef-45f9-af4a-a634695dcd65

Annotations

ATT&CK

ATT&CK

ID	Technique	Tactic
T1003.001	LSASS Memory	Credential Access

Kill Chain Phase

• Exploitation

NIST

• DE.CM

CIS20

• CIS 10

CVE

Search

`sysmon` EventID=7 Image=*lsass.exe Signed=false 
| stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 
| rename Computer as dest 
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)` 
| `unsigned_image_loaded_by_lsass_filter` 

Macros

The SPL above uses the following Macros:

• sysmon
• security_content_ctime

unsigned_image_loaded_by_lsass_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

How To Implement

This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named sysmon. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.

Known False Positives

Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs.

Associated Analytic Story

• Credential Dumping

RBA

Risk Score	Impact	Confidence	Message
25.0	50	50	tbd

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://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf

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

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