CVE-2024-5206

mediumpriority · track · 19EPSS 0.002 · 8 %ileDEEUNLUS
grimoire priorityP3 · Track
Exploitable?
—
no known exploitation
Likely / severe?
0.19% (8th) EPSS
CVSS 4.7 · medium
Is it mine?
84 products
Check your exposure
Who says so?
5 sources
cnnvd · enisa_euvd · osv · cert_bund

EPSS · scored 2026-10-23

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.

01

cvss

Technical severity, 0–10. One row per scoring source.

5.3
010

base score 0–10 · higher = more severe · hover a vector to decode

v3.14.7mediumCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nprimary · NVD / NIST USexploitability 1 · impact 3.6
v3.04.7mediumCVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nsecondary · ENISA EU
v3.05.3mediumCVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nsecondary · NCSC-NL NL
v3.04.7mediumCVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nsecondary · security@huntr.devexploitability 1 · impact 3.6
v3.05.3mediumCVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nsecondary · OSV
v3.14.7mediumCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:Nsecondary · OSV
v3.14.3mediumCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N/E:Usecondary · CVSS-BT (t0sche)
02

ssvc

A stakeholder decision — act, attend, or track — from exploitation and impact.

Exploitation: poc · Automatable: no · Technical Impact: partialcoordinatorcisa_ssvcUS
03

weaknesses

The CWE weakness classes this flaw belongs to.

CWE-922USprimaryCWE-921USCWE-921USCWE-921USCWE-922US
04

affected products (84)

Products and version ranges known to be affected.

showing 20 of 84
05

advisories (6)

Vendor and ecosystem advisories describing this.

  • NCSC-2025-0127Kwetsbaarheden verholpen in Oracle Financial ServicesNL2025-04-16csaf · ncsc_nlNL

    Oracle heeft kwetsbaarheden verholpen in verschillende Financial Services producten

  • WID-SEC-W-2024-1802IBM Business Automation Workflow: Mehrere SchwachstellenDeutsch2024-08-08csaf · cert_bundDE

    Ein entfernter Angreifer kann mehrere Schwachstellen in IBM Business Automation Workflow ausnutzen, um Informationen offenzulegen oder beliebigen Code auszuführen.

  • WID-SEC-W-2025-0225Dell PowerProtect Data Domain: Mehrere SchwachstellenDeutsch2025-01-30csaf · cert_bundDE

    Ein Angreifer kann mehrere Schwachstellen in Dell PowerProtect Data Domain ausnutzen, um erhöhte Rechte zu erlangen, einen Denial-of-Service-Zustand herbeizuführen und einen nicht näher spezifizierten Angriff durchzuführen.

  • WID-SEC-W-2025-0819Oracle Financial Services Applications: Mehrere SchwachstellenDeutsch2025-04-15csaf · cert_bundDE

    Ein entfernter, anonymer oder authentisierter Angreifer kann mehrere Schwachstellen in Oracle Financial Services Applications ausnutzen, um die Vertraulichkeit, Integrität und Verfügbarkeit zu gefährden.

  • GHSA-jw8x-6495-233vscikit-learn sensitive data leakage vulnerability2024-06-06ghsa · osvUS

    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.

  • PYSEC-2024-1102024-06-06vendor · osvUS

    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.

06

also known as (6)

Other names and identifiers for this entity.

07

sources

Which sources assert this record, and when.

cnnvdenisa_euvdosvcert_bundncsc_nlNVDCVE.orgMITRE
published 2024-06-06modified 2026-06-17
09

references (9)

External citations — patches, advisories, analysis.

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