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CVE-2026-34760

CVE-2026-34760 · vLLM: Downmix Implementation Differences as Attack Vectors Against Audio AI Models

Esta página presenta datos de fuentes públicas de vulnerabilidades. Consulta el aviso original antes de actualizar.

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.

CVSS 5.9 · Media · EPSS 0,3% · Corrección disponible

Publicación
Actualización

Pila tecnológica: python

Productos y versiones afectados

  • vllm

    Versiones
    • >= 0.5.5, < 0.18.0: Afectada

    Sin corrección publicada

  • vllm PyPI

    Versiones
    • 0.10.0
    • 0.10.1
    • 0.10.1.1
    • 0.10.2
    • 0.11.0
    • 0.11.1
    • 0.11.2
    • 0.12.0
    • 0.13.0
    • 0.14.0
    • 0.14.1
    • 0.15.0
    • 0.15.1
    • 0.16.0
    • 0.17.0
    • 0.17.1
    • 0.5.5
    • 0.6.0
    • 0.6.1
    • 0.6.1.post1
    • 0.6.1.post2
    • 0.6.2
    • 0.6.3
    • 0.6.3.post1
    • 0.6.4
    • 0.6.4.post1
    • 0.6.5
    • 0.6.6
    • 0.6.6.post1
    • 0.7.0
    • 0.7.1
    • 0.7.2
    • 0.7.3
    • 0.8.0
    • 0.8.1
    • 0.8.2
    • 0.8.3
    • 0.8.4
    • 0.8.5
    • 0.8.5.post1
    • 0.9.0
    • 0.9.0.1
    • 0.9.1
    • 0.9.2
    Intervalos de versiones afectados
    • ECOSYSTEM: ≥ 0.5.5, < 0.18.0

    Actualiza a 0.18.0

Fuentes originales

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