CVE-2026-47747
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 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.
Vulnerability Summary
CVSS v3 Score
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS Score (Exploitation Probability)
This vulnerability has a 0.14% probability of being exploited in the next 30 days, ranking higher than 4% of all scored CVEs.
Related Vulnerabilities
Same Weakness Type(CWE-122, CWE-787)
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 GLOBAL opcode handler. The issue was caused by missing validation when searching for newline-delimited fields. A crafted .ckpt file without the expected newline could cause the parser to use -1 as a copy length, resulting in immediate heap corruption. The attack requires the victim or application to load a .ckpt file from an untrusted source, such as a downloaded model from a model sharing site. 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 following these instructions: do not load .ckpt checkpoint files from untrusted sources, and prefer trusted model sources and safer formats such as .safetensors where possible.
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Similar SeverityHIGH
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