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Fencer Vulns
high 7.5

CVE-2026-76098 json

Mistune has Denial of Service — RecursionError via Excessive Emphasis Markers in Markdown

published 2026-08-24 2 mo ago modified 2026-10-12 27 d ago also GHSA-6m44-fpc8-c3rq , PYSEC-2026-3863 , EUVD-2026-65137

cvss
7.5
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.5%
EPSS 0.5% chance of exploitation in 30 days, percentile 42%
public exploits
0
none known

Summary

Mistune is a Python Markdown parser with renderers and plugins. Versions 3.3.0 through 3.3.2 are vulnerable to DoS through deeply nested tokens. HTML rendering creates deeply nested emphasis tokens from consecutive asterisk characters, and recursive rendering in HTMLRenderer.render_token() can exceed Python's recursion limit and raise RecursionError, allowing crafted Markdown to crash a parsing process. This issue is fixed in version 3.3.3

Patch / fix

  • pypi mistune 3.3.3
  • python-mistune Azure Linux 3.0 3.3.4-1

azure linux advisories AZL-97956

Azure Linux vulnerability data, Copyright (c) Microsoft Corporation, from https://github.com/microsoft/AzureLinuxVulnerabilityData via OSV, under the MIT licence; changed: normalised to fixed package versions per release. MIT

Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-76098 updated cvss 7.5

mistune: Mistune: Denial of Service via excessive emphasis markers in Markdown

  • Red Hat OpenShift AI (RHOAI) rhoai/odh-th06-cpu-torch291-py312-rhel9, rhoai/odh-th06-cuda130-torch291-py312-rhel9
    affected: workaround, no fix available
  • Red Hat OpenShift AI 2.25 rhoai/odh-feature-server-rhel9 1792148523, rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9 1791393968, rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 1791902759, rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 1791867137, rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9 1791870787, rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9 1791867222, +12 more
    fixed: vendor fix RHSA-2026:87410
  • Red Hat OpenShift AI 3.4 rhoai/odh-feature-server-rhel9 1791863220, rhoai/odh-th06-cpu-torch210-py312-rhel9 1791874335, rhoai/odh-th06-rocm64-torch291-py312-rhel9 1791872119, rhoai/odh-th06-cuda130-torch210-py312-rhel9 1791961113, rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9 1791829069, rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 1791829182, +15 more
    fixed: vendor fix RHSA-2026:84734
  • Red Hat OpenShift AI 3.5 rhoai/odh-th-torch-cpu-py312-rhel9 1791926611, rhoai/odh-th-torch-cuda-py312-rhel9 1791927642, rhoai/odh-th-torch-rocm-py312-rhel9 1791925861, rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9 1791572004, rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 1791816462, rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 1791951049, +15 more
    fixed: vendor fix RHSA-2026:86891
  • Red Hat Migration Toolkit for Applications 8 mta/mta-solution-server-rhel9
    not affected: component not present
  • Red Hat OpenShift AI 2.25 rhoai/odh-rhel9-operator 1792570619, rhoai/odh-vllm-cpu-rhel9 1792018436, rhoai/odh-dashboard-rhel9 1791853525, rhoai/odh-modelmesh-rhel9 1790881700, rhoai/odh-operator-bundle 1792571069, rhoai/odh-vllm-cuda-rhel9 1791358976, +48 more Red Hat OpenShift AI 3.4 rhoai/odh-cli-rhel9 1791509689, rhoai/rhai-cli-rhel9 1791509689, rhoai/odh-automl-rhel9 1791535789, rhoai/odh-mlflow-rhel9 1791865967, rhoai/odh-autorag-rhel9 1791557539, rhoai/odh-trainer-rhel9 1791869783, +79 more Red Hat OpenShift AI 3.5 rhoai/odh-cli-rhel9 1791945905, rhoai/rhai-cli-rhel9 1791945905, rhoai/odh-automl-rhel9 1791916705, rhoai/odh-mlflow-rhel9 1791947857, rhoai/odh-autorag-rhel9 1791903266, rhoai/odh-trainer-rhel9 1791952138, +92 more
    not affected: vulnerable code not present
  • Red Hat OpenShift Container Platform 4 python-mistune 0.8.3-15.2.el9ocp
    not affected: vulnerable code not in execute path

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
Proof of concept is public
Automatable
yes
Technical impact
partial
Assessed
2 mo ago

Exploit prediction

0.49% chance of exploitation in the next 30 days, higher than 42% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/lepture/mistune/security/advisories/GHSA-6m44-fpc8-c3rq referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
GitHub 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
OSV 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi mistune
>=3.3.0, <3.3.3
3.3.3

Affected products

  • lepture mistune

Classification

Weakness

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.