Version 3.9.1

nltk

NLTK Source

Install Instructions

pip install nltk
Current Version Release Date August 18, 2024
Language Python
Package URL (purl) pkg:pip/nltk@3.9.1

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nltk Vulnerabilities

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CVE question mark icon CVSS Score question mark icon CWE(s) question mark icon EPSS Score question mark icon EPSS % question mark icon Impacted Versions
CVE-2019-14751 High 7.5 CWE-22 0.00774 0.81899
  • 3.0.0–3.4.4
  • 2.0.1–2.0b9
  • 0.8–0.9.9
CVE-2021-3828 High 7.5 CWE-697 0.00117 0.46914
  • 3.0.0–3.5b1
  • 2.0.1–2.0b9
  • 0.8–0.9.9
CVE-2021-3842 High 7.5 CWE-1333 0.0015 0.52346
  • 3.0.0–3.5b1
  • 2.0.1–2.0b9
  • 0.8–0.9.9
CVE-2021-43854 High 7.5 CWE-400 0.0037 0.73325
  • 3.0.0–3.5b1
  • 2.0.1–2.0b9
  • 0.8–0.9.9
CVE-2024-39705 High 9.8 CWE-300, CWE-502 0.00045 0.17069
  • 3.0.0–3.9b1
  • 2.0.1–2.0b9
  • 0.8–0.9.9

nltk Vulnerability Remediation Guidance

CVE Description Full list of Impacted Versions Fix
CVE-2024-39705 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. 3.4.2, 3.5b1, 3.4.5, 3.9b1, 3.7, 3.2.5, 3.4, 3.2.3 (Show all) Patch → 3.9
CVE-2021-43854 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. 3.4.2, 3.5b1, 3.4.5, 3.2.5, 3.4, 3.2.3, 3.2.4, 3.2.2 (Show all) Patch → 3.9
CVE-2021-3842 nltk is vulnerable to Inefficient Regular Expression Complexity 3.4.2, 3.5b1, 3.4.5, 3.2.5, 3.4, 3.2.3, 3.2.4, 3.2.2 (Show all) Patch → 3.9
CVE-2021-3828 nltk is vulnerable to Inefficient Regular Expression Complexity 3.4.2, 3.5b1, 3.4.5, 3.2.5, 3.4, 3.2.3, 3.2.4, 3.2.2 (Show all) Patch → 3.9
CVE-2019-14751 NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during extraction. 3.4.2, 3.2.5, 3.4, 3.2.3, 3.2.4, 3.2.2, 3.4.1, 3.2.1 (Show all) Patch → 3.9

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Dependencies

Packages using versions of nltk affected by its vulnerabilities

Dependent Packages
click
joblib
regex>=2021.8.3
tqdm
numpy; extra == "all"
requests; extra == "all"
twython; extra == "all"
python-crfsuite; extra == "all"
pyparsing; extra == "all"
scipy; extra == "all"
matplotlib; extra == "all"
scikit-learn; extra == "all"
requests; extra == "corenlp"
numpy; extra == "machine-learning"
python-crfsuite; extra == "machine-learning"
scikit-learn; extra == "machine-learning"
scipy; extra == "machine-learning"
matplotlib; extra == "plot"
pyparsing; extra == "tgrep"
twython; extra == "twitter"