CVE-2026-81724

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.