Affected: nltk

NLTK from 3.2.5 before 3.10.4 contains an algorithmic complexity vulnerability in TreebankWordTokenizer.span_tokenize that allows remote attackers to cause quadratic CPU consumption through repeated list.pop(0) calls. Attackers can submit long runs of double-quote characters to services span-tokenizing untrusted text, exhausting a CPU core and degrading availability.

Affected: PyPI: nltk

## 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 O(len(list)) operation because all remaining elements are shifted. For an all-quote input the tokenizer produces n quote tokens and `matched` has n entries, so `pop(0)` is called n times, each time on a list of shrinking but still linear length, giving cumulative O(n^2) CPU work. The violated invariant is bounded per-input work: there is no length cap on `span_tokenize` or the underlying `tokenize`, so untrusted input length translates into quadratic processing time. The neighboring `align_tokens`…