Detection: JetBrains TeamCity Authentication Bypass CVE-2024-27198

Updated Date: 2024-09-30 ID: fbcc04c7-8a79-453c-b3a9-c232c423bdd4 Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic identifies attempts to exploit the JetBrains TeamCity Authentication Bypass vulnerability (CVE-2024-27198). It detects suspicious POST requests to the /app/rest/users and /app/rest/users/id:1/tokens endpoints, which are indicative of attempts to create new administrator users or generate admin access tokens without authentication. This detection leverages the Web datamodel and CIM-compliant log sources, such as Nginx or TeamCity logs. This activity is significant as it can lead to full control over the TeamCity server, including all projects, builds, agents, and artifacts. If confirmed malicious, attackers could gain unauthorized administrative access, leading to severe security breaches.

1
2| tstats count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where ((Web.url="*?jsp=*" AND Web.url="*;.jsp*") Web.status=200 Web.http_method=POST) OR (Web.url IN ("*jsp=/app/rest/users;.jsp","*?jsp=/app/rest/users;.jsp","*?jsp=.*/app/rest/users/id:*/tokens;*") Web.status=200 Web.http_method=POST ) by Web.src, Web.dest, Web.http_user_agent, Web.url, Web.status, Web.http_method, sourcetype, source 
3| `drop_dm_object_name("Web")` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)`
6| `jetbrains_teamcity_authentication_bypass_cve_2024_27198_filter`

Data Source

Name Platform Sourcetype Source
Suricata N/A 'suricata' 'suricata'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
jetbrains_teamcity_authentication_bypass_cve_2024_27198_filter search *
jetbrains_teamcity_authentication_bypass_cve_2024_27198_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
KillChainPhase.DELIVERY
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

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 relies on the Web datamodel and a CIM compliant log source, that may include Nginx, TeamCity logs, or other web server logs.

Known False Positives

False positives are not expected, as this detection is based on the presence of specific URI paths and HTTP methods that are indicative of the CVE-2024-27198 vulnerability exploitation. Monitor, filter and tune as needed based on organization log sources.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Possible JetBrains TeamCity Authentication Bypass CVE-2024-27198 Attempt against $dest$ from $src$. 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 suricata suricata
Integration ✅ Passing Dataset suricata suricata

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