Information disclosure via guessable Py4J token
Published Sep 24, 2024 · Updated Sep 24, 2024
Inadequate token entropy in Apache Linkis Spark EngineConn before 1.6.0 allows remote attackers to read data through Py4J. SparkPythonExecutor derives py4jToken from an integer below 100,000, leaving only 100,000 possible values instead of using a long cryptographic token. A Python Spark session and network access to its Py4J interface are required; successful guessing exposes session data without altering it.
Summary
What happened
Inadequate token entropy in Apache Linkis Spark EngineConn before 1.6.0 allows remote attackers to read data through Py4J. SparkPythonExecutor derives py4jToken from an integer below 100,000, leaving only 100,000 possible values instead of using a long cryptographic token. A Python Spark session and network access to its Py4J interface are required; successful guessing exposes session data without altering it.
The record
- CVE
- CVE-2024-39928
- Published
- Sep 24, 2024
- Updated
- Sep 24, 2024
- Vendor
- The Apache Software Foundation
- Product
- Apache Linkis Spark EngineConn
- Classifications
- CWE-326, T1110
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Sep 24, 2024CVE publishedPublication date reported by the CVE source.
- Sep 24, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=1.3.0 <1.6.0
- Affected versionversion=13.0 <1.6.0
What conditions does exploitation require?
What is affected?
Published CVSS scores
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Attacks
What attackers are doing with it
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Public exploit references
No public exploit references are available in this record.
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Technologies
Your stack
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Your stack
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