Raw vector
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/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-2026-42309 is a medium-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Python Pillow. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Computer Vision; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-28901
Vulnerability Data
Pillow is a Python imaging library. From version 11.2.1 to before version 12.2.0, passing nested lists as coordinates to APIs that accept coordinates such as ImagePath.Path, ImageDraw.ImageDraw.polygon and ImageDraw.ImageDraw.line could cause a heap buffer overflow, as nested lists were recursively…
more
unpacked beyond the allocated buffer. Coordinate lists are now validated to contain exactly two numeric coordinates. This issue has been patched in version 12.2.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Computer Vision
- Risk Domain
- Other ATLAS/OWASP Terms
- 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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V1.4.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and memory-error detectors) can discover heap overflows after they have been coded.
Input validation enforces bounds checking on data written to heap buffers, directly stopping the overflow condition from being introduced.
Security engineering principles require use of memory-safe constructs and bounds-checked allocation routines that avoid introducing heap overflows.
Memory-protection mechanisms limit the ability of a heap overflow to execute attacker-controlled code or corrupt adjacent structures.
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 directly require bounds checking and safe memory handling that prevent heap overflows.
Vulnerability scanning and recording can discover heap-overflow flaws but does not prevent their introduction in code.
Timely patching removes known heap-overflow instances after they exist.
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 heap overflows before release.
Secure development lifecycle mandates practices that reduce the likelihood of introducing heap overflows.
Application security requirements can specify bounds-checking and safe memory APIs that mitigate heap overflows.
Secure architecture and engineering principles include memory-safety and input-validation controls that address heap overflows.
Secure coding standards directly prescribe techniques (safe functions, bounds checks) that prevent heap-based buffer overflows.
Change management ensures controlled deployment of fixes for discovered heap-overflow vulnerabilities.