Detection: Windows Exchange Autodiscover SSRF Abuse

Updated Date: 2024-09-30 ID: d436f9e7-0ee7-4a47-864b-6dea2c4e2752 Author: Michael Haag, Nathaniel Stearns, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects potential abuse of the ProxyShell or ProxyNotShell vulnerabilities in Microsoft Exchange via Server Side Request Forgery (SSRF). It leverages the Web datamodel to identify suspicious POST requests with specific URI paths and queries related to autodiscover, powershell, and mapi. This activity is significant as it may indicate an attempt to exploit Exchange server vulnerabilities to access internal services or sensitive data. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or further compromise of the network.

Search

 1
 2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.status=200 OR Web.status=302 OR Web.status=401) AND Web.http_method=POST by Web.src Web.status Web.uri_path Web.dest Web.http_method Web.uri_query 
 3| `drop_dm_object_name("Web")` 
 4| eval is_autodiscover=if(like(lower(uri_path),"%autodiscover%"),1,0) 
 5| eval powershell = if(match(lower(uri_query),"powershell"), "1",0) 
 6| eval mapi=if(like(uri_query,"%/mapi/%"),1,0) 
 7| addtotals fieldname=Score is_autodiscover, powershell, mapi 
 8| fields Score, src,dest, status, uri_query,uri_path,http_method 
 9| where Score >= 2 
10| `security_content_ctime(firstTime)` 
11| `security_content_ctime(lastTime)` 
12| `windows_exchange_autodiscover_ssrf_abuse_filter`

Data Source

Name	Platform	Sourcetype	Source
Windows IIS	Windows	`'IIS:Configuration:Operational'`	`'IIS:Configuration:Operational'`

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
windows_exchange_autodiscover_ssrf_abuse_filter	`search *`

windows_exchange_autodiscover_ssrf_abuse_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
T1190	Exploit Public-Facing Application	Initial Access
T1133	External Remote Services	Initial Access

KillChainPhase.DELIVERY

KillChainPhase.INSTALLATION

NistCategory.DE_CM

Cis18Value.CIS_13

APT28

APT29

APT39

APT41

APT5

Agrius

Axiom

BackdoorDiplomacy

BlackTech

Blue Mockingbird

Cinnamon Tempest

Dragonfly

Earth Lusca

Ember Bear

FIN13

FIN7

Fox Kitten

GALLIUM

GOLD SOUTHFIELD

HAFNIUM

INC Ransom

Ke3chang

Kimsuky

Magic Hound

Moses Staff

MuddyWater

Play

Rocke

Sandworm Team

Threat Group-3390

ToddyCat

Volatile Cedar

Volt Typhoon

Winter Vivern

menuPass

APT18

APT28

APT29

APT41

Akira

Chimera

Dragonfly

Ember Bear

FIN13

FIN5

GALLIUM

GOLD SOUTHFIELD

Ke3chang

Kimsuky

LAPSUS$

Leviathan

OilRig

Play

Sandworm Team

Scattered Spider

TeamTNT

Threat Group-3390

Volt Typhoon

Wizard Spider

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

To successfully implement this search you need to be ingesting information on Web traffic, Exchange OR IIS logs, mapped to Web datamodel in the Web node. In addition, confirm the latest CIM App 4.20 or higher is installed.

Known False Positives

False positives are limited.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
Activity related to ProxyShell or ProxyNotShell has been identified on $dest$. Review events and take action accordingly.	72	90	80

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	`ms:iis:splunk`	`ms:iis:splunk`
Integration	✅ Passing	Dataset	`ms:iis:splunk`	`ms:iis:splunk`

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: 3