CVE-2020-13092
First published: Fri May 15 2020(Updated: )
** DISPUTED ** scikit-learn (aka sklearn) through 0.23.0 can unserialize and execute commands from an untrusted file that is passed to the joblib.load() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the joblib.load() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner.
Credit: cve@mitre.org cve@mitre.org cve@mitre.org
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/scikit-learn | <=0.23.0 | |
| Scikit-learn | <=0.23.0 |
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Reference Links
- https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md
- https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
- https://nvd.nist.gov/vuln/detail/CVE-2020-13092
- https://github.com/advisories/GHSA-jjw5-xxj6-pcv5 (Advisory)
- https://github.com/pypa/advisory-database/tree/main/vulns/scikit-learn/PYSEC-2020-107.yaml
Frequently Asked Questions
What is the severity of CVE-2020-13092?
CVE-2020-13092 is considered a medium severity vulnerability due to the potential for remote code execution.
How do I fix CVE-2020-13092?
To mitigate CVE-2020-13092, upgrade to scikit-learn version 0.24.0 or later where this issue is resolved.
What software is affected by CVE-2020-13092?
CVE-2020-13092 affects scikit-learn versions up to and including 0.23.0.
What is the nature of the vulnerability in CVE-2020-13092?
CVE-2020-13092 involves the unserialization of untrusted files through the joblib.load() function which can lead to the execution of arbitrary commands.
Is CVE-2020-13092 a confirmed vulnerability?
CVE-2020-13092 is disputed by some parties who claim that the joblib.load() function is documented as unsafe.
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