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Apache Hadoop Flaw Could Trigger System Crashes or Data Corruption

A moderate out-of-bounds write vulnerability in Apache Hadoop's HDFS native client has been identified, potentially allowing system crashes or data corruption in production environments.

CBy Charles NolanJan 26, 20261 min read

A moderate out-of-bounds write vulnerability in Apache Hadoop's HDFS native client has been identified, potentially allowing system crashes or data corruption in production environments.

The flaw, identified as CVE-2025-27821, affects the native HDFS client's URI parser and has been assigned moderate severity by Apache.

This vulnerability was discovered and reported by security researcher BUI Ngoc Tan.

Apache Hadoop is a widely used distributed storage and processing framework, essential for big data operations across numerous enterprises. The HDFS (Hadoop Distributed File System) native client is frequently deployed in data pipelines and cluster management configurations.

An out-of-bounds write condition in the URI parser can enable untrusted input to write data beyond allocated memory boundaries, potentially corrupting system memory or causing denial-of-service conditions.

The vulnerability impacts Apache Hadoop HDFS native client versions 3.2.0 through 3.4.1. Systems running version 3.4.2 or later are not affected.

Apache recommends that all affected organizations immediately upgrade to version 3.4.2, which includes the necessary patches to address the vulnerability. The issue is being tracked under JIRA ticket HDFS-17754.

The flaw, identified as CVE-2025-27821, affects the native HDFS client's URI parser and has been assigned moderate severity by Apache.
Charles Nolan · Thehackingpost

Field Details

CVE ID CVE-2025-27821

Component Apache Hadoop HDFS Native Client (org.apache.hadoop:hadoop-hdfs-native-client)

Vulnerability Type Out-of-Bounds Write in URI Parser

Severity Moderate

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The out-of-bounds write occurs during URI parsing, suggesting the vulnerability could be exploited by providing maliciously crafted URIs to HDFS clients.

Successful exploitation could lead to memory corruption, uncontrolled system behavior, data loss, or complete system unavailability.

Organizations storing sensitive data on HDFS clusters are at particular risk if the vulnerability is exploited in production environments.

Organizations should assess their Hadoop deployment versions and prioritize upgrading to patched releases. System administrators should monitor HDFS logs for suspicious URI patterns and consider implementing network-level access controls to restrict HDFS client connections to trusted sources. Patch management procedures should prioritize this vulnerability due to its potential for system-level impact.

Based on reporting by GBHackers.

AI transparency. This article was produced with the assistance of artificial intelligence and published under human editorial oversight. AI systems can make mistakes. Read how we use AI (EU AI Act, Art. 50).
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