There are 4 open security issues in bullseye.
4 issues left for the package maintainer to handle:
- CVE-2021-3828:
(needs triaging)
nltk is vulnerable to Inefficient Regular Expression Complexity
- CVE-2021-3842:
(needs triaging)
nltk is vulnerable to Inefficient Regular Expression Complexity
- CVE-2021-43854:
(needs triaging)
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, then we would strongly recommend upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions. Our recommendation is to implement such a limit.
- CVE-2024-39705:
(postponed; to be fixed through a stable update)
NLTK through 3.8.1 allows remote code execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.
You can find information about how to handle these issues in the security team's documentation.