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High, CVSS 7.5amended

scikit-learn Denial of Service

CVE-2020-28975GHSA-jxfp-4rvq-9h9m

What to do

Vendor fix available. Upgrade each affected package to the fixed version on its release line (scikit-learn 1.0.1), redeploy, then verify what is actually installed.

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.

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Affected packages

Sources

Severity and exploitation
Exploitation
No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.
CVSS
7.5 · CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS
  • CVE-2020-28975: 3.50% estimated exploitation activity in the next 30 days; percentile 89.18 (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.

svmpredictvalues in svm.cpp in Libsvm v324, as used in scikit-learn 0.23.2 and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the nsupport array. NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

Dates and revisions
Published by the source
Last modified by the source
Source last checked
  1. Revision 2 · amended ·

    Amended from ghsa record GHSA-jxfp-4rvq-9h9m

  2. Revision 1 · created ·

    Published from osv record GHSA-jxfp-4rvq-9h9m

Agent brief

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# Patch Next advisory brief: CVE-2020-28975

Advisory: scikit-learn Denial of Service
IDs: CVE-2020-28975, GHSA-jxfp-4rvq-9h9m
Record: https://patchnext.com/advisories/cve-2020-28975 (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: High (CVSS 7.5)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: scikit-learn 1.0.1. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI scikit-learn: affected >= 0.23.2, < 1.0.1; fixed in 1.0.1

## Suggested inspection (read-only)
- `python -m pip show scikit-learn`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## 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-jxfp-4rvq-9h9m (OSV record GHSA-jxfp-4rvq-9h9m lists affected ranges: PyPI scikit-learn >=0.23.2 <1.0.1 (fixed))
- Verified: https://github.com/advisories/GHSA-jxfp-4rvq-9h9m (GitHub-reviewed advisory GHSA-jxfp-4rvq-9h9m lists affected ranges: PyPI scikit-learn >=0.23.2 <1.0.1)

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