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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-2021-43854 - High Severity Vulnerability
Vulnerable Library - nltk-3.4.5.zip
Natural Language Toolkit
Library home page: https://files.pythonhosted.org/packages/f6/1d/d925cfb4f324ede997f6d47bea4d9babba51b49e87a767c170b77005889d/nltk-3.4.5.zip
Path to dependency file: /requirements.txt
Path to vulnerable library: /requirements.txt,/datastore
Dependency Hierarchy:
Found in HEAD commit: a835daa282bf10ee52224e097ff04df34ab7852d
Found in base branch: develop
Vulnerability Details
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.
Publish Date: 2021-12-23
URL: CVE-2021-43854
CVSS 3 Score Details (7.5)
Base Score Metrics:
Suggested Fix
Type: Upgrade version
Origin: https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-43854
Release Date: 2021-12-23
Fix Resolution: 3.6.6
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