<Vulnerability name="CVE-2026-59923">
    <DocumentDistribution xml:lang="en">Copyright © 2012 Red Hat, Inc. All rights reserved.</DocumentDistribution>
    <ThreatSeverity>Moderate</ThreatSeverity>
    <PublicDate>2026-07-08T16:14:39</PublicDate>
    <Bugzilla id="2498142" url="https://bugzilla.redhat.com/show_bug.cgi?id=2498142" xml:lang="en:us">
mistune: Mistune: Arbitrary code execution through crafted Markdown links
    </Bugzilla>
    <CVSS3 status="draft">
        <CVSS3BaseScore>6.1</CVSS3BaseScore>
        <CVSS3ScoringVector>CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N</CVSS3ScoringVector>
    </CVSS3>
    <CWE>CWE-79</CWE>
    <Details xml:lang="en:us" source="Mitre">
Mistune is a Python Markdown parser with renderers and plugins. Prior to 3.3.0, HTMLRenderer.safe_url() does not block percent-encoded javascript URIs, allowing attacker-supplied Markdown links or images to bypass URL protections and execute script in rendered HTML. This issue is fixed in version 3.3.0.
    </Details>
    <Details xml:lang="en:us" source="Red Hat">
A flaw was found in Mistune, a Python Markdown parser. This vulnerability allows an attacker to bypass URL protections by using specially crafted Markdown links or images containing percent-encoded javascript URIs. This can lead to the execution of arbitrary scripts in the rendered HTML, potentially compromising the user's system.
    </Details>
    <Statement xml:lang="en:us">
Red Hat products ship python-mistune in both the older 0.8.x series and newer 3.x series. The URL sanitization bypass applies to both versions: the 0.8.x escape_link() function and the 3.x safe_url() function both fail to decode percent-encoded characters before checking for dangerous URI schemes. Exploitation requires an attacker who can inject Markdown content into an application that renders it with mistune, and a victim who clicks the malicious link. This limits the exposure.
    </Statement>
    <Mitigation xml:lang="en:us">
Applications that render user-supplied Markdown with mistune can pass the HTML output through a dedicated HTML sanitizer such as bleach or nh3 before serving it to users. This removes dangerous URI schemes regardless of encoding.
    </Mitigation>
    <PackageState cpe="cpe:/a:redhat:migration_toolkit_applications:8">
        <ProductName>Migration Toolkit for Applications 8</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>mta/mta-solution-server-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-th06-cpu-torch210-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-th06-cpu-torch291-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-th06-cuda130-torch210-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-th06-cuda130-torch291-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-th06-rocm64-torch291-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift_ai">
        <ProductName>Red Hat OpenShift AI (RHOAI)</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:openshift:4">
        <ProductName>Red Hat OpenShift Container Platform 4</ProductName>
        <FixState>Fix deferred</FixState>
        <PackageName>python-mistune</PackageName>
    </PackageState>
    <PackageState cpe="cpe:/a:redhat:satellite:6">
        <ProductName>Red Hat Satellite 6</ProductName>
        <FixState>Under investigation</FixState>
        <PackageName>satellite/iop-advisor-engine-rhel9</PackageName>
    </PackageState>
    <References xml:lang="en:us">
https://www.cve.org/CVERecord?id=CVE-2026-59923
https://nvd.nist.gov/vuln/detail/CVE-2026-59923
https://github.com/lepture/mistune/commit/c7101fcbb6e8790e8e39157c5ca2238fc6dd6cbc
https://github.com/lepture/mistune/releases/tag/v3.3.0
https://github.com/lepture/mistune/security/advisories/GHSA-8c25-4j27-2rv3
    </References>
</Vulnerability>