Detection: Spring4Shell Payload URL Request

Updated Date: 2024-05-26 ID: 9d44d649-7d67-4559-95c1-8022ff49420b Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects attempts to exploit the Spring4Shell vulnerability (CVE-2022-22963) by identifying specific URL patterns associated with web shell payloads. It leverages web traffic data, focusing on HTTP GET requests with URLs containing indicators like "tomcatwar.jsp," "poc.jsp," and "shell.jsp." This activity is significant as it suggests an attacker is trying to deploy a web shell, which can lead to remote code execution. If confirmed malicious, this could allow the attacker to gain persistent access, execute arbitrary commands, and potentially escalate privileges within the compromised environment.

1
2| tstats count from datamodel=Web where Web.http_method IN ("GET") Web.url IN ("*tomcatwar.jsp*","*poc.jsp*","*shell.jsp*") by Web.http_user_agent Web.http_method, Web.url,Web.url_length Web.src, Web.dest sourcetype 
3| `drop_dm_object_name("Web")` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `spring4shell_payload_url_request_filter`

Data Source

Name Platform Sourcetype Source Supported App
Nginx Access N/A 'nginx:plus:kv' '/var/log/nginx/access.log' N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
spring4shell_payload_url_request_filter search *
spring4shell_payload_url_request_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
T1505.003 Web Shell Persistence
T1505 Server Software Component Persistence
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
APT32
APT38
APT39
APT5
BackdoorDiplomacy
Deep Panda
Dragonfly
FIN13
Fox Kitten
GALLIUM
HAFNIUM
Kimsuky
Leviathan
Magic Hound
Moses Staff
OilRig
Sandworm Team
Threat Group-3390
Tonto Team
Tropic Trooper
Volatile Cedar
Volt Typhoon
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 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 that include fields relavent for traffic into the Web datamodel.

Known False Positives

The jsp file names are static names used in current proof of concept code. =

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A URL was requested related to Spring4Shell POC code on $dest$ by $src$. 36 60 60
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 /var/log/nginx/access.log nginx:plus:kv
Integration ✅ Passing Dataset /var/log/nginx/access.log nginx:plus:kv

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