Detection: Detect malicious requests to exploit JBoss servers

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-10-17 ID: c8bff7a4-11ea-4416-a27d-c5bca472913d Author: Bhavin Patel, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic identifies malicious HTTP requests targeting the jmx-console in JBoss servers. It detects unusually long URLs, indicative of embedded payloads, by analyzing web server logs for GET or HEAD requests with specific URL patterns and lengths. This activity is significant as it may indicate an attempt to exploit JBoss vulnerabilities, potentially leading to unauthorized remote code execution. If confirmed malicious, attackers could gain control over the server, escalate privileges, and compromise sensitive data, posing a severe threat to the organization's security.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") by Web.http_method, Web.url,Web.url_length Web.src, Web.dest 
3| search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" AND Web.url_length > 200 
4| `drop_dm_object_name("Web")` 
5| `security_content_ctime(firstTime)` 
6| `security_content_ctime(lastTime)` 
7| table src, dest_ip, http_method, url, firstTime, lastTime 
8| `detect_malicious_requests_to_exploit_jboss_servers_filter`

Data Source

No data sources specified for this detection.

Macros Used

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

detect_malicious_requests_to_exploit_jboss_servers_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

NistCategory.DE_CM

Cis18Value.CIS_13

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

You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model

Known False Positives

No known false positives for this detection.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
tbd	25	50	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.

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	❌ Failing	N/A	`N/A`	`N/A`
Integration	❌ Failing	N/A	`N/A`	`N/A`

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