CVE-2021-43854: Inefficient Regular Expression Complexity in nltk

Published Dec 23, 2021
·
Updated

Impact The vulnerability is present in PunktSentenceTokenizer, senttokenize and wordtokenize. Any users of this class, or these two functions, are vulnerable to a Regular Expression Denial of Service (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. The effect of this vulnerability is noticeable with the following example: python from nltk.tokenize import wordtokenize

n = 8 for length in [10i for i in range(2, n)]: # Prepare a malicious input text = "a" length startt = time.time() # Call wordtokenize and naively measure the execution time wordtokenize(text) print(f"A length of {length:<{n}} takes {time.time() - startt:.4f}s") Which gave the following output during testing: python A length of 100 takes 0.0060s A length of 1000 takes 0.0060s A length of 10000 takes 0.6320s A length of 100000 takes 56.3322s ... I canceled the execution of the program after running it for several hours.

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, or applying the workaround described below.

Patches The problem has been patched in NLTK 3.6.6. After the fix, running the above program gives the following result: python A length of 100 takes 0.0070s A length of 1000 takes 0.0010s A length of 10000 takes 0.0060s A length of 100000 takes 0.0400s A length of 1000000 takes 0.3520s A length of 10000000 takes 3.4641s This output shows a linear relationship in execution time versus input length, which is desirable for regular expressions. We recommend updating to NLTK 3.6.6+ if possible.

Workarounds The execution time of the vulnerable functions is exponential to the length of a malicious input. With other words, 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.

References The issue showcasing the vulnerability: https://github.com/nltk/nltk/issues/2866 The pull request containing considerably more information on the vulnerability, and the fix: https://github.com/nltk/nltk/pull/2869 The commit containing the fix: 1405aad979c6b8080dbbc8e0858f89b2e3690341 Information on CWE-1333: Inefficient Regular Expression Complexity: https://cwe.mitre.org/data/definitions/1333.html

For more information If you have any questions or comments about this advisory: Open an issue in github.com/nltk/nltk Email us at nltk.team@gmail.com

Other sources

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, senttokenize and wordtokenize. 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.

MITRE

Affected Software

3 affected componentsFixes available
pip/nltk<3.6.6
3.6.6
nltk nltk<3.6.5
debian/nltk<=3.5-1
3.8-13.9.1-2

Event History

Dec 23, 2021
CVE Published
via MITRE·05:55 PM
Data Sourced
via MITRE·05:55 PM
DescriptionSeverityWeakness
Jan 6, 2022
Advisory Published
via GitHub·05:38 PM
Mar 24, 2025
Data Sourced
via Launchpad·05:33 AM
Description
Mar 28, 2025
Data Sourced
via Ubuntu·05:33 AM
RemedyDescriptionSeverityAffected Software

Frequently Asked Questions

1

What is NLTK (Natural Language Toolkit)?

NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing.

2

What is the vulnerability ID of NLTK?

The vulnerability ID of NLTK is CVE-2021-43854.

3

What is the severity of CVE-2021-43854?

The severity of CVE-2021-43854 is high with a CVSS score of 7.5.

4

How does CVE-2021-43854 affect NLTK?

CVE-2021-43854 affects NLTK versions prior to 3.6.5 and exposes them to regular expression denial of service (ReDoS) attacks.

5

How can I fix CVE-2021-43854?

To fix CVE-2021-43854, it is recommended to update NLTK to version 3.6.5 or higher.

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