Vulnerability-Lookup

GHSA-CW6X-M8JW-QMRH

Vulnerability from github – Published: 2026-09-02 14:33 – Updated: 2026-09-02 14:33

Summary

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

Details

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):

FeatStructReader.fromstring() (featstruct.py:2184) calls read_partial() → _read_partial() (featstruct.py:2250).
_read_partial() dispatches to _read_partial_featdict(), which calls _read_value() (featstruct.py:2436) for each feature's value.
_read_value() calls read_value() (featstruct.py:2442), which matches the value against VALUE_HANDLERS (featstruct.py:2478).
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): python 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.

Severity

5.3 (Medium)


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

6.9 (Medium)


                  
                    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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.10.2"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "nltk"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.10.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-81724"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-674"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-09-02T14:33:22Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "### Summary\n\n`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\u0027s recursion limit and raises an **unhandled `RecursionError`** instead of the library\u0027s 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.\n\nThis appears to be the same bug class as two issues already fixed elsewhere in the codebase \u2014 `nltk/jsontags.py` (`JSONTaggedDecoder.decode_obj`, guarded by `MAX_DECODE_DEPTH = 200`) and `nltk/sem/logic.py` (`LogicParser`, guarded by `MAX_PARSE_DEPTH = 200`) \u2014 but `nltk/featstruct.py` does not have an equivalent guard.\n\n### Details\n\nThe recursive call chain (current `develop` branch, `nltk/featstruct.py`):\n\n1. `FeatStructReader.fromstring()` ([`featstruct.py:2184`](nltk/featstruct.py#L2184)) calls `read_partial()` \u2192 `_read_partial()` ([`featstruct.py:2250`](nltk/featstruct.py#L2250)).\n2. `_read_partial()` dispatches to `_read_partial_featdict()`, which calls `_read_value()` ([`featstruct.py:2436`](nltk/featstruct.py#L2436)) for each feature\u0027s value.\n3. `_read_value()` calls `read_value()` ([`featstruct.py:2442`](nltk/featstruct.py#L2442)), which matches the value against `VALUE_HANDLERS` ([`featstruct.py:2478`](nltk/featstruct.py#L2478)).\n4. If the value itself starts with `[` (a nested feature structure), the matched handler is `read_fstruct_value` ([`featstruct.py:2479`](nltk/featstruct.py#L2479), defined at [`featstruct.py:2495`](nltk/featstruct.py#L2495)):\n   ```python\n   def read_fstruct_value(self, s, position, reentrances, match):\n       return self.read_partial(s, position, reentrances)\n   ```\n   This calls `read_partial()` again, which re-enters `_read_partial()` \u2014 the same function from step 1.\n\nThis closes a recursive cycle (`_read_partial \u2192 _read_value \u2192 read_value \u2192 read_fstruct_value \u2192 read_partial \u2192 _read_partial \u2192 ...`) 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\u0027s own recursion-limit protection fires and raises `RecursionError`, which is not a subclass of `ValueError` (the exception type this parser\u0027s own `_error()` helper raises for normal, well-formed parse errors) and therefore propagates uncaught through this API.\n\nFor comparison, `nltk/sem/logic.py`\u0027s `LogicParser` was hardened against exactly this class of issue:\n```python\n#: Maximum expression-nesting depth the recursive-descent parser will\n#: descend to. Deeply nested input would otherwise recurse until Python\n#: raises an uncaught RecursionError and crashes the caller\n#: (uncontrolled recursion, CWE-674); past this depth a normal\n#: LogicalExpressionException is raised instead. Configurable.\nMAX_PARSE_DEPTH = 200\n```\n(`nltk/sem/logic.py:102-107`), and `nltk/jsontags.py`\u0027s `JSONTaggedDecoder` similarly has `MAX_DECODE_DEPTH = 200` with an explicit depth check. `nltk/featstruct.py` has no analogous protection.\n\n`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.\n\n### PoC\n\nVerified against the current `develop` branch in a clean virtualenv (Python 3.12, NLTK installed from this checkout via `pip install -e .