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MEDIUM severity

CVE-2024-5206 — scikit-learn

MEDIUMFix: scikit-learn/scikit-learn@70ca21f

CVE-2024-5206 is a medium-severity (CVSS 4.7) CWE-921 vulnerability in scikit-learn. A fix is available for scikit-learn — see the affected versions and patch details below.

Sensitive Data Leakage in sklearn.feature_extraction.text.TfidfVectorizer in scikit-learn/scikit-learn

Also known asGHSA-jw8x-6495-233vPYSEC-2024-110
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Nov 1, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for CVE-2024-5206.

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs9th percentile — riskier than 9% of all scored CVEsHighest risk
0.00%0.23%0.46%0.69%0.0%0.2%May 26Aug 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

1 pkg affected
🐍scikit-learn

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up to and including 1.4.1.post1, which was fixed in version 1.5.0. The vulnerability arises from the unexpected storage of all tokens present in the training data within the stop_words_ attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the stop_words_ attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIscikit-learnall versions1.5.0pip install --upgrade 'scikit-learn==1.5.0'

Affected Products

1 product · 1 configurations
Application
scikit-learnscikit-learn
< 1.5.0
range

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for scikit-learn, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update scikit-learn to 1.5.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2024-5206 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate
ProductFixed inAdvisory
Red Hat Ceph Storage 7.1rhceph/rhceph-7-rhel9:1791452477RHSA-2026:83548

Frequently Asked Questions

A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up to and including 1.4.1.post1, which was fixed in version 1.5.0. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or ke
O3 Security · Impact-Aware SCA

Is CVE-2024-5206 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2024-5206: scikit-learn Info Disclosure — Fixed in 1.5.0