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 return stale heap data when reading a crafted deep scanline EXR that uses layer-prefixed RGB channels. With the default channel coalescing (separate_channels=False), the wrapper groups channels such as left.R, left.G, and left.B into a single RGB sample array, but the lane-offset calculation in PyPart::setDeepSliceData() only recognizes the exact unprefixed names G, B, and A. As a result, prefixed channels like left.G and left.B are decoded into lane 0 while lanes 1 and 2 are left uninitialized and returned to Python. A Python application that reads untrusted deep EXR files through the default OpenEXR.File API and then logs, serializes, previews, or otherwise processes the resulting NumPy sample arrays may expose uninitialized same-process heap contents, in addition to receiving incorrect green and blue channel data. This issue is fixed in versions 3.3.13 and 3.4.14.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 4.3, indicating it can be exploited remotely over the network with relatively low complexity though user interaction is required and does not require pre-existing privileges . The vulnerability impacts limited data confidentiality, for affected systems.
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.
2026-08-25T19:16:52.120
2026-08-25T20:17:00.027
Received
CVSSv3.1: 4.3 (MEDIUM)
-
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.