CVSS 3.1
Вероятност да бъде експлоатирана в следващите 30 дни (EPSS)
Атакува се
Време до експлоатация
Атакува се по мрежата, при специфични условия, с обикновен потребителски вход и без действие от потребителя.
- Експлоатация: няма данни за експлоатация
- Атаката не може да се автоматизира
Описание
Оригинално описание
vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults to using numpy.mean for mono downmixing (to_mono), while the international standard ITU-R BS.775-4 specifies a weighted downmixing algorithm. This discrepancy results in inconsistency between audio heard by humans (e.g., through headphones/regular speakers) and audio processed by AI models (Which infra via Librosa, such as vllm, transformer). This issue has been patched in version 0.18.0.
Засегнати продукти
- vllm-project vllm: >= 0.5.5, < 0.18.0
Вид слабост
История
- 2 април 2026 Публикувано
Други уязвимости в vllm-project vllm
Първоизточници
- https://www.cve.org/CVERecord?id=CVE-2026-34760
- https://nvd.nist.gov/vuln/detail/CVE-2026-34760
- https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8
- https://github.com/vllm-project/vllm/pull/37058
- https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4
- https://github.com/vllm-project/vllm/releases/tag/v0.18.0