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.
Metrics
Affected Vendors & Products
References
History
Thu, 24 Oct 2024 20:15:00 +0000
Type | Values Removed | Values Added |
---|---|---|
First Time appeared |
Scikit-learn
Scikit-learn scikit-learn |
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Weaknesses | CWE-922 | |
CPEs | cpe:2.3:a:scikit-learn:scikit-learn:*:*:*:*:*:python:*:* | |
Vendors & Products |
Scikit-learn
Scikit-learn scikit-learn |
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Metrics |
cvssV3_1
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MITRE
Status: PUBLISHED
Assigner: @huntr_ai
Published: 2024-06-06T18:28:14.267Z
Updated: 2024-08-01T21:03:11.034Z
Reserved: 2024-05-22T15:52:49.284Z
Link: CVE-2024-5206
Vulnrichment
Updated: 2024-08-01T21:03:11.034Z
NVD
Status : Modified
Published: 2024-06-06T19:16:06.363
Modified: 2024-11-21T09:47:11.143
Link: CVE-2024-5206
Redhat