CVE-2026-47747
Memory Safety in Leejet Stable-Diffusion.Cpp ≤ master-584-0a7ae07
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-47747 is a high-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Leejet Stable-Diffusion.Cpp. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 8th 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 Supply Chain and Deployment 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
No EU or UK CSIRT advisories indexed for this CVE.
Vulnerability Data
stable-diffusion.cpp is a pure C/C++ library for running diffusion model (Stable Diffusion, Flux, Wan, Qwen Image, Z-Image, and more) inference. In versions prior to master-584-0a7ae07, the pickle .ckpt parser in src/model.cpp contained a heap buffer overflow vulnerability in the BINUNICODE…
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opcode handler. The issue was caused by sign confusion on the opcode length field. A crafted .ckpt file could trigger memcpy with a very large length derived from a negative signed value, causing immediate heap corruption. The issue has been resolved in version master-584-0a7ae07. If developers are unable to immediately update their applications they can work around this issue by only loading .ckpt checkpoint files from trusted sources and preferring trusted model sources and safer formats such as .safetensors where possible.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Computer Vision
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: stable diffusion
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.
Requiring documented secure-development standards and tools can mandate bounds-checked coding practices that avoid the weakness.
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 can enforce review gates that catch unsafe memory operations before deployment.