Inefficient Algorithmic Complexity Affecting nltk package, versions [,3.10.3)
Threat Intelligence
Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
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.
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Test your applications- Snyk IDSNYK-PYTHON-NLTK-19513454
- published3 Sept 2026
- disclosed27 Aug 2026
- creditUnknown
Introduced: 27 Aug 2026
NewCVE-2026-81725 (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 in the read_block method of TEICorpusView (nltk/corpus/reader/pl196x.py), whose lazy .*? whole-block regexes rescan the text from each opening-tag position. An attacker can force quadratic CPU growth and stall the parser thread by supplying a PL196X or TEI-like corpus file with many unmatched opening tags, so each regex attempt scans to the block end, fails, and restarts from the next tag. This requires the application to parse an attacker-influenced corpus file through the Pl196xCorpusReader public APIs such as words() or tagged_words().