CVE-2024-5206
low-risk
Published 2024-06-06
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.
Do I need to act?
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0.04% chance of exploitation
EPSS score — low exploit probability
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Not on CISA KEV list
No confirmed active exploitation reported to CISA
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Patch status unknown
Check vendor advisories for fix availability and mitigation guidance
4
CVSS 4.7/10
Medium
LOCAL
/ HIGH complexity
Affected Products (1)
Scikit-Learn
Affected Vendors
References (4)
Third Party Advisory
https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c
Third Party Advisory
https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c
17
/ 100
low-risk
Severity
12/34 · Low
Exploitability
0/34 · Minimal
Exposure
5/34 · Minimal