OpenEXR: Heap buffer overflow in PyOpenEXR from literal/prefixed RGB channel name collision in deep images
Published Aug 25, 2026 · Updated Nov 3, 2026
Original summary
Normalized public record · Updated Nov 3, 2026
OpenEXR: Heap buffer overflow in PyOpenEXR from literal/prefixed RGB channel name collision in deep images
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QFinch assessment
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.
Evidence: public source recordsAffected products
| Affected package, product or range | Fix status |
|---|---|
| Consult the referenced vendor advisory for affected versions. | Consult source advisory |
Matching a version is only one part of assessing exposure. QFinch has not assessed your environment on this public page.
Remediation
Apply the vendor-supported fixed release or mitigation, then verify the affected component is no longer reachable.
- Confirm the affected product and reachable code path exist in your environment.
- Apply the vendor-supported patch or mitigation from the primary advisory.
- Rescan the exact deployed revision and retain verification evidence.
Evidence coverage
- SSVC priority
- LOW
- Confidence
- Not available
- Aliases
- None reported
Scores appear only when corresponding evidence exists. Missing data is never interpreted as zero risk.
Sources and record history
Record history
Published Aug 25, 2026 · Last refreshed Nov 3, 2026