scikit-learn Deserialization of Untrusted Data
CVE-2020-13092GHSA-jjw5-xxj6-pcv5
What to do
Vendor response not established. Follow the primary source's mitigation guidance and check back for a fix.
This page has no inventory attached, so it cannot say whether you are affected. A vendor fix is not proof that your deployment is fixed.
Affected packages
PyPI scikit-learn
- Affected
- <= 0.23.0
- Fixed in
- no fixed version recorded
Sources
- Open Source Vulnerabilities (OSV.dev), including the GitHub Advisory Database
OSV record GHSA-jjw5-xxj6-pcv5 lists affected ranges: PyPI scikit-learn >=0 <=0.23.0
VerifiedObserved Structured OSV record; GitHub-reviewed advisory.
- GitHub Advisory Database and maintainer security advisories on GitHub
GitHub-reviewed advisory GHSA-jjw5-xxj6-pcv5 lists affected ranges: PyPI scikit-learn >=0 <=0.23.0
VerifiedObserved Structured GitHub Advisory Database record (type=reviewed) from the GitHub REST API.
Severity and exploitation
- Exploitation
- No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.
- CVSS
- 9.8 · CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
- EPSS
- CVE-2020-13092: 3.41% estimated exploitation activity in the next 30 days; percentile 88.88 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.
Source description
As published by the source; long descriptions are shortened.
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.
Dates and revisions
- Published by the source
- Last modified by the source
- Source last checked
- Revision 2 · amended ·
Amended from ghsa record GHSA-jjw5-xxj6-pcv5
- Revision 1 · created ·
Published from osv record GHSA-jjw5-xxj6-pcv5
Agent brief
Preview the exact text before you copy it. Commands are read-only suggestions; review them before running anything.
# Patch Next advisory brief: CVE-2020-13092 Advisory: scikit-learn Deserialization of Untrusted Data IDs: CVE-2020-13092, GHSA-jjw5-xxj6-pcv5 Record: https://patchnext.com/advisories/cve-2020-13092 (revision 2, source checked 26 Oct 2026, 13:22 UTC) Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected. Severity: Critical (CVSS 9.8) Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV. Vendor response: Vendor response not established. A vendor fix does not mean a deployment is fixed. ## Affected components - PyPI scikit-learn: affected <= 0.23.0 ## Suggested inspection (read-only) - `python -m pip show scikit-learn`: prints the installed version. Run with the environment that serves production active. ## Supported action No complete vendor fix is recorded. Follow the primary source's mitigation guidance and check this record again before closing anything. ## Required regression checks - Run the test suite and a production build. - Exercise the features that depend on scikit-learn. - Repeat the inspection and confirm that only fixed versions remain installed. ## Rollback considerations - Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward. ## Unresolved questions - Which deployments run an affected version? - Exploitation status can change. Check again before lowering the priority. - Mark the work resolved only after the fixed version is verified in production. ## Sources - Verified: https://osv.dev/vulnerability/GHSA-jjw5-xxj6-pcv5 (OSV record GHSA-jjw5-xxj6-pcv5 lists affected ranges: PyPI scikit-learn >=0 <=0.23.0) - Verified: https://github.com/advisories/GHSA-jjw5-xxj6-pcv5 (GitHub-reviewed advisory GHSA-jjw5-xxj6-pcv5 lists affected ranges: PyPI scikit-learn >=0 <=0.23.0) Commands are suggestions: review each one before running it.
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