Path to dependency file: /redline_hackathon_model/requirements.txt
Path to vulnerable library: /teSource-ArchiveExtractor_10185ad7-6719-45f4-abc0-7cff4f731fd5/20190531052439_2943/20190531052421_depth_0/numpy-1.16.2-cp27-cp27mu-manylinux1_x86_64/numpy/ma
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.
CVE-2024-5206 - Medium Severity Vulnerability
A set of python modules for machine learning and data mining
Library home page: https://files.pythonhosted.org/packages/bc/67/370aa248f54769a56216707ad7b9af19745e85a603fafa47bde353f327fb/scikit_learn-0.19.2-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /redline_hackathon_model/requirements.txt
Path to vulnerable library: /teSource-ArchiveExtractor_10185ad7-6719-45f4-abc0-7cff4f731fd5/20190531052439_2943/20190531052421_depth_0/numpy-1.16.2-cp27-cp27mu-manylinux1_x86_64/numpy/ma
Dependency Hierarchy: - :x: **scikit_learn-0.19.2-cp27-cp27mu-manylinux1_x86_64.whl** (Vulnerable Library)
Found in base branch: master
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.
Publish Date: 2024-06-06
URL: CVE-2024-5206
Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: High - Privileges Required: Low - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: High - Integrity Impact: None - Availability Impact: None
For more information on CVSS3 Scores, click here.Type: Upgrade version
Origin: https://www.cve.org/CVERecord?id=CVE-2024-5206
Release Date: 2024-06-06
Fix Resolution: scikit-learn - 1.5.0
Step up your Open Source Security Game with Mend here