Bug 2291228 (CVE-2024-5206)

Summary: CVE-2024-5206 scikit-learn: Possible sensitive data leak
Product: [Other] Security Response Reporter: Marco Benatto <mbenatto>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
Status: NEW --- QA Contact:
Severity: medium Docs Contact:
Priority: medium    
Version: unspecifiedCC: adudiak, epacific, jcammara, jhardy, jneedle, jobarker, kshier, mabashia, omaciel, simaishi, smcdonal, stcannon, teagle, yguenane, zsadeh
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A vulnerability was found in the scikit-learn package. Before version 1.4.1, post1 scikit-learn stores all tokens with "stop_words_" attributes. This action may cause scikit-learn to expose sensitive data that will not be used in the model training, possibly leaking passwords and keys.
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Bug Depends On: 2291229, 2291230    
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Description Marco Benatto 2024-06-10 21:06:17 UTC 
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.

https://github.com/scikit-learn/scikit-learn/commit/70ca21f106b603b611da73012c9ade7cd8e438b8
https://huntr.com/bounties/14bc0917-a85b-4106-a170-d09d5191517c
Comment 1 Marco Benatto 2024-06-10 21:08:39 UTC 
Created python-imbalanced-learn tracking bugs for this issue:

Affects: fedora-all [bug 2291229]


Created python-scikit-learn tracking bugs for this issue:

Affects: fedora-all [bug 2291230]