Remote Service creation#

Hypothesis#

Adversaries might be creating new services remotely to execute code and move laterally in my environment

Technical Context#

Offensive Tradecraft#

Adversaries may execute a binary, command, or script via a method that interacts with Windows services, such as the Service Control Manager. This can be done by by adversaries creating a new service. Adversaries can create services remotely to execute code and move lateraly across the environment.

Pre-Recorded Security Datasets#

Metadata

Value

docs

https://securitydatasets.com/notebooks/atomic/windows/lateral_movement/SDWIN-190518210652.html

link

https://raw.githubusercontent.com/OTRF/Security-Datasets/master/datasets/atomic/windows/lateral_movement/host/empire_psexec_dcerpc_tcp_svcctl.zip

Download Dataset#

import requests
from zipfile import ZipFile
from io import BytesIO

url = 'https://raw.githubusercontent.com/OTRF/Security-Datasets/master/datasets/atomic/windows/lateral_movement/host/empire_psexec_dcerpc_tcp_svcctl.zip'
zipFileRequest = requests.get(url)
zipFile = ZipFile(BytesIO(zipFileRequest.content))
datasetJSONPath = zipFile.extract(zipFile.namelist()[0])

Read Dataset#

import pandas as pd
from pandas.io import json

df = json.read_json(path_or_buf=datasetJSONPath, lines=True)

Analytics#

Analytic I#

Look for new services being created in your environment under a network logon session (3). That is a sign that the service creation was performed from another endpoint in the environment.

Data source

Event Provider

Relationship

Event

Service

Microsoft-Windows-Security-Auditing

User created Service

4697

Authentication log

Microsoft-Windows-Security-Auditing

User authenticated Host

4624

Logic#

SELECT o.`@timestamp`, o.Hostname, o.SubjectUserName, o.SubjectUserName, o.ServiceName, a.IpAddress
FROM dataTable o
INNER JOIN (
    SELECT Hostname,TargetUserName,TargetLogonId,IpAddress
    FROM dataTable
    WHERE LOWER(Channel) = "security"
        AND EventID = 4624
        AND LogonType = 3            
        AND NOT TargetUserName LIKE "%$"
    ) a
ON o.SubjectLogonId = a.TargetLogonId
WHERE LOWER(o.Channel) = "security"
    AND o.EventID = 4697

Pandas Query#

serviceInstallDf= (
df[['@timestamp','Hostname','SubjectUserName','SubjectLogonId','ServiceName','ServiceType']]

[(df['Channel'].str.lower() == 'security')
    & (df['EventID'] == 4697)
]
)

networkLogonDf = (
df[['@timestamp', 'Hostname', 'TargetUserName', 'TargetLogonId', 'IpAddress']]

[(df['Channel'].str.lower() == 'security')
    & (df['EventID'] == 4624)
    & (df['LogonType'] == 3)
    & (~df['SubjectUserName'].str.endswith('$', na=False))
]
)

(
pd.merge(serviceInstallDf, networkLogonDf,
  left_on = 'SubjectLogonId', right_on = 'TargetLogonId', how = 'inner')
)

Known Bypasses#

False Positives#

Hunter Notes#

  • If there are a lot of unique services being created in your environment, try to categorize the data based on the bussiness unit.

  • Identify the source of unique services being created everyday. I have seen Microsoft applications doing this.

  • Stack the values of the service file name associated with the new service.

  • Document what users create new services across your environment on a daily basis