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GHSA-cw6x-m8jw-qmrh CVE-2026-81724 PYSEC-2026-3739

NLTK: Uncontrolled recursion in nltk.featstruct.FeatStructReader causes unhandled RecursionError (DoS) via deeply nested feature-structure input

Medium PyPI
Severity
0.0 / 10
Medium · CVSS 4.0
Exploit chance (EPSS)
0.46%
Chance of exploitation in the next 30 days. Higher than 39.59% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-674 Uncontrolled Recursion
Fix
3.10.3
Upgrade nltk to this version or later

Description

Summary

nltk.featstruct.FeatStructReader (used by FeatStruct(str) and by FeatureGrammar.fromstring()) parses feature-structure strings such as [a=1] with a recursive-descent parser that has no nesting-depth limit. A small, trivially-crafted input (~700 bytes) with deeply nested brackets drives the parser past Python's recursion limit and raises an unhandled RecursionError instead of the library's normal, catchable ValueError/LogicalExpressionException. Any application that parses user-supplied feature-structure or feature-grammar text (e.g. NLP teaching tools, grammar "playgrounds", unification-grammar-based NLU pipelines) can be crashed by an unauthenticated input with no special privileges. This is a Denial of Service issue (CWE-674, Uncontrolled Recursion), not a memory-safety or code-execution issue.

This appears to be the same bug class as two issues already fixed elsewhere in the codebase — nltk/jsontags.py (JSONTaggedDecoder.decode_obj, guarded by MAX_DECODE_DEPTH = 200) and nltk/sem/logic.py (LogicParser, guarded by MAX_PARSE_DEPTH = 200) — but nltk/featstruct.py does not have an equivalent guard.

Details

The recursive call chain (current develop branch, nltk/featstruct.py):

  1. FeatStructReader.fromstring() (featstruct.py:2184) calls read_partial() → _read_partial() (featstruct.py:2250).
  2. _read_partial() dispatches to _read_partial_featdict(), which calls _read_value() (featstruct.py:2436) for each feature's value.
  3. _read_value() calls read_value() (featstruct.py:2442), which matches the value against VALUE_HANDLERS (featstruct.py:2478).
  4. If the value itself starts with [ (a nested feature structure), the matched handler is read_fstruct_value (featstruct.py:2479, defined at featstruct.py:2495):
    def read_fstruct_value(self, s, position, reentrances, match):
        return self.read_partial(s, position, reentrances)
    
    This calls read_partial() again, which re-enters _read_partial() — the same function from step 1.

This closes a recursive cycle (_read_partial → _read_value → read_value → read_fstruct_value → read_partial → _read_partial → ...) with no depth counter, no MAX_*_DEPTH constant, and no try/except RecursionError anywhere in the class. Each additional [ in the input adds one more full cycle of Python stack frames. Once the input nests deeply enough, Python's own recursion-limit protection fires and raises RecursionError, which is not a subclass of ValueError (the exception type this parser's own _error() helper raises for normal, well-formed parse errors) and therefore propagates uncaught through this API.

For comparison, nltk/sem/logic.py's LogicParser was hardened against exactly this class of issue:

#: Maximum expression-nesting depth the recursive-descent parser will
#: descend to. Deeply nested input would otherwise recurse until Python
#: raises an uncaught RecursionError and crashes the caller
#: (uncontrolled recursion, CWE-674); past this depth a normal
#: LogicalExpressionException is raised instead. Configurable.
MAX_PARSE_DEPTH = 200

(nltk/sem/logic.py:102-107), and nltk/jsontags.py's JSONTaggedDecoder similarly has MAX_DECODE_DEPTH = 200 with an explicit depth check. nltk/featstruct.py has no analogous protection.

FeatureGrammar.fromstring() (nltk/grammar.py) parses feature structures embedded in FCFG grammar rules via the same FeatStructReader, so the same crash is reachable through grammar-string parsing as well as through FeatStruct() directly.

PoC

Verified against the current develop branch in a clean virtualenv (Python 3.12, NLTK installed from this checkout via pip install -e .):

from nltk.featstruct import FeatStruct

depth = 167
payload = "[a=" * depth + "1" + "]" * depth   # 669 bytes
FeatStruct(payload)

Result:

Traceback (most recent call last):
  ...
  File ".../nltk/featstruct.py", line 2310, in _read_partial_featdict
    value, position = self._read_value(name, s, position, reentrances)
  File ".../nltk/featstruct.py", line 2440, in _read_value
    return self.read_value(s, position, reentrances)
  File ".../nltk/featstruct.py", line 2446, in read_value
    return handler_func(s, position, reentrances, match)
  [... repeats ~167 times ...]
RecursionError: maximum recursion depth exceeded
  • Crash threshold: nesting depth 167 (binary-searched between 50 and 200).
  • Payload size: 669 bytes — fits trivially in a single HTTP request body/query parameter.
  • Time to crash: <2ms — no resource exhaustion is needed, only recursion depth.

