CVE-2026-0992: libxml2: catalog loop DoS in ML platform images
LOWThis is a low-severity (CVSS 2.9) denial-of-service flaw in libxml2, where crafted XML catalogs with repeated <nextCatalog> entries pointing to the same downstream catalog force the parser to redundantly traverse catalog chains and burn CPU. The blast radius is wide because libxml2 is a base-image dependency: 695 downstream dependents are tracked, and Red Hat lists dozens of OpenShift AI (rhoai) operator and controller images, including KServe, KubeRay, MLflow, Model Registry and Notebook controllers, plus OpenShift CoreOS nodes. Exploitation likelihood is low: the attack vector is local with high complexity, there is no EPSS score, no public exploit, no Nuclei template, and it is not in CISA KEV. Treat it as routine patch hygiene: apply Red Hat errata RHSA-2026:7519 and rebuild or pull updated rhoai images in the normal maintenance cycle, prioritizing components that parse untrusted XML or catalogs.
What is the risk?
Low overall. CVSS 3.1 is 2.9 (AV:L/AC:H/PR:N/UI:N/A:L), with availability-only impact and no confidentiality or integrity effect. Exploitation requires local access to supply a crafted catalog and high attack complexity. No EPSS data, public exploit, scanner template or KEV listing exists. The main aggravating factor is exposure breadth: libxml2 sits in many container images across OpenShift AI, and the package has a risk score of 81/100, 137 other CVEs and an OpenSSF Scorecard of 5.4/10, indicating a heavily scrutinized and moderately maintained dependency.
How does the attack unfold?
What systems are affected?
How severe is it?
What is the attack surface?
What should I do?
1 step1) Apply Red Hat errata RHSA-2026:7519 and update to the patched libxml2 build; pull refreshed rhoai operator and component images and OpenShift CoreOS releases containing the fix. 2) Inventory container images and SBOMs for libxml2 to identify unpatched workloads. 3) Do not allow untrusted users or inputs to supply XML catalogs or set XML_CATALOG_FILES; restrict write access to catalog files. 4) Set CPU limits and requests on pods so a runaway parser cannot starve neighbours. 5) Alert on sustained high CPU in operator and controller pods and on repeated restarts. 6) Track the upstream issue (GNOME/libxml2 #1019) and Red Hat Bugzilla 2429975 for further fixes.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2026-0992?
This is a low-severity (CVSS 2.9) denial-of-service flaw in libxml2, where crafted XML catalogs with repeated <nextCatalog> entries pointing to the same downstream catalog force the parser to redundantly traverse catalog chains and burn CPU. The blast radius is wide because libxml2 is a base-image dependency: 695 downstream dependents are tracked, and Red Hat lists dozens of OpenShift AI (rhoai) operator and controller images, including KServe, KubeRay, MLflow, Model Registry and Notebook controllers, plus OpenShift CoreOS nodes. Exploitation likelihood is low: the attack vector is local with high complexity, there is no EPSS score, no public exploit, no Nuclei template, and it is not in CISA KEV. Treat it as routine patch hygiene: apply Red Hat errata RHSA-2026:7519 and rebuild or pull updated rhoai images in the normal maintenance cycle, prioritizing components that parse untrusted XML or catalogs.
Is CVE-2026-0992 actively exploited?
No confirmed active exploitation of CVE-2026-0992 has been reported, but organizations should still patch proactively.
How to fix CVE-2026-0992?
1) Apply Red Hat errata RHSA-2026:7519 and update to the patched libxml2 build; pull refreshed rhoai operator and component images and OpenShift CoreOS releases containing the fix. 2) Inventory container images and SBOMs for libxml2 to identify unpatched workloads. 3) Do not allow untrusted users or inputs to supply XML catalogs or set XML_CATALOG_FILES; restrict write access to catalog files. 4) Set CPU limits and requests on pods so a runaway parser cannot starve neighbours. 5) Alert on sustained high CPU in operator and controller pods and on repeated restarts. 6) Track the upstream issue (GNOME/libxml2 #1019) and Red Hat Bugzilla 2429975 for further fixes.
What systems are affected by CVE-2026-0992?
This vulnerability affects the following AI/ML architecture patterns: Model serving, MLOps platforms, Training pipelines, Notebook and workbench environments, Kubernetes operators and controllers, Container base images.
What is the CVSS score for CVE-2026-0992?
CVE-2026-0992 has a CVSS v3.1 base score of 2.9 (LOW).
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0029Denial of AI ServiceAML.T0034.001Resource-Intensive QueriesCompliance Controls Affected
What are the technical details?
Original Advisory
A flaw was found in the libxml2 library. This uncontrolled resource consumption vulnerability occurs when processing XML catalogs that contain repeated <nextCatalog> elements pointing to the same downstream catalog. A remote attacker can exploit this by supplying crafted catalogs, causing the parser to redundantly traverse catalog chains. This leads to excessive CPU consumption and degrades application availability, resulting in a denial-of-service condition.
Exploitation Scenario
An attacker with a local foothold, such as a compromised notebook or workbench user in a shared OpenShift AI cluster, places a crafted XML catalog containing many repeated <nextCatalog> entries pointing to the same downstream catalog in a location read by a component using libxml2 catalog resolution. When the process resolves a document through that catalog, the parser redundantly traverses the chain, pinning CPU. The affected controller or service slows or becomes unresponsive, degrading model serving or pipeline operations until the process is restarted.
Weaknesses (CWE)
CWE-400 — Uncontrolled Resource Consumption: The product does not properly control the allocation and maintenance of a limited resource.
- [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: 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. 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.
Source: MITRE CWE corpus.
CVSS Vector
CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:LReferences
- access.redhat.com/errata/RHSA-2026:7519vendor-advisoryx_refsource_REDHAT
- access.redhat.com/security/cve/CVE-2026-0992vdb-entryx_refsource_REDHAT
- bugzilla.redhat.com/show_bug.cgiissue-trackingx_refsource_REDHAT
- gitlab.gnome.org/GNOME/libxml2/-/issues/1019
Timeline
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