CVE-2026-81724VulnerabilityPublished 2 Sep 2026Updated 29 Oct 2026

nltk.featstruct.FeatStructReader causes unhandled RecursionError (DoS) · NLTK: Uncontrolled recursion

Affects acronymSource GCVE Database

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Not known to be exploited · CVSS 5.3 Medium : upgrade to 2.0.0_5 when convenient.

Data as of 30 Oct 2026, 07:30 UTC

CVSS 3.1 base score

5.3Medium

How severe the flaw is on the 0–10 CVSS scale.

Patch: Available – fixed in 2.0.0_5

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

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 2 Sep 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade acronym to 2.0.0_5.

Affected software

Product	Affected	Fixed in
Homebrewacronym`pkg:brew/acronym`Other threats	Affected >=2.0.0 <2.0.0_5	Fixed in 2.0.0_5

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

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`](nltk/featstruct.py#L2184)) calls `read_partial()` → `_read_partial()` ([`featstruct.py:2250`](nltk/featstruct.py#L2250)). 2. `_read_partial()` dispatches to `_read_partial_featdict()`, which calls `_read_value()` ([`featstruct.py:2436`](nltk/featstruct.py#L2436)) for each feature's value. 3. `_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)). 4. 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)): ```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: ```python #: 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 .`): ```python 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): ```bash python3 -c " from nltk.featstruct import FeatStruct FeatStruct('[a=' * 200 + '1' + ']' * 20

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