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Количество 6

Количество 6

ubuntu логотип

CVE-2024-5206

около 2 лет назад

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.

CVSS3: 4.7
EPSS: Низкий
redhat логотип

CVE-2024-5206

около 2 лет назад

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.

CVSS3: 5.3
EPSS: Низкий
nvd логотип

CVE-2024-5206

около 2 лет назад

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.

CVSS3: 4.7
EPSS: Низкий
debian логотип

CVE-2024-5206

около 2 лет назад

A sensitive data leakage vulnerability was identified in scikit-learn' ...

CVSS3: 4.7
EPSS: Низкий
suse-cvrf логотип

SUSE-SU-2024:2029-1

около 2 лет назад

Security update for python-scikit-learn

EPSS: Низкий
github логотип

GHSA-jw8x-6495-233v

около 2 лет назад

scikit-learn sensitive data leakage vulnerability

CVSS3: 5.3
EPSS: Низкий

Уязвимостей на страницу

Уязвимость
CVSS
EPSS
Опубликовано
ubuntu логотип
CVE-2024-5206

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.

CVSS3: 4.7
0%
Низкий
около 2 лет назад
redhat логотип
CVE-2024-5206

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.

CVSS3: 5.3
0%
Низкий
около 2 лет назад
nvd логотип
CVE-2024-5206

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.

CVSS3: 4.7
0%
Низкий
около 2 лет назад
debian логотип
CVE-2024-5206

A sensitive data leakage vulnerability was identified in scikit-learn' ...

CVSS3: 4.7
0%
Низкий
около 2 лет назад
suse-cvrf логотип
SUSE-SU-2024:2029-1

Security update for python-scikit-learn

0%
Низкий
около 2 лет назад
github логотип
GHSA-jw8x-6495-233v

scikit-learn sensitive data leakage vulnerability

CVSS3: 5.3
0%
Низкий
около 2 лет назад

Уязвимостей на страницу