Raw vector
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-27622 is a high-severity Out-of-bounds Write (CWE-787) vulnerability in Openexr Openexr. Its CVSS base score is 8.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 10th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-27622 is a buffer overflow vulnerability (CWE-787) in the OpenEXR library, the reference implementation and specification for the EXR image file format widely used in the motion picture industry. The issue occurs in the CompositeDeepScanLine::readPixels function, where per-pixel totals accumulated in a vector<unsigned int> total_sizes wrap around modulo 2^32 due to attacker-controlled large counts across many parts. This leads to an underestimated overall_sample_count, causing samples[channel].resize to allocate an undersized buffer, which is later overrun during decode pointer setup and write operations in generic_unpack_deep_pointers.
The vulnerability has a CVSS v3.1 base score of 7.8 (AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H), indicating local access with low attack complexity, no privileges required, and user interaction needed. A local attacker can exploit it by supplying a malformed EXR file that tricks a user into processing it via an application using vulnerable OpenEXR versions, potentially achieving arbitrary code execution with high impacts on confidentiality, integrity, and availability through the buffer overrun.
The GitHub Security Advisory (GHSA-cr4v-6jm6-4963) confirms the vulnerability and states it is fixed in OpenEXR versions v3.2.6, v3.3.8, and v3.4.6. Security practitioners should update affected OpenEXR deployments to these patched releases and validate EXR file inputs where possible to mitigate risks from untrusted sources.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-9342
Vulnerability Data
OpenEXR provides the specification and reference implementation of the EXR file format, an image storage format for the motion picture industry. In CompositeDeepScanLine::readPixels, per-pixel totals are accumulated in vector<unsigned int> total_sizes for attacker-controlled large counts across many parts, total_sizes[ptr] wraps…
more
modulo 2^32. overall_sample_count is then derived from wrapped totals and used in samples[channel].resize(overall_sample_count). Decode pointer setup/consumption proceeds with true sample counts, and write operations in core unpack (generic_unpack_deep_pointers) overrun the undersized composite sample buffer. This vulnerability is fixed in v3.2.6, v3.3.8, and v3.4.6.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V5.2.6
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and bounds checks) finds out-of-bounds write flaws before deployment.
Requiring documented secure-development standards and tools can mandate bounds-checked coding practices that avoid the weakness.
Secure engineering principles require use of safe arithmetic constructs or language features that structurally eliminate integer overflow during calculation.
Input validation can structurally reject or sanitize data that would otherwise trigger an out-of-bounds write.
Memory-protection mechanisms limit the exploitability and blast radius of a successful out-of-bounds write.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure-development practices (static analysis, bounds checking, code review) are the primary means of preventing out-of-bounds writes.
Vulnerability scanning and recording can discover out-of-bounds write flaws so they can be remediated.
Patching or replacing vulnerable software directly eliminates known instances of this coding weakness.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development and acceptance can detect and prevent out-of-bounds write defects.
Secure development life cycle mandates practices that prevent out-of-bounds writes.
Application security requirements can specify bounds-checking and safe memory handling.
Secure architecture and engineering principles reduce the likelihood of buffer overflows.
Secure coding directly addresses out-of-bounds writes through language choice and coding standards.
Change management can enforce review gates that catch unsafe memory operations before deployment.