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CVE-2026-68514


OpenEXR is the reference implementation and specification for the EXR image file format, widely used in the motion picture industry. In versions 3.3.0 through 3.3.12 and 3.4.0 through 3.4.13, the PyOpenEXR Python bindings contain a heap out-of-bounds write triggered when reading a crafted deep scanline EXR file. When a deep file declares a literal channel named left alongside layer-prefixed RGB channels left.R, left.G, and left.B, the wrapper processes the literal left channel first and allocates a scalar deep sample array for it, then reuses that same array as the coalesced destination for the prefixed RGB group. The deep reader registers sample slices with an RGB stride (three lanes) into storage that was allocated with scalar shape, so decoding the deep samples writes past the allocation. Opening such a file through the default public Python API, OpenEXR.File(path), causes a heap buffer overflow during normal deep sample decode, leading to memory corruption and a crash. This issue is fixed in versions 3.3.13 and 3.4.14.


Security Impact Summary

This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 5.5, requiring local system access to exploit with relatively low complexity though user interaction is required and does not require pre-existing privileges . The vulnerability impacts and availability (service disruption) for affected systems.

Historical Context

Reported in 2026, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.


Published

2026-08-25T20:17:02.613

Last Modified

2026-09-09T21:07:31.353

Status

Deferred

Source

[email protected]

Severity

CVSSv3.1: 5.5 (MEDIUM)

Weaknesses
  • Type: Secondary
    CWE-122
    CWE-787

Affected Vendors & Products

-


References

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For affected software, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.