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CVE-2026-53702 Red Hat CVE debrief

A stack buffer overflow flaw was found in the GStreamer H.265 codec parser library (gst-plugins-bad). When parsing a buffering period SEI message, the parser uses an incorrect loop bound derived from cpb_cnt_minus1[i] (the loop index) instead of the sub-layer 0 CPB count cpb_cnt_minus1[0] from the referenced Sequence Parameter Set. A crafted H.265 video file or stream can cause the parser to write beyond the bounds of stack-allocated CPB delay arrays, resulting in a crash or potential stack memory corruption.

Vendor
Red Hat
Product
Red Hat Enterprise Linux 10
CVSS
MEDIUM 6.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-11
Original CVE updated
2026-06-11
Advisory published
2026-06-11
Advisory updated
2026-06-11

Who should care

Users of GStreamer H.265 codec parser library (gst-plugins-bad) should be aware of this vulnerability and take steps to mitigate it.

Technical summary

The vulnerability is caused by an incorrect loop bound in the parser, which can lead to a stack buffer overflow when parsing a buffering period SEI message. This can result in a crash or potential stack memory corruption.

Defensive priority

MEDIUM

Recommended defensive actions

  • Update to the latest version of GStreamer H.265 codec parser library (gst-plugins-bad) as soon as available.
  • Avoid parsing untrusted H.265 video files or streams.

Evidence notes

The CVE-2026-53702 vulnerability was reported by Red Hat.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-53702 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-53702

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-53702 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-53702

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.