Detection: ProxyShell ProxyNotShell Behavior Detected

Updated Date: 2024-05-21 ID: c32fab32-6aaf-492d-bfaf-acbed8e50cdf Author: Michael Haag, Splunk Type: Correlation Product: Splunk Enterprise Security

Description

The following analytic identifies potential exploitation of Windows Exchange servers via ProxyShell or ProxyNotShell vulnerabilities, followed by post-exploitation activities such as running nltest, Cobalt Strike, Mimikatz, and adding new users. It leverages data from multiple analytic stories, requiring at least five distinct sources to trigger, thus reducing noise. This activity is significant as it indicates a high likelihood of an active compromise, potentially leading to unauthorized access, privilege escalation, and persistent threats within the environment. If confirmed malicious, attackers could gain control over the Exchange server, exfiltrate data, and maintain long-term access.

1
2| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as risk_score, count(All_Risk.calculated_risk_score) as risk_event_count, values(All_Risk.annotations.mitre_attack.mitre_tactic_id) as annotations.mitre_attack.mitre_tactic_id, dc(All_Risk.annotations.mitre_attack.mitre_tactic_id) as mitre_tactic_id_count, values(All_Risk.analyticstories) as analyticstories values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count, values(All_Risk.tag) as tag, values(source) as source, dc(source) as source_count dc(All_Risk.analyticstories) as dc_analyticstories from datamodel=Risk.All_Risk where All_Risk.analyticstories IN ("ProxyNotShell","ProxyShell") OR (All_Risk.analyticstories IN ("ProxyNotShell","ProxyShell") AND All_Risk.analyticstories="Cobalt Strike") All_Risk.risk_object_type="system" by _time span=1h All_Risk.risk_object All_Risk.risk_object_type 
3| `drop_dm_object_name(All_Risk)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)`
6| where source_count >=5 
7| `proxyshell_proxynotshell_behavior_detected_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
proxyshell_proxynotshell_behavior_detected_filter search *
proxyshell_proxynotshell_behavior_detected_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_AE
Cis18Value.CIS_13
APT28
APT29
APT39
APT41
APT5
Axiom
BackdoorDiplomacy
BlackTech
Blue Mockingbird
Cinnamon Tempest
Dragonfly
Earth Lusca
FIN13
FIN7
Fox Kitten
GALLIUM
GOLD SOUTHFIELD
HAFNIUM
Ke3chang
Kimsuky
Magic Hound
Moses Staff
MuddyWater
Rocke
Sandworm Team
Threat Group-3390
ToddyCat
Volatile Cedar
Volt Typhoon
menuPass
APT18
APT28
APT29
APT41
Akira
Chimera
Dragonfly
FIN13
FIN5
GALLIUM
GOLD SOUTHFIELD
Ke3chang
Kimsuky
LAPSUS$
Leviathan
OilRig
Sandworm Team
Scattered Spider
TeamTNT
Threat Group-3390
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 False
This configuration file applies to all detections of type Correlation. These correlations will generate Notable Events.

Implementation

To implement this correlation, you will need to enable ProxyShell, ProxyNotShell and Cobalt Strike analytic stories (the anaytics themselves) and ensure proper data is being collected for Web and Endpoint datamodels. Run the correlation rule seperately to validate it is not triggering too much or generating incorrectly. Validate by running ProxyShell POC code and Cobalt Strike behavior.

Known False Positives

False positives will be limited, however tune or modify the query as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
ProxyShell or ProxyNotShell activity has been identified on $risk_object$. 81 90 90
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 proxyshell stash
Integration ✅ Passing Dataset proxyshell stash

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