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githubGitHub Advisory DatabaseGHSA-JW8X-6495-233V
HistoryJun 06, 2024 - 9:30 p.m.

scikit-learn sensitive data leakage vulnerability

2024-06-0621:30:37
CWE-921
GitHub Advisory Database
github.com
17
scikit-learn
tfidfvectorizer
vulnerability
sensitive data
leakage
versions
fix
storage
tokens
stop_words_
attribute

4.7 Medium

CVSS3

Attack Vector

LOCAL

Attack Complexity

HIGH

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

NONE

Availability Impact

NONE

CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N

6.5 Medium

AI Score

Confidence

Low

0.0004 Low

EPSS

Percentile

9.1%

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.

Affected configurations

Vulners
Node
scikitlearnRange<1.5.0
CPENameOperatorVersion
scikit-learnlt1.5.0

4.7 Medium

CVSS3

Attack Vector

LOCAL

Attack Complexity

HIGH

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

NONE

Availability Impact

NONE

CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N

6.5 Medium

AI Score

Confidence

Low

0.0004 Low

EPSS

Percentile

9.1%