GHSA-f8m6-h2c7-8h9x

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Source
https://github.com/advisories/GHSA-f8m6-h2c7-8h9x
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/01/GHSA-f8m6-h2c7-8h9x/GHSA-f8m6-h2c7-8h9x.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-f8m6-h2c7-8h9x
Aliases
Published
2022-01-06T17:38:45Z
Modified
2023-11-08T04:07:14.650619Z
Severity
  • 7.5 (High) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H CVSS Calculator
Summary
Inefficient Regular Expression Complexity in nltk (word_tokenize, sent_tokenize)
Details

Impact

The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. 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:

from nltk.tokenize import word_tokenize

n = 8
for length in [10**i for i in range(2, n)]:
    # Prepare a malicious input
    text = "a" * length
    start_t = time.time()
    # Call `word_tokenize` and naively measure the execution time
    word_tokenize(text)
    print(f"A length of {length:<{n}} takes {time.time() - start_t:.4f}s")

Which gave the following output during testing:

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:

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

References

Affected packages

PyPI / nltk

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
3.6.6

Affected versions

2.*

2.0.1rc2-git
2.0b4
2.0b5
2.0b6
2.0b7
2.0b8
2.0b9
2.0.1rc1
2.0.1rc3
2.0.1rc4
2.0.1
2.0.2
2.0.3
2.0.4
2.0.5

0.*

0.8
0.9
0.9.3
0.9.4
0.9.5
0.9.6
0.9.7
0.9.8
0.9.9

3.*

3.0.0b1
3.0.0b2
3.0.0
3.0.1
3.0.2
3.0.3
3.0.4
3.0.5
3.1
3.2
3.2.1
3.2.2
3.2.3
3.2.4
3.2.5
3.3
3.4
3.4.1
3.4.2
3.4.3
3.4.4
3.4.5
3.5b1
3.5
3.6
3.6.1
3.6.2
3.6.3
3.6.4
3.6.5