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GHSA-vp2x-qp44-57v7 CVE-2026-81723 PYSEC-2026-3871

NLTK: Quadratic CPU Exhaustion in `XMLCorpusView._read_xml_fragment()`

Low PyPI
Severity
0.0 / 10
Low · CVSS 4.0
Exploit chance (EPSS)
0.28%
Chance of exploitation in the next 30 days. Higher than 20.60% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-400 Uncontrolled Resource Consumption
CWE-407 Inefficient Algorithmic Complexity
Fix
3.10.3
Upgrade nltk to this version or later

Description

Summary

XMLCorpusView._read_xml_fragment() reads a corpus file in 1 KiB blocks, appending each block to a growing fragment string, then calls _VALID_XML_RE.match(fragment) on the full accumulated buffer every iteration. Because each iteration rescans the entire accumulated fragment, the total amount of work grows quadratically with input size.

Commit c9c332284 (CWE-1333) made each match() call linear. The quadratic behavior is separate: the loop calls match() once per 1 KiB block, each time on a longer buffer.

On the test system, an 8 MiB malformed XML file consumed approximately 48 CPU-seconds through the public BNCCorpusReader.words() API with no source modification. Absolute timings vary by hardware. _read_xml_fragment() imposes no limit on fragment size or iteration count.

Details

File: nltk/corpus/reader/xmldocs.py
Function: XMLCorpusView._read_xml_fragment(), lines 261–308

The relevant loop:

fragment = ""
while True:
    fragment += stream.read(self._BLOCK_SIZE)      # grows by 1 KiB per iteration
    if self._VALID_XML_RE.match(fragment):         # rescans full buffer each time
        return fragment
    ...
    last_open_bracket = fragment.rfind("<")
    if last_open_bracket > 0:                      # False for single-'<' payload
        if self._VALID_XML_RE.match(fragment[:last_open_bracket]):
            return ...
    # loop continues

For a payload of b'<' + b'a' * (N-1):

  • For this malformed input, _VALID_XML_RE.match(fragment) does not succeed because the unterminated tag prevents the expression from matching before EOF.
  • fragment.rfind("<") returns 0; the guard last_open_bracket > 0 is False, so the backtrack branch is never taken.
  • The only exit is EOF, after all N bytes are consumed.

Affected readers -> readers that rely on XMLCorpusView, including BNCCorpusReader, NPSChatCorpusReader, SemcorCorpusReader, MTECorpusReader, NKJPCorpusReader, FrameNetCorpusReader, VerbNetCorpusReader, and direct XMLCorpusView instantiation. XMLCorpusReader.xml() is not affected -> it calls defusedxml.safe_parse().

PoC

Requires only pip install nltk. No corpus data needed.

from pathlib import Path
from tempfile import TemporaryDirectory
from time import perf_counter
from nltk.corpus.reader.bnc import BNCCorpusReader

SIZES_KIB = (256, 512, 1024, 2048, 4096, 8192)
results = []
with TemporaryDirectory() as directory:
    root = Path(directory)
    malformed = root / "unterminated.xml"
    for kib in SIZES_KIB:
        malformed.write_bytes(b"<" + b"a" * (kib * 1024 - 1))
        t = perf_counter()
        try:
            list(BNCCorpusReader(str(root), [malformed.name]).words())
        except ValueError as e:
            assert "tag not closed" in str(e)
        results.append(perf_counter() - t)

print("KiB      seconds   growth")
for i, (kib, elapsed) in enumerate(zip(SIZES_KIB, results)):
    ratio = "-" if i == 0 else f"{elapsed / results[i-1]:.2f}x"
    print(f"{kib:5d}  {elapsed:9.3f}  {ratio}")

Runtime should increase by approximately fourfold for each doubling of input size, although absolute timings vary by hardware.

During verification, _VALID_XML_RE.match() was instrumented to record the size of each input. For a 256 KiB malformed file it was invoked 257 times on monotonically increasing buffers (1024, 2048, …, 262144 bytes), with the final call occurring after EOF. This confirms that every iteration rescans the accumulated fragment.

Impact

Applications that process attacker-controlled XML corpus files through an affected reader are vulnerable. The attacker needs only write access to a path the reader will open. No NLTK credentials or special privileges required. Offline tools reading only trusted local corpora are not at risk.

Affected versions: Verified in NLTK 3.9.4, 3.10.0, and the current develop branch. Historical inspection indicates the same loop structure has existed since the introduction of XMLCorpusView (2007), but only the listed versions were experimentally verified. No patch exists in any published release.

This issue results in CPU exhaustion and may allow denial of service in applications that process attacker-controlled XML corpus files.

Suggested Fix

Avoid rescanning the accumulated fragment from the beginning after each 1 KiB read. Incremental parsing, bounded fragment accumulation, or another streaming approach would eliminate the quadratic behavior while preserving existing semantics.

A regression test should verify that BNCCorpusReader.words() raises ValueError within a fixed timeout (e.g. 5 seconds) against a 2 MiB malformed input. The existing test_xmldocs_security.py covers only the prior ReDoS payloads and does not exercise this path.

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:H/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

Attack vector
Network
Attack complexity
High
Attack requirements
Present
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 3.7

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

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

Weakness

CWE-400: Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource.

How to prevent it
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Implementation: Ensure that all failures in resource allocation place the system into a safe posture.

CWE-407: Inefficient Algorithmic Complexity

An algorithm in a product has an inefficient worst-case computational complexity that may be detrimental to system performance and can be triggered by an attacker, typically using crafted manipulations that ensure that the worst case is being reached.

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-cw6x-m8jw-qmrh
NLTK: Uncontrolled recursion in nltk.featstruct.FeatStructReader causes unhandled RecursionError (DoS) via deeply nested feature-structure input
Medium 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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