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GHSA-f8m6-h2c7-8h9x CVE-2021-43854 PYSEC-2021-859

Inefficient Regular Expression Complexity in nltk (word_tokenize, sent_tokenize)

High PyPI
Severity
0.0 / 10
High · CVSS 4.0
Exploit chance (EPSS)
2.79%
Chance of exploitation in the next 30 days. Higher than 86.42% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-400 Uncontrolled Resource Consumption
Fix
3.6.6
Upgrade nltk to this version or later

Description

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

For more information

If you have any questions or comments about this advisory:

Affected versions

PyPI

PackageVulnerableFixed in
nltk
< 3.6.6
3.6.6
nltk
< 3.6.5
3.6.5

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

nltk PyPI → 3.6.6

pip
pip install --upgrade "nltk>=3.6.6"
poetry
poetry add "nltk>=3.6.6"
uv
uv add "nltk>=3.6.6"

Severity breakdown

CVSS 4.0 0.0

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Attack vector
Network
Attack complexity
Low
Attack requirements
None
Privileges required
None
User interaction
None
Confidentiality (vulnerable system)
None
Integrity (vulnerable system)
None
Availability (vulnerable system)
High
Confidentiality (subsequent systems)
None
Integrity (subsequent systems)
None
Availability (subsequent systems)
None

CVSS 3.1 7.5

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-400: Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource.

How to prevent it
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Implementation: Ensure that all failures in resource allocation place the system into a safe posture.

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-j456-xh4h-cpf2
NLTK: WekaClassifier passes an unvalidated caller-controlled model path to the weka JVM, bypassing nltk.pathsec containment
High Also affects nltk
GHSA-ff5c-cp5c-9wjf
NLTK: Uncontrolled resource consumption in RecursiveDescentParser via ambiguous or left-recursive grammars
Medium Also affects nltk
GHSA-f794-5jv7-7672
NLTK: Downloader.download follows hardlinks and overwrites outside-root files
High Also affects nltk
GHSA-8mgp-746c-j5xp
NLTK: Model-artifact APIs bypass pathsec and touch files outside allowed roots
High Also affects nltk
GHSA-8mpw-7fpc-4gqj
NLTK: Pl196xCorpusReader has quadratic ReDoS on malformed TEI blocks
Low Also affects nltk
GHSA-cw6x-m8jw-qmrh
NLTK: Uncontrolled recursion in nltk.featstruct.FeatStructReader causes unhandled RecursionError (DoS) via deeply nested feature-structure input
Medium Also affects nltk
GHSA-vp2x-qp44-57v7
NLTK: Quadratic CPU Exhaustion in `XMLCorpusView._read_xml_fragment()`
Low Also affects nltk
GHSA-ww6m-cw3f-q94g
NLTK: Quadratic-time DoS in PorterStemmer via long runs of 'y'
High Also affects nltk
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