Detection: Confluence Data Center and Server Privilege Escalation

Updated Date: 2024-09-30 ID: 115bebac-0976-4f7d-a3ec-d1fb45a39a11 Author: Michael Haag, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic identifies potential exploitation attempts on a known vulnerability in Atlassian Confluence, specifically targeting the /setup/.action URL pattern. It leverages web logs within the Splunk 'Web' Data Model, filtering for successful accesses (HTTP status 200) to these endpoints. This activity is significant as it suggests attackers might be exploiting a privilege escalation flaw in Confluence. If confirmed malicious, it could result in unauthorized access or account creation with escalated privileges, leading to potential data breaches or further exploitation within the environment.

Search

1
2| tstats count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where Web.url IN ("*/setup/setupadministrator.action*", "*/setup/finishsetup.action*", "*/json/setup-restore-local.action*", "*/json/setup-restore-progress.action*", "*/json/setup-restore.action*", "*/bootstrap/selectsetupstep.action*") 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| `confluence_data_center_and_server_privilege_escalation_filter`

Data Source

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

Macros Used

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

confluence_data_center_and_server_privilege_escalation_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

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

False positives may be present with legitimate applications. Attempt to filter by dest IP or use Asset groups to restrict to confluence servers.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
Potential exploitation attempts on a known vulnerability in Atlassian Confluence detected. The source IP is $src$ and the destination hostname is $dest$.	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	`nginx:plus:kv`	`nginx:plus:kv`
Integration	✅ Passing	Dataset	`nginx:plus:kv`	`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: 5