`):\n\n```python\nfrom nltk.featstruct import FeatStruct\n\ndepth = 167\npayload = \"[a=\" * depth + \"1\" + \"]\" * depth   # 669 bytes\nFeatStruct(payload)\n```\n\nResult:\n```\nTraceback (most recent call last):\n  ...\n  File \".../nltk/featstruct.py\", line 2310, in _read_partial_featdict\n    value, position = self._read_value(name, s, position, reentrances)\n  File \".../nltk/featstruct.py\", line 2440, in _read_value\n    return self.read_value(s, position, reentrances)\n  File \".../nltk/featstruct.py\", line 2446, in read_value\n    return handler_func(s, position, reentrances, match)\n  [... repeats ~167 times ...]\nRecursionError: maximum recursion depth exceeded\n```\n\n- Crash threshold: nesting depth 167 (binary-searched between 50 and 200).\n- Payload size: 669 bytes \u2014 fits trivially in a single HTTP request body/query parameter.\n- Time to crash: \u003c2ms \u2014 no resource exhaustion is needed, only recursion depth.\n\nMinimal reproduction (no server required):\n```bash\npython3 -c \"\nfrom nltk.featstruct import FeatStruct\nFeatStruct(\u0027[a=\u0027 * 200 + \u00271\u0027 + \u0027]\u0027 * 200)\n\"\n```\n\nIllustrative server-side context (not part of NLTK itself, but representative of how the bug becomes reachable):\n```python\nfrom flask import Flask, request\nfrom nltk.featstruct import FeatStruct\n\napp = Flask(__name__)\n\n@app.route(\"/parse\", methods=[\"POST\"])\ndef parse_grammar():\n    return {\"result\": str(FeatStruct(request.json[\"grammar\"]))}\n```\nA POST of `{\"grammar\": \"[a=\" * 200 + \"1\" + \"]\" * 200}` to this endpoint raises the uncaught `RecursionError` inside the request handler.\n\n### Impact\n\n**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 \u2014 Python\u0027s own recursion-limit safety net converts what would be a C-level stack overflow into a catchable (but here, uncaught) `RecursionError`.\n\n**Who is affected:** Any application that passes externally-supplied text into `nltk.featstruct.FeatStruct()` or `nltk.grammar.FeatureGrammar.fromstring()` \u2014 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\u0027s user base than, e.g., tokenization or POS tagging, since feature-structure/unification-grammar parsing is a more specialized part of the library.\n\n**Practical severity depends on deployment:**\n- 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.\n- 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.\n\n**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\u0027s normal `ValueError`-based parse error once the limit is exceeded instead of letting `RecursionError` propagate.",
  "id": "GHSA-cw6x-m8jw-qmrh",
  "modified": "2026-09-02T14:33:22Z",
  "published": "2026-09-02T14:33:22Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/nltk/nltk/security/advisories/GHSA-cw6x-m8jw-qmrh"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-81724"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nltk/nltk/commit/43c7b78cc8ea37e5cd3a129e27e32c415ea21cf1"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/nltk/nltk"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nltk/nltk/releases/tag/v3.10.3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/nltk/PYSEC-2026-3739.yaml"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/nltk-before-3.10.3-denial-of-service-via-uncontrolled-recursion"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "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",
      "type": "CVSS_V4"
    }
  ],
  "summary": "NLTK: Uncontrolled recursion in nltk.featstruct.FeatStructReader causes unhandled RecursionError (DoS) via deeply nested feature-structure input"
}

CVE-2026-81724 (GCVE-0-2026-81724)

Vulnerability from cvelistv5 – Published: 2026-08-27 14:51 – Updated: 2026-08-27 18:29

Title

NLTK before 3.10.3 Denial of Service via Uncontrolled Recursion

Summary

NLTK before 3.10.3 contains an uncontrolled recursion vulnerability in nltk.featstruct.FeatStructReader that allows unauthenticated attackers to cause a denial of service by supplying deeply nested feature-structure input. Attackers can craft trivial payloads with nested brackets that exceed Python's recursion limit and raise an unhandled RecursionError, crashing applications that parse user-supplied feature structures or feature grammars.

