Описание
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.
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.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| Red Hat Ansible Automation Platform 2 | aap-cloud-metrics-collector-container | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-supported-rhel8 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/ee-dellemc-openmanage-rhel8 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/ee-minimal-rhel9 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/ee-supported-rhel9 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/platform-resource-runner-rhel8 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-25/ansible-builder-rhel8 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-25/ansible-dev-tools-rhel8 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-25/ee-cloud-services-rhel9 | Not affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-25/lightspeed-rhel8 | Not affected |
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Дополнительная информация
Статус:
EPSS
5.3 Medium
CVSS3
Связанные уязвимости
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.
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.
A sensitive data leakage vulnerability was identified in scikit-learn' ...
scikit-learn sensitive data leakage vulnerability
EPSS
5.3 Medium
CVSS3