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HIGH severity

CVE-2021-43854 — nltk

HIGHFix: nltk/nltk@1405aad

CVE-2021-43854 is a high-severity (CVSS 7.5) Uncontrolled Resource Consumption vulnerability in nltk. 3 public exploit references exist, so weaponization risk is real. A fix is available for nltk — see the affected versions and patch details below.

Inefficient Regular Expression Complexity in nltk (word_tokenize, sent_tokenize)

Also known asGHSA-f8m6-h2c7-8h9xPYSEC-2021-859
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
3 known
Exploitation data as of Oct 1, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
2.6%probability of exploitation in next 30 days
Lower Risk-0.07%
Lower risk than most CVEs85th percentile — riskier than 85% of all scored CVEsHighest risk
0.29%1.26%2.24%3.22%0.8%0.8%2.7%2.7%2.6%Apr 26Jul 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2021-43854 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 385,738 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

Real-World Exposure

1 pkg affected
🐍nltk

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

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 Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPInltkall versions3.6.6pip install --upgrade 'nltk==3.6.6'

Affected Products

1 product · 1 configurations
Application
nltknltk
< 3.6.5
range
Exploits & PoCs
3

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for nltk, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update nltk to 3.6.6 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-43854 is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Frequently Asked Questions

### Impact The vulnerability is present in [`PunktSentenceTokenizer`](https://www.nltk.org/api/nltk.tokenize.punkt.html#nltk.tokenize.punkt.PunktSentenceTokenizer), [`sent_tokenize`](https://www.nltk.org/api/nltk.tokenize.html#nltk.tokenize.sent_tokenize) and [`word_tokenize`](https://www.nltk.org/api/nltk.tokenize.html#nltk.tokenize.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 amoun
O3 Security · Impact-Aware SCA

Is CVE-2021-43854 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2021-43854: nltk DoS — Fixed in 3.6.6