Detection: Suspicious Java Classes

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: 6ed33786-5e87-4f55-b62c-cb5f1168b831 Author: Jose Hernandez, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies suspicious Java classes often used for remote command execution exploits in Java frameworks like Apache Struts. It detects this activity by analyzing HTTP POST requests with specific content patterns using Splunk's stream_http data source. This behavior is significant because it may indicate an attempt to exploit vulnerabilities in web applications, potentially leading to unauthorized remote code execution. If confirmed malicious, this activity could allow attackers to execute arbitrary commands on the server, leading to data breaches, system compromise, and further network infiltration.

Search

1`stream_http` http_method=POST http_content_length>1 
2| regex form_data="(?i)java\.lang\.(?:runtime
3|processbuilder)" 
4| rename src_ip as src 
5| stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest 
6| `security_content_ctime(firstTime)` 
7| `security_content_ctime(lastTime)` 
8| `suspicious_java_classes_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($field$)`
suspicious_java_classes_filter	`search *`

suspicious_java_classes_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_AE

Cis18Value.CIS_10

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 Risk Event	True

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro.

Known False Positives

There are no known false positives.

Associated Analytic Story

Apache Struts Vulnerability

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