Insecure Storage of Sensitive Information Affecting kubeflow-katib package, versions <0.16.0-r12


Severity

Recommended
0.0
medium
0
10

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Threat Intelligence

EPSS
0.04% (11th percentile)

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  • Snyk IDSNYK-WOLFILATEST-KUBEFLOWKATIB-7267275
  • published18 Jun 2024
  • disclosed6 Jun 2024

Introduced: 6 Jun 2024

CVE-2024-5206  (opens in a new tab)
CWE-922  (opens in a new tab)

How to fix?

Upgrade Wolfi kubeflow-katib to version 0.16.0-r12 or higher.

NVD Description

Note: Versions mentioned in the description apply only to the upstream kubeflow-katib package and not the kubeflow-katib package as distributed by Wolfi. See How to fix? for Wolfi relevant fixed versions and status.

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.

CVSS Scores

version 3.1