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.

An improper use of the SD card for sensitive data vulnerability was reported in the Motorola Device Help application that could allow a local attacker to read system logs. 

Storage of Sensitive Data in a Mechanism without Access Control in GitHub repository francoisjacquet/rosariosis prior to 11.0.

Philips Gemini PET/CT family software stores sensitive information in a removable media device that does not have built-in access control.