Vulnerability in Scikit-Learn

CVE-2024-5206

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.

EPSS: 0.002 (8.5th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 4.7 (Medium). Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N.

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2024-5206?
CVE-2024-5206 is a medium-severity vulnerability in Scikit-Learn, classified under CWE-921. CVSS score: 4.7/10. Published 2024-06-06.
How severe is CVE-2024-5206?
Medium severity. CVSS v3 base score is 4.7 out of 10.
Is CVE-2024-5206 known to be exploited?
2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.