Detection: Adobe ColdFusion Access Control Bypass

Updated Date: 2024-09-30 ID: d6821c0b-fcdc-4c95-a77f-e10752fae41a Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects potential exploitation attempts against Adobe ColdFusion vulnerabilities CVE-2023-29298 and CVE-2023-26360. It monitors requests to specific ColdFusion Administrator endpoints, especially those with an unexpected additional forward slash, using the Web datamodel. This activity is significant for a SOC as it indicates attempts to bypass access controls, which can lead to unauthorized access to ColdFusion administration endpoints. If confirmed malicious, this could result in data theft, brute force attacks, or further exploitation of other vulnerabilities, posing a serious security risk to the environment.

1
2| tstats count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where Web.url IN ("//restplay*", "//CFIDE/restplay*", "//CFIDE/administrator*", "//CFIDE/adminapi*", "//CFIDE/main*", "//CFIDE/componentutils*", "//CFIDE/wizards*", "//CFIDE/servermanager*","/restplay*", "/CFIDE/restplay*", "/CFIDE/administrator*", "/CFIDE/adminapi*", "/CFIDE/main*", "/CFIDE/componentutils*", "/CFIDE/wizards*", "/CFIDE/servermanager*") Web.status=200 by Web.http_user_agent, Web.status, 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| `adobe_coldfusion_access_control_bypass_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($field$)
adobe_coldfusion_access_control_bypass_filter search *
adobe_coldfusion_access_control_bypass_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

This detection requires the Web datamodel to be populated from a supported Technology Add-On like Splunk for Apache, Splunk for Nginx, or Splunk for Palo Alto.

Known False Positives

This analytic is limited to HTTP Status 200; adjust as necessary. False positives may occur if the URI path is IP-restricted or externally blocked. It's recommended to review the context of the alerts and adjust the analytic parameters to better fit the specific environment.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Possible exploitation of CVE-2023-29298 against $dest$. 45 90 50
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