CVE-2024-5206

MEDIUM
Published June 6, 2024

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...

Full analysis pending. Showing NVD description excerpt.

Affected Systems

Package Ecosystem Vulnerable Range Patched
scikit-learn pip No patch

Do you use scikit-learn? You're affected.

Severity & Risk

CVSS 3.1
4.7 / 10
EPSS
N/A
KEV Status
Not in KEV
Sophistication
N/A

Recommended Action

No patch available

Monitor for updates. Consider compensating controls or temporary mitigations.

Compliance Impact

Compliance analysis pending. Sign in for full compliance mapping when available.

Technical Details

NVD 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.

CVSS Vector

CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N

Timeline

Published
June 6, 2024
Last Modified
November 21, 2024
First Seen
June 6, 2024