CVE-2024-5206
scikit-learn sensitive data leakage vulnerability
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.
How to fix CVE-2024-5206
To remediate CVE-2024-5206, upgrade the affected package to a fixed version below.
- —no fix listed
- —upgrade to 1.5.0 or later
- —upgrade to 70ca21f106b603b611da73012c9ade7cd8e438b8 or later
Is CVE-2024-5206 being exploited?
Low — EPSS is 0.2%, meaning exploitation activity has not been observed at scale.
Affected packages (3)
- from 0
- from 0, < 1.5.0
- from 0, < 70ca21f106b603b611da73012c9ade7cd8e438b8 | from 0, < 1.5.0
CVSS scores
| Source | Version | Severity | Vector |
|---|---|---|---|
| osv | CVSS 3.1 | MEDIUM5.3 | CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N |