CVE-2026-81722 — nltk
Fix: nltk/nltk@7808692CVE-2026-81722 is a CWE-407 vulnerability in nltk. A fix is available for nltk — see the affected versions and patch details below.
nltk PorterStemmer before 3.10.3 Quadratic-time DoS
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
Exploitation and automatability from CISA’s SSVC triage for CVE-2026-81722.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
Real-World Exposure
nltkReal-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
nltk.stem.PorterStemmer.stem() -- a ubiquitous public API applied to arbitrary, often untrusted, tokens -- runs in O(n^2) time on a token containing a long run of the letter 'y', letting a single ~20-50 KB token pin a CPU core (CWE-407).
Root cause
_is_consonant(word, i) was made iterative (commit for #3633, GHSA/CWE-674) to fix an earlier unbounded-recursion RecursionError on 'y'*10000. The iterative form walks backward over the whole run of 'y's on every call:
while i > 0 and word[i] == 'y':
negate = not negate
i -= 1
_measure() then calls _is_consonant(stem, i) once for every position i of the stem. For a run of n 'y's that is sum_{i} O(i) = O(n^2). The recursion fix therefore traded a CWE-674 RecursionError for a CWE-407 quadratic-time DoS.
Proof of concept
Measured (Python 3.13): stem('y'*5000 + 'ness') = 2.6s, stem('y'*10000 + 'ness') = 11.3s (2x input -> ~4.3x time = quadratic), stem('y'*20000 + 'ness') > 20s. A pure run of 'y' with no matching suffix is fast because the stemmer rules that call _measure do not fire; a real suffix such as 'ness' triggers _measure on the long stem.
from nltk.stem import PorterStemmer
PorterStemmer().stem('y' * 20000 + 'ness') # >20s of CPU
Impact
Stemming is routinely applied to untrusted text (search, indexing, NLP pipelines). A single unbroken ~20-50 KB token of 'y' characters (no whitespace, so it survives tokenization) causes multi-second-to-minutes CPU consumption per request. No confidentiality/integrity impact; single-process availability only.
Fix direction
Classify each character's consonant/vowel status in a single left-to-right O(n) pass (memoise the 'y' run parity) instead of re-walking the run on every _is_consonant call, so _measure and stemming are linear. This is a sibling of the corpus-reader quadratic advisories GHSA-vp2x-qp44-57v7 and GHSA-8mpw-7fpc-4gqj (CWE-407).
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | nltk | all versions | 3.10.3pip install --upgrade 'nltk==3.10.3' |
Affected Products
nltknltkDetection & mitigation playbook
Open-source dependencyDetect
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.
Fix
Update nltk to 3.10.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-81722 is resolved across your whole dependency graph.
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.
This is denial of service vulnerability in the `nltk PorterStemmer` component, which is utilized across various Red Hat products. Processing a specially crafted, untrusted token can lead to excessive CPU consumption due to inefficient algorithmic complexity, potentially causing a denial of service for applications…
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.Source: Red Hat security advisory for CVE-2026-81722 (CC BY 4.0)
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat OpenShift AI 3.3 | rhoai/odh-llama-stack-core-rhel9:1789121286 | RHSA-2026:73987 |
| Red Hat OpenShift AI 3.5 | rhoai/odh-ta-lmes-job-rhel9:1788935863 | RHSA-2026:69539 |
Frequently Asked Questions
Is CVE-2026-81722 in your dependencies?
Find it across PyPI, including transitive dependencies.