Minimal reproduction (no server required):

python3 -c "
from nltk.featstruct import FeatStruct
FeatStruct('[a=' * 200 + '1' + ']' * 200)
"

Illustrative server-side context (not part of NLTK itself, but representative of how the bug becomes reachable):

from flask import Flask, request
from nltk.featstruct import FeatStruct

app = Flask(__name__)

@app.route("/parse", methods=["POST"])
def parse_grammar():
    return {"result": str(FeatStruct(request.json["grammar"]))}

A POST of {"grammar": "[a=" * 200 + "1" + "]" * 200} to this endpoint raises the uncaught RecursionError inside the request handler.

Impact

Vulnerability type: Denial of Service via uncontrolled recursion (CWE-674). This is not a memory-corruption bug and does not lead to code execution or data disclosure — Python's own recursion-limit safety net converts what would be a C-level stack overflow into a catchable (but here, uncaught) RecursionError.

Who is affected: Any application that passes externally-supplied text into nltk.featstruct.FeatStruct() or nltk.grammar.FeatureGrammar.fromstring() — for example, NLP/computational-linguistics teaching tools, unification-grammar demo services, or NLU pipelines that accept user-authored feature grammars. This is a narrower slice of NLTK's user base than, e.g., tokenization or POS tagging, since feature-structure/unification-grammar parsing is a more specialized part of the library.

Practical severity depends on deployment:

  • In typical WSGI-style web frameworks (Flask/Django/FastAPI behind gunicorn/uwsgi), an uncaught exception inside a request handler is caught at the framework/server boundary: the single request fails (HTTP 500), the worker process itself survives, and unaffected requests are unimpacted.
  • In single-threaded or per-task-unprotected contexts (e.g. a queue-consuming worker without per-task exception isolation), the uncaught RecursionError can terminate the entire process; without a process supervisor that auto-restarts it, this is a persistent outage until manually restarted. An attacker who repeats the payload can keep such a worker in a crash loop for as long as the attack continues.

Suggested fix: Add a depth counter and a MAX_PARSE_DEPTH-style constant to FeatStructReader, mirroring the existing fix in nltk/sem/logic.py, and raise the library's normal ValueError-based parse error once the limit is exceeded instead of letting RecursionError propagate.

Affected versions

PyPI

PackageVulnerableFixed in
nltk
< 3.10.3
3.10.3

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

nltk PyPI → 3.10.3

pip
pip install --upgrade "nltk>=3.10.3"
poetry
poetry add "nltk>=3.10.3"
uv
uv add "nltk>=3.10.3"

Severity breakdown

CVSS 4.0 0.0

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

Attack vector
Network
Attack complexity
Low
Attack requirements
None
Privileges required
None
User interaction
None
Confidentiality (vulnerable system)
None
Integrity (vulnerable system)
None
Availability (vulnerable system)
Low
Confidentiality (subsequent systems)
None
Integrity (subsequent systems)
None
Availability (subsequent systems)
None

CVSS 3.1 5.3

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

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low

Weakness

CWE-674: Uncontrolled Recursion

The product does not properly control the amount of recursion that takes place, consuming excessive resources, such as allocated memory or the program stack.

How to prevent it
  • Implementation: Ensure that an end condition will be reached under all logic conditions. The end condition may include checking against the depth of recursion and exiting with an error if the recursion goes too deep. The complexity of the end condition contributes to the effectiveness of this action.
  • Implementation: Increase the stack size.

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-j456-xh4h-cpf2
NLTK: WekaClassifier passes an unvalidated caller-controlled model path to the weka JVM, bypassing nltk.pathsec containment
High Also affects nltk
GHSA-ff5c-cp5c-9wjf
NLTK: Uncontrolled resource consumption in RecursiveDescentParser via ambiguous or left-recursive grammars
Medium Also affects nltk
GHSA-f794-5jv7-7672
NLTK: Downloader.download follows hardlinks and overwrites outside-root files
High Also affects nltk
GHSA-8mgp-746c-j5xp
NLTK: Model-artifact APIs bypass pathsec and touch files outside allowed roots
High Also affects nltk
GHSA-8mpw-7fpc-4gqj
NLTK: Pl196xCorpusReader has quadratic ReDoS on malformed TEI blocks
Low Also affects nltk
GHSA-vp2x-qp44-57v7
NLTK: Quadratic CPU Exhaustion in `XMLCorpusView._read_xml_fragment()`
Low Also affects nltk
GHSA-ww6m-cw3f-q94g
NLTK: Quadratic-time DoS in PorterStemmer via long runs of 'y'
High Also affects nltk
GHSA-w3v8-gmh9-3wv7
NLTK: ReDoS in nltk.tgrep via unvalidated user-supplied regular expressions
Medium Also affects nltk
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