CVE-2024-5206

4.7 MEDIUM 0.2% exploit odds Fix listed Other

What it is

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.

At a glance

Exploitability: Can be exploited locally on the machine with a low-privilege account. High risk of data exposure.
Exploit odds: 0.2% chance of exploitation in the next 30 days (EPSS).
Fix: A patch, advisory or fixed version is referenced. Upgrade or apply it.

Timeline

2024-06-06 19:16 UTC PublishedDisclosed publicly on CVE.org and NVD
2026-06-17 08:15 UTC Last updatedMost recent change to the record

Why it ranks here

Exploited in the wild: no, CISA does not list it.
Exploit odds: 0.2% in the next 30 days (EPSS).
Severity: 4.7 MEDIUM (CVSS).
Fix: a patch or advisory is linked.

Details

Published: 2024-06-06 19:16 UTC
Last modified: 2026-06-17 08:15 UTC
Exploit probability: 0.2% · EPSS, next 30 days
Weakness: CWE-921
Record status: Modified

Affected

scikit-learn < 1.5.0

Attack profile CVSS 3.1 · 4.7

Attack vector: Local
Complexity: High
Privileges needed: Low
User interaction: None
Scope: Unchanged
Confidentiality: High
Integrity: None
Availability: None

Raw vector

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

Is it in your code?

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Fix and advisories

References

NVD record · CVE.org record