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cpe:2.3:a:scikit-learn:scikit-learn:*:*:*:*:*:python:*:*

part: a version: * update: *

VendorScikit Learn (e6549cc1-332c-5bd1-b6e8-01d6d7e90c02)
ProductScikit Learn (dcb2a3c4-27ca-528b-9319-99087fd7652d)
Edition*
Language*
Software edition*
Target softwarepython
Target hardware*
Other*
NotesImported from purl2cpe mapping

PURL mappings

PURLSourceLast updated
pkg:deb/debian/scikit-learn purl2cpe 2026-06-01 10:12:28.887086
pkg:deb/ubuntu/scikit-learn purl2cpe 2026-06-01 10:12:28.887088
pkg:github/scikit-learn/scikit-learn purl2cpe 2026-06-01 10:12:28.887090
pkg:pypi/scikit-learn purl2cpe 2026-06-01 10:12:28.887091
pkg:rpm/fedora/python-scikit-learn purl2cpe 2026-06-01 10:12:28.887093
pkg:rpm/opensuse/python-scikit-learn purl2cpe 2026-06-01 10:12:28.887094

Vulnerability references

IdentifiercpeApplicabilitySubmitteddb.gcve.eu detailsRationale
CVE:CVE-2024-5206 vulnerable 2026-06-08 06:56:15.155513 Sensitive Data Leakage in sklearn.feature_extraction.text.TfidfVectorizer in scikit-learn/scikit-learn
MEDIUM (4.7)
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.
Published: 2024-06-06T18:28:14.267Z
Updated: 2024-08-01T21:03:11.034Z
Reference links
Imported from gcve-enriched-dumps CVE data

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