Vulnerability Database

383,211

Total vulnerabilities in the database

CVE-2026-12876 — nltk

Inefficient Algorithmic Complexity

nltk.parse.RecursiveDescentParser (and SteppingRecursiveDescentParser) enumerate parses top-down with no bound on the number of recursive steps. A small, crafted context-free grammar makes a short input consume unbounded CPU (and/or exhaust the Python recursion stack), pinning a process indefinitely — a denial of service.

Proof of concept

Both of the following hang on a 24-token input (killed after 8s; growth is super-linear in input length), on NLTK develop:

from nltk import CFG from nltk.parse import RecursiveDescentParser # (a) left recursion -> unbounded recursion g = CFG.fromstring("S -> S S | 'a'") list(RecursiveDescentParser(g).parse(["a"] * 24)) # hangs # (b) ambiguous grammar -> exponential number of parses g = CFG.fromstring("S -> 'a' S | 'a' S S | 'a'") list(RecursiveDescentParser(g).parse(["a"] * 24)) # hangs

Impact

An application that runs RecursiveDescentParser on a grammar (or an input) drawn from an untrusted source can be driven into an unbounded CPU / stack-exhaustion loop by a tiny payload. No confidentiality or integrity impact; single-process availability only.

Sibling

The RegexpTokenizer ReDoS reported alongside this (CVE-2026-12875) is a different class (caller-supplied regex) and is addressed under GHSA-w3v8-gmh9-3wv7.

No technical information available.

Frequently Asked Questions

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Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.

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