https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Sat, 03 Oct 2026 23:13:15 +0000 https://cve.radiocsirt.org/vuln/certfr-2024-avi-0579 certfr-2024-avi-0579 https://cve.radiocsirt.org/vuln/certfr-2024-avi-0579 https://cve.radiocsirt.org/vuln/euvd-2026-2899 EUVD-2026-2899 https://cve.radiocsirt.org/vuln/euvd-2026-2899 https://cve.radiocsirt.org/vuln/fkie_cve-2024-5206 <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> https://cve.radiocsirt.org/vuln/fkie_cve-2024-5206 https://cve.radiocsirt.org/vuln/ghsa-jw8x-6495-233v <p><strong>Affected:</strong> PyPI: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> <p><strong>Affected:</strong> PyPI: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> https://cve.radiocsirt.org/vuln/ghsa-jw8x-6495-233v https://cve.radiocsirt.org/vuln/oesa-2024-1745 <p><strong>Affected:</strong> openEuler:20.03-LTS-SP4: python-scikit-learn, openEuler:22.03-LTS-SP1: python-scikit-learn, openEuler:22.03-LTS-SP3: python-scikit-learn, openEuler:24.03-LTS: python-scikit-learn</p> <p>A Python module for machine learning built on top of SciPy Security Fix(es): A sensitive data leakage vulnerability was identified in scikit-learn&amp;apos;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.(CVE-2024-5206)</p> <p><strong>Affected:</strong> openEuler:20.03-LTS-SP4: python-scikit-learn, openEuler:22.03-LTS-SP1: python-scikit-learn, openEuler:22.03-LTS-SP3: python-scikit-learn, openEuler:24.03-LTS: python-scikit-learn</p> <p>A Python module for machine learning built on top of SciPy Security Fix(es): A sensitive data leakage vulnerability was identified in scikit-learn&amp;apos;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.(CVE-2024-5206)</p> https://cve.radiocsirt.org/vuln/oesa-2024-1745 https://cve.radiocsirt.org/vuln/opensuse-su-2024:14043-1 <p>python310-scikit-learn-1.5.0-1.1 on GA media</p> <p>python310-scikit-learn-1.5.0-1.1 on GA media</p> https://cve.radiocsirt.org/vuln/opensuse-su-2024:14043-1 https://cve.radiocsirt.org/vuln/pysec-2024-110 <p><strong>Affected:</strong> PyPI: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> <p><strong>Affected:</strong> PyPI: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> https://cve.radiocsirt.org/vuln/pysec-2024-110 https://cve.radiocsirt.org/vuln/suse-su-2024:2029-1 <p>Security update for python-scikit-learn</p> <p>Security update for python-scikit-learn</p> https://cve.radiocsirt.org/vuln/suse-su-2024:2029-1 https://cve.radiocsirt.org/vuln/ubuntu-cve-2024-5206 <p><strong>Affected:</strong> Ubuntu:14.04:LTS: scikit-learn, Ubuntu:16.04:LTS: scikit-learn, Ubuntu:18.04:LTS: scikit-learn, Ubuntu:20.04:LTS: scikit-learn, Ubuntu:22.04:LTS: scikit-learn, Ubuntu:24.04:LTS: scikit-learn, Ubuntu:25.10: scikit-learn, Ubuntu:26.04:LTS: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> <p><strong>Affected:</strong> Ubuntu:14.04:LTS: scikit-learn, Ubuntu:16.04:LTS: scikit-learn, Ubuntu:18.04:LTS: scikit-learn, Ubuntu:20.04:LTS: scikit-learn, Ubuntu:22.04:LTS: scikit-learn, Ubuntu:24.04:LTS: scikit-learn, Ubuntu:25.10: scikit-learn, Ubuntu:26.04:LTS: scikit-learn</p> <p>A sensitive data leakage vulnerability was identified in scikit-learn&#39;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.</p> https://cve.radiocsirt.org/vuln/ubuntu-cve-2024-5206 https://cve.radiocsirt.org/vuln/wid-sec-w-2024-1802 <p>Ein entfernter Angreifer kann mehrere Schwachstellen in IBM Business Automation Workflow ausnutzen, um Informationen offenzulegen oder beliebigen Code auszuführen.</p> <p>Ein entfernter Angreifer kann mehrere Schwachstellen in IBM Business Automation Workflow ausnutzen, um Informationen offenzulegen oder beliebigen Code auszuführen.</p> https://cve.radiocsirt.org/vuln/wid-sec-w-2024-1802