CVE-2026-56210 (GCVE-0-2026-56210)
Vulnerability from cvelistv5 – Published: 2026-06-19 16:28 – Updated: 2026-11-04 22:51
VLAI
EPSS
VEX
Title
Libaom: libaom: heap-buffer-overflow read via missing bounds check in ctrl_set_layer_id
Summary
A heap-buffer-overflow read vulnerability was found in libaom, the reference AV1 codec implementation. A missing bounds check in the SVC (Scalable Video Coding) layer ID control function allows setting a spatial_layer_id exceeding the configured number of layers. This causes an out-of-bounds heap read of approximately 40,728 bytes when computing a layer context array index. An attacker who can influence SVC encoder parameters in a network-facing service could exploit this for information disclosure (heap content leak) or denial of service (segmentation fault from hitting unmapped memory).
Severity
7.1 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-22 18:22 UTC
CWE
- CWE-125 - Out-of-bounds Read
Assigner
References
53 references
Impacted products
57 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Red Hat | Red Hat Enterprise Linux AI 3.3 for RHEL 9 |
Unaffected:
0:3.14.0-1.el9ai , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.4 for RHEL 9 |
Unaffected:
0:3.14.0-1.el9ai , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.4::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.5 for RHEL 9 |
Unaffected:
0:3.14.0-1.el9ai , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.5::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1787860580 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1787772157 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1787884873 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1789508287 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1789502493 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1789504371 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
||
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1789582776 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790936334 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790936351 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790850900 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790866732 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790791893 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Enterprise Linux AI 3.3 |
Unaffected:
1790954179 , < *
(rpm)
cpe:/a:redhat:enterprise_linux_ai:3.3::el9 |
||
| Red Hat | Red Hat Hardened Images |
Unaffected:
3.14.0-0.1.hum1 , < *
(rpm)
cpe:/a:redhat:hummingbird:1 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789137552 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789137548 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789137636 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789137641 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789137607 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1786611800 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787076778 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787077779 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787076481 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197680 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197530 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197632 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197747 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197549 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788199622 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197744 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1788197677 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1791785804 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788198404 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788198407 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197492 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197542 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197975 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197512 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197688 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788197385 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1788198016 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703552 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703656 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703557 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703645 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703554 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703630 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.5 |
Unaffected:
1790703706 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.5::el9 |
||
| Red Hat | Red Hat AI Inference Server |
cpe:/a:redhat:ai_inference_server:3
|
||
| Red Hat | Red Hat Enterprise Linux 10 |
cpe:/a:redhat:enterprise_linux:10
|
||
| Red Hat | Red Hat Enterprise Linux 9 |
cpe:/a:redhat:enterprise_linux:9
|
||
| Red Hat | Red Hat OpenShift AI (RHOAI) |
cpe:/a:redhat:openshift_ai
|
||
| Red Hat | Red Hat Enterprise Linux 10 |
cpe:/o:redhat:enterprise_linux:10
|
||
| Red Hat | Red Hat Enterprise Linux 9 |
cpe:/o:redhat:enterprise_linux:9
|
Date Public
2026-06-19 00:00
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"timestamp": "2026-06-22T18:22:57.799192Z",
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"product": "Red Hat OpenShift AI 3.4",
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{
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"product": "Red Hat OpenShift AI 3.4",
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"product": "Red Hat OpenShift AI 3.4",
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{
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"cpes": [
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"defaultStatus": "affected",
"packageName": "rhoai/odh-th06-rocm64-torch291-py312-rhel9",
"product": "Red Hat OpenShift AI 3.4",
"vendor": "Red Hat",
"versions": [
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"cpes": [
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"defaultStatus": "affected",
"packageName": "rhaii/model-opt-cuda-rhel9",
"product": "Red Hat AI Inference Server",
"vendor": "Red Hat"
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"product": "Red Hat AI Inference Server",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
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"vendor": "Red Hat"
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{
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"cpes": [
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"product": "Red Hat Enterprise Linux 10",
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{
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"cpes": [
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"packageName": "thunderbird",
"product": "Red Hat Enterprise Linux 10",
"vendor": "Red Hat"
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{
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"cpes": [
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"defaultStatus": "affected",
"packageName": "firefox",
"product": "Red Hat Enterprise Linux 9",
"vendor": "Red Hat"
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{
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"packageName": "thunderbird",
"product": "Red Hat Enterprise Linux 9",
"vendor": "Red Hat"
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{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:openshift_ai"
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"defaultStatus": "affected",
"packageName": "rhai/base-image-cpu-rhel9",
"product": "Red Hat OpenShift AI (RHOAI)",
"vendor": "Red Hat"
},
{
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"cpes": [
"cpe:/a:redhat:openshift_ai"
],
"defaultStatus": "affected",
"packageName": "rhai/base-image-cuda-12.9-rhel9",
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"vendor": "Red Hat"
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{
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"cpes": [
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],
"defaultStatus": "affected",
"packageName": "rhai/base-image-cuda-13.0-rhel9",
"product": "Red Hat OpenShift AI (RHOAI)",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:openshift_ai"
],
"defaultStatus": "affected",
"packageName": "rhai/base-image-gaudi-rhel9",
"product": "Red Hat OpenShift AI (RHOAI)",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:openshift_ai"
],
"defaultStatus": "affected",
"packageName": "rhai/base-image-neuron-rhel9",
"product": "Red Hat OpenShift AI (RHOAI)",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:openshift_ai"
],
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"assignerShortName": "redhat",
"cveId": "CVE-2026-56210",
"datePublished": "2026-06-19T16:28:33.035Z",
"dateReserved": "2026-06-19T15:50:16.801Z",
"dateUpdated": "2026-11-04T22:51:44.869Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
Solutions
ADP · redhat-SADP
RHSA-2026:51100: Red Hat Enterprise Linux AI 3.3 for RHEL 9
RHSA-2026:51146: Red Hat Enterprise Linux AI 3.4 for RHEL 9
RHSA-2026:42875: Red Hat Enterprise Linux AI 3.5 for RHEL 9
RHSA-2026:61628: Red Hat AI Inference Server 3.2
RHSA-2026:61627: Red Hat AI Inference Server 3.2
RHSA-2026:61629: Red Hat AI Inference Server 3.2
RHSA-2026:30814: Red Hat Hardened Images
RHSA-2026:60520: Red Hat OpenShift AI 3.4
Workarounds
CNA · redhat
There is no complete mitigation for this vulnerability. The following measures can reduce risk:
1. If using libaom as a standalone encoder library with SVC enabled, validate that spatial_layer_id does not exceed the number of configured spatial layers before calling aom_codec_control with AV1E_SET_SVC_LAYER_ID.
2. Restrict access to encoding services to trusted clients only.
3. For Firefox and Thunderbird, ensure browsers are updated to versions that include the patched libaom (v3.14.0 or later).
4. Monitor encoding service processes for unexpected crashes (segfaults) that may indicate exploitation attempts.
ADP · redhat-SADP
There is no complete mitigation for this vulnerability. The following measures can reduce risk:
1. If using libaom as a standalone encoder library with SVC enabled, validate that spatial_layer_id does not exceed the number of configured spatial layers before calling aom_codec_control with AV1E_SET_SVC_LAYER_ID.
2. Restrict access to encoding services to trusted clients only.
3. For Firefox and Thunderbird, ensure browsers are updated to versions that include the patched libaom (v3.14.0 or later).
4. Monitor encoding service processes for unexpected crashes (segfaults) that may indicate exploitation attempts.
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.