Apache Linkis <1.8.0 HiveUtils Base64 decode log info leak
CVE-2025-59355 Published on January 19, 2026
Apache Linkis: Password Exposure
A vulnerability.
When org.apache.linkis.metadata.util.HiveUtils.decode() fails to perform Base64 decoding, it records the complete input parameter string in the log via logger.error(str + "decode failed", e). If the input parameter contains sensitive information such as Hive Metastore keys, plaintext passwords will be left in the log files when decoding fails, resulting in information leakage.
Affected Scope
Component: Sensitive fields in hive-site.xml (e.g., javax.jdo.option.ConnectionPassword) or other fields encoded in Base64.
Version: Apache Linkis 1.0.0 1.7.0
Trigger Conditions
The value of the configuration item is an invalid Base64 string.
Log files are readable by users other than hive-site.xml administrators.
Severity: Low
The probability of Base64 decoding failure is low.
The leakage is only triggered when logs at the Error level are exposed.
Remediation
Apache Linkis 1.8.0 and later versions have replaced the log with desensitized content.
logger.error("URL decode failed: {}", e.getMessage()); // str
Users are recommended to upgrade to version 1.8.0, which fixes the issue.
Vulnerability Analysis
CVE-2025-59355 can be exploited with network access, and requires small amount of user privileges. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a high impact on confidentiality, with no impact on integrity and availability.
Weakness Type
Insertion of Sensitive Information into Log File
Information written to log files can be of a sensitive nature and give valuable guidance to an attacker or expose sensitive user information.
Products Associated with CVE-2025-59355
Want to know whenever a new CVE is published for Apache Linkis? stack.watch will email you.
Affected Versions
Apache Software Foundation Apache Linkis:- Version 1.0.0, <= 1.7.0 is affected.
Exploit Probability
EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.