Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
Low
Attack Vector
Local
0

CVE-2024-5206

Disclosure Date: June 06, 2024
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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.

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CVSS V3 Severity and Metrics
Base Score:
4.7 Medium
Impact Score:
3.6
Exploitability Score:
1
Vector:
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N
Attack Vector (AV):
Local
Attack Complexity (AC):
High
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
High
Integrity (I):
None
Availability (A):
None

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