libaom Heap-Buffer-Overflow in SVC Layer ID Read (CVE-2026-56210)
CVE-2026-56210 Published on June 19, 2026

Libaom: libaom: heap-buffer-overflow read via missing bounds check in ctrl_set_layer_id
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).

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Vulnerability Analysis

CVE-2026-56210 is exploitable with network access, requires user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a small impact on confidentiality, a small impact on integrity, and a high impact on availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
NONE
User Interaction:
REQUIRED
Scope:
UNCHANGED
Confidentiality Impact:
LOW
Integrity Impact:
NONE
Availability Impact:
HIGH

Timeline

Reported to Red Hat.

Made public.

Weakness Type

Out-of-bounds Read

The software reads data past the end, or before the beginning, of the intended buffer. Typically, this can allow attackers to read sensitive information from other memory locations or cause a crash. A crash can occur when the code reads a variable amount of data and assumes that a sentinel exists to stop the read operation, such as a NUL in a string. The expected sentinel might not be located in the out-of-bounds memory, causing excessive data to be read, leading to a segmentation fault or a buffer overflow. The software may modify an index or perform pointer arithmetic that references a memory location that is outside of the boundaries of the buffer. A subsequent read operation then produces undefined or unexpected results.


Products Associated with CVE-2026-56210

You can be notified by email with stack.watch whenever vulnerabilities like CVE-2026-56210 are published in these products:

Red Hat Enterprise Linux (RHEL)
 
Red Hat Enterprise Linux Ai
 
Red Hat Hummingbird
 
Red Hat Ai Inference Server
 
Red Hat Openshift Ai
 
Canonical Ubuntu Linux
 

Affected Versions

Red Hat Enterprise Linux AI 3.3 for RHEL 9: Red Hat Enterprise Linux AI 3.4 for RHEL 9: Red Hat Enterprise Linux AI 3.5 for RHEL 9: Red Hat AI Inference Server 3.2: Red Hat AI Inference Server 3.2: Red Hat AI Inference Server 3.2: Red Hat AI Inference Server 3.3: Red Hat AI Inference Server 3.3: Red Hat AI Inference Server 3.3: Red Hat AI Inference Server 3.3: Red Hat Hardened Images: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat OpenShift AI 3.5: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat Enterprise Linux 10: Red Hat Enterprise Linux 10: Red Hat Enterprise Linux 9: Red Hat Enterprise Linux 9: Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat Enterprise Linux AI 3.3 for RHEL 9: Red Hat Enterprise Linux AI 3.4 for RHEL 9: Red Hat Enterprise Linux AI 3.5 for RHEL 9: Red Hat Hardened Images: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat Enterprise Linux 10: Red Hat Enterprise Linux 10: Red Hat Enterprise Linux 9: Red Hat Enterprise Linux 9: Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI): Red Hat OpenShift AI (RHOAI):

Exploit Probability

EPSS
0.25%
Percentile
15.81%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.