Detection: SecretDumps Offline NTDS Dumping Tool

Description

The following analytic detects the potential use of the secretsdump.py tool to dump NTLM hashes from a copy of ntds.dit and the SAM, SYSTEM, and SECURITY registry hives. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns and process names associated with secretsdump.py. This activity is significant because it indicates an attempt to extract sensitive credential information offline, which is a common post-exploitation technique. If confirmed malicious, this could allow an attacker to obtain NTLM hashes, facilitating further lateral movement and potential privilege escalation within the network.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = "python*.exe" Processes.process = "*.py*" Processes.process = "*-ntds*" (Processes.process = "*-system*" OR Processes.process = "*-sam*" OR Processes.process = "*-security*" OR Processes.process = "*-bootkey*") by Processes.process_name Processes.process Processes.parent_process_name Processes.parent_process Processes.dest Processes.user Processes.process_id Processes.process_guid 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `secretdumps_offline_ntds_dumping_tool_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($field$)
secretdumps_offline_ntds_dumping_tool_filter search *
secretdumps_offline_ntds_dumping_tool_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1003.003 NTDS Credential Access
T1003 OS Credential Dumping Credential Access
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT28
APT41
Chimera
Dragonfly
FIN13
FIN6
Fox Kitten
HAFNIUM
Ke3chang
LAPSUS$
Mustang Panda
Sandworm Team
Scattered Spider
Volt Typhoon
Wizard Spider
menuPass
APT28
APT32
APT39
Axiom
Leviathan
Poseidon Group
Sowbug
Suckfly
Tonto Team

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 Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

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 secretdump process $process_name$ with secretdump commandline $process$ to dump credentials in host $dest$ 80 80 100
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

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