Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P/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-2026-28231 is a medium-severity Out-of-bounds Read (CWE-125) vulnerability in Bigcat88 Pillow-Heif. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 47th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Computer Vision; in the Privacy and Disclosure risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-8 (Security and Privacy Engineering Principles) — 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-2026-28231 is an integer overflow vulnerability in the encode path buffer validation within the `_pillow_heif.c` file of the pillow_heif Python library, which handles HEIF images and serves as a plugin for Pillow. Versions prior to 1.3.0 are affected, where large image dimensions provided by an attacker can bypass bounds checks, triggering a heap out-of-bounds read. This issue, tied to CWE-125 (Out-of-bounds Read) and CWE-190 (Integer Overflow or Wraparound), carries a CVSS v3.1 base score of 9.1 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H) and was published on 2026-02-27.
Any remote attacker can exploit this vulnerability without privileges or user interaction by supplying maliciously crafted image dimensions during the encoding process, which requires no special configuration and triggers under default settings. Successful exploitation results in either information disclosure, where server heap memory leaks into the encoded images, or denial of service via process crash.
The pillow_heif project addresses this in version 1.3.0, available via the release at https://github.com/bigcat88/pillow_heif/releases/tag/v1.3.0. The fixing commit is at https://github.com/bigcat88/pillow_heif/commit/8305a15d3780c533b762578cbe987d27a2c59c7a, and further details are in the security advisory at https://github.com/bigcat88/pillow_heif/security/advisories/GHSA-5gjj-6r7v-ph3x. Security practitioners should update to 1.3.0 or later to mitigate the risk.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-9061
Vulnerability Data
pillow_heif is a Python library for working with HEIF images and plugin for Pillow. Prior to version 1.3.0, an integer overflow in the encode path buffer validation of `_pillow_heif.c` allows an attacker to bypass bounds checks by providing large image…
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dimensions, resulting in a heap out-of-bounds read. This can lead to information disclosure (server heap memory leaking into encoded images) or denial of service (process crash). No special configuration is required — this triggers under default settings. Version 1.3.0 fixes the issue.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Computer Vision
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: pillow
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 directly finds out-of-bounds read flaws through static analysis, fuzzing, and dynamic bounds checks.
Secure engineering principles require bounds checking and memory-safe constructs that stop out-of-bounds reads from being introduced.
Process isolation confines the effects of an out-of-bounds read to the compromised process.
Input validation rejects malformed indices or lengths that would otherwise cause reads outside buffer bounds.
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 such as bounds checking and memory-safe languages directly prevent out-of-bounds reads.
Vulnerability scanning and recording can discover instances of out-of-bounds reads after code is deployed.
Routine patching replaces vulnerable code containing out-of-bounds read flaws.
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 includes fuzzing and static analysis that detect out-of-bounds read defects before release.
Logging can record evidence of an out-of-bounds read but does not prevent the weakness itself.
Secure development life cycle mandates input validation and bounds checking that directly prevent out-of-bounds reads.
Application security requirements include explicit bounds and memory-safety specifications that mitigate buffer over-reads.
Secure system architecture and engineering principles require memory-safe design patterns and runtime protections against out-of-bounds access.
Secure coding standards explicitly forbid unsafe pointer arithmetic and mandate bounds-checked reads, eliminating CWE-125.