:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

Try in Splunk Security Cloud

Description

This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Web
  • Last Updated: 2017-09-23
  • Author: Bhavin Patel, Splunk
  • ID: 104658f4-afdc-499e-9719-17243f982681

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1082 System Information Discovery Discovery
T1133 External Remote Services Persistence, Initial Access
Kill Chain Phase
  • Exploitation
  • Installation
  • Delivery
NIST
  • DE.CM
CIS20
  • CIS 13
CVE
1
2
3
4
5
6
| 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") AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest 
| `drop_dm_object_name("Web")` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `detect_attackers_scanning_for_vulnerable_jboss_servers_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_attackers_scanning_for_vulnerable_jboss_servers_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Web.http_method
  • Web.url
  • Web.src
  • Web.dest

How To Implement

You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model.

Known False Positives

It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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

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