NLTK: Quadratic CPU exhaustion in TreebankWordTokenizer.span_tokenize via list.pop(0) in quote-restore loop

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS

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

EPSS

• CVE-2026-126300: 0.47% estimated exploitation activity in the next 30 days; percentile 41.45 (FIRST EPSS, 2026-11-14). This is a model estimate, not proof of exploitation or customer exposure.

As published by the source; long descriptions are shortened.

Summary `TreebankWordTokenizer.span_tokenize` in the NLTK tokenizer package contains an unguarded O(n^2) processing loop in its quote-restoration step. When the method is invoked on text containing a long run of double-quote characters (for example `'"' * n`), it performs a `list.pop(0)` operation once per quote token, and because `list.pop(0)` is O(length), the total cost grows with the square of the input length. An attacker who can supply untrusted text to this public span-tokenization API can force a single request to saturate one CPU core for a prolonged period, degrading availability. No authentication, special configuration, or user interaction is required.

Root Cause Inside `span_tokenize`, when the input contains double or repeated quotes, the code builds `matched`, a list with one entry per quote occurrence, and then reconstructs tokens in a comprehension that calls `matched.pop(0)` for each token that is a quote. Removing the first element of a Python list is an…

Published by the source

13 Nov 2026, 21:08 UTC

Last modified by the source

13 Nov 2026, 21:15 UTC

Source last checked

14 Nov 2026, 07:50 UTC

1. Revision 2 · amended · 14 Nov 2026

   Amended from osv record GHSA-ffr9-mgrr-wcvr

2. Revision 1 · created · 13 Nov 2026

   Published from ghsa record GHSA-ffr9-mgrr-wcvr

Preview the exact text before you copy it. Commands are read-only suggestions; review them before running anything.

# Patch Next advisory brief: CVE-2026-126300

Advisory: NLTK: Quadratic CPU exhaustion in TreebankWordTokenizer.span_tokenize via list.pop(0) in quote-restore loop
IDs: CVE-2026-126300, GHSA-ffr9-mgrr-wcvr
Record: https://patchnext.com/advisories/cve-2026-126300 (revision 2, source checked 14 Nov 2026, 07:50 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Medium (CVSS 5.3)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: nltk 3.10.4. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI nltk: affected >= 3.2.5, < 3.10.4; fixed in 3.10.4

## Suggested inspection (read-only)
- `python -m pip show nltk`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on nltk.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://github.com/advisories/GHSA-ffr9-mgrr-wcvr (GitHub-reviewed advisory GHSA-ffr9-mgrr-wcvr lists affected ranges: PyPI nltk >=3.2.5 <=3.10.3)
- Verified: https://osv.dev/vulnerability/GHSA-ffr9-mgrr-wcvr (OSV record GHSA-ffr9-mgrr-wcvr lists affected ranges: PyPI nltk >=3.2.5 <3.10.4 (fixed))

Commands are suggestions: review each one before running it.