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yawkat LZ4 Java has a possible information leak in Java safe decompressor

High severity GitHub Reviewed Published Dec 5, 2025 in yawkat/lz4-java • Updated Dec 5, 2025

Package

maven at.yawk.lz4:lz4-java (Maven)

Affected versions

<= 1.10.0

Patched versions

1.10.1
maven net.jpountz.lz4:lz4 (Maven)
<= 1.8.1
None
maven org.lz4:lz4-java (Maven)
<= 1.8.1
None
maven org.lz4:lz4-pure-java (Maven)
<= 1.8.1
None

Description

Summary

Insufficient clearing of the output buffer in Java-based decompressor implementations in lz4-java 1.10.0 and earlier allows remote attackers to read previous buffer contents via crafted compressed input. In applications where the output buffer is reused without being cleared, this may lead to disclosure of sensitive data.

JNI-based implementations are not affected.

Details

During the decompression process, the lz4 algorithm may have to repeat data that was previously decompressed in the same input frame. In the Java implementation, this is implemented by copy operations within the output buffer.

With a crafted input, an attacker may induce the Java implementation to copy from a region in the output buffer that does not contain decompressed data yet. If that region contains sensitive information because the output buffer was not cleared prior to decompression, that data will then be copied to the decompressed output.

  • LZ4Factory.nativeInstance().safeDecompressor() is not affected.
  • LZ4Factory.nativeInstance().fastDecompressor() is affected because it actually uses safeInstance() since 1.8.1. In 1.8.0 and earlier versions, this implementation is instead vulnerable to the more severe CVE‐2025‐12183, so downgrading is not a solution.
  • Both decompressors of LZ4Factory.safeInstance(), LZ4Factory.unsafeInstance() and LZ4Factory.fastestJavaInstance() are affected.
  • LZ4Factory.fastestInstance() uses the nativeInstance or fastestJavaInstance depending on platform. LZ4Factory.fastestInstance().fastDecompressor() is always affected, while LZ4Factory.fastestInstance().safeDecompressor() is affected only when JNI cannot be used (e.g. on unsupported platforms).

Independent of this vulnerability, it is recommended that users migrate from fastDecompressor to safeDecompressor, as the latter is more performant (despite the name).

The impact of this vulnerability depends on how user code interacts with the decompression API. Users that allocate a new destination buffer each time, or use only zeroed buffers, are not impacted. When the buffer is reused, however, the confidentiality impact can be severe. This vulnerability is marked as VC:H out of caution.

Mitigation

lz4-java 1.10.1 fixes this issue without requiring changes in user code.

If you cannot upgrade to 1.10.1, you can mitigate this vulnerability by zeroing the output buffer before passing it to the decompression function.

Relation to CVE‐2025‐12183

This CVE is a different attack than CVE‐2025‐12183, affecting different implementations with different impact. This new vulnerability was discovered by CodeIntelligence during research that followed up on CVE‐2025‐12183. Users are recommended to upgrade to 1.10.1 to fix both vulnerabilities.

References

@yawkat yawkat published to yawkat/lz4-java Dec 5, 2025
Published by the National Vulnerability Database Dec 5, 2025
Published to the GitHub Advisory Database Dec 5, 2025
Reviewed Dec 5, 2025
Last updated Dec 5, 2025

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Insertion of Sensitive Information Into Sent Data

The code transmits data to another actor, but a portion of the data includes sensitive information that should not be accessible to that actor. Learn more on MITRE.

CVE ID

CVE-2025-66566

GHSA ID

GHSA-cmp6-m4wj-q63q

Source code

Credits

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