Inefficient Algorithmic Complexity Affecting nltk package, versions [,3.10.3)
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
Do your applications use this vulnerable package?
In a few clicks we can analyze your entire application and see what components are vulnerable in your application, and suggest you quick fixes.
Test your applications- Snyk IDSNYK-PYTHON-NLTK-19639019
- published7 Sept 2026
- disclosed27 Aug 2026
- creditUnknown
Introduced: 27 Aug 2026
NewCVE-2026-81722 (opens in a new tab)How to fix?
Upgrade nltk to version 3.10.3 or higher.
Overview
nltk is a Natural Language Toolkit (NLTK) is a Python package for natural language processing.
Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity via the PorterStemmer.stem() path in nltk/stem/porter.py. An attacker can pin a CPU core by supplying a single token with a long run of y characters, especially one that reaches stemming logic such as a y...ness input. The vulnerable code calls _is_consonant(word, i) once per character in _measure() and _contains_vowel(), and _is_consonant() walks backward across the same y run on every call. That makes stemming a long y token consume O(n^2) time, delaying or stalling requests that process untrusted text.