Severity

6.9 (Medium)


                        
                          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

5.3 (Medium)


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

SSVC

Exploitation: poc Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-08-27 18:28 UTC

CWE

CWE-674 - Uncontrolled Recursion

Assigner

VulnCheck mitre root

References

2 references

URL	Tags
https://github.com/nltk/nltk/security/advisories/…	vendor-advisory
https://www.vulncheck.com/advisories/nltk-before-…	third-party-advisory

Impacted products

1 product

Vendor	Product	Version
nltk	nltk	Affected: 0 , < 3.10.3 (semver) Unaffected: 3.10.3 (semver) cpe:2.3:a:nltk:nltk::::::::

Date Public

2026-08-12 00:00

Credits

JoshgunAbdullayev

Show details on NVD website

JSON

To clipboard

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PYSEC-2026-3739

Vulnerability from pysec - Published: 2026-08-27 17:21 - Updated: 2026-09-01 08:54

Details

Severity

6.9 (Medium)


                  
                    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

Impacted products

Name	purl
nltk	pkg:pypi/nltk

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "nltk",
        "purl": "pkg:pypi/nltk"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.10.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.8",
        "0.9",
        "0.9.3",
        "0.9.4",
        "0.9.5",
        "0.9.6",
        "0.9.7",
        "0.9.8",
        "0.9.9",
        "2.0.1",
        "2.0.1rc1",
        "2.0.1rc2-git",
        "2.0.1rc3",
        "2.0.1rc4",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.0.5",
        "2.0b4",
        "2.0b5",
        "2.0b6",
        "2.0b7",
        "2.0b8",
        "2.0b9",
        "3.0.0",
        "3.0.0b1",
        "3.0.0b2",
        "3.0.1",
        "3.0.2",
        "3.0.3",
        "3.0.4",
        "3.0.5",
        "3.1",
        "3.10.0",
        "3.10.1",
        "3.10.2",
        "3.2",
        "3.2.1",
        "3.2.2",
        "3.2.3",
        "3.2.4",
        "3.2.5",
        "3.3",
        "3.4",
        "3.4.1",
        "3.4.2",
        "3.4.3",
        "3.4.4",
        "3.4.5",
        "3.5",
        "3.5b1",
        "3.6",
        "3.6.1",
        "3.6.2",
        "3.6.3",
        "3.6.4",
        "3.6.5",
        "3.6.6",
        "3.6.7",
        "3.7",
        "3.8",
        "3.8.1",
        "3.9",
        "3.9.1",
        "3.9.2",
        "3.9.3",
        "3.9.4",
        "3.9b1"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-81724",
    "GHSA-cw6x-m8jw-qmrh"
  ],
  "details": "NLTK before 3.10.3 contains an uncontrolled recursion vulnerability in nltk.featstruct.FeatStructReader that allows unauthenticated attackers to cause a denial of service by supplying deeply nested feature-structure input. Attackers can craft trivial payloads with nested brackets that exceed Python\u0027s recursion limit and raise an unhandled RecursionError, crashing applications that parse user-supplied feature structures or feature grammars.",
  "id": "PYSEC-2026-3739",
  "modified": "2026-09-01T08:54:52.383436Z",
  "published": "2026-08-27T17:21:03.100Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://www.vulncheck.com/advisories/nltk-before-3.10.3-denial-of-service-via-uncontrolled-recursion"
    },
    {
      "type": "EVIDENCE",
      "url": "https://github.com/nltk/nltk/security/advisories/GHSA-cw6x-m8jw-qmrh"
    }
  ],
  "severity": [
    {
      "score": "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/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.

Action not permitted

GHSA-CW6X-M8JW-QMRH

Summary

Details

PoC

Impact

CVE-2026-81724 (GCVE-0-2026-81724)

PYSEC-2026-3739

Tags

Sightings

Nomenclature