How severe is CVE-2026-34760?

CVE-2026-34760 has a CVSS 3.x base score of 5.9, rated medium severity. It is exploitable over network with high attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity high, and availability low.

Is CVE-2026-34760 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (18th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2026-34760?

CVE-2026-34760 affects Vllm. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2026-34760?

Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.

Does CVE-2026-34760 have an EU (EUVD) identifier?

Yes. CVE-2026-34760 is tracked in the ENISA EU Vulnerability Database (EUVD) as EUVD-2026-18522.

When was CVE-2026-34760 published?

CVE-2026-34760 was published on 2026-04-02 and last updated on 2026-06-17.

CVE-2026-34760

CVE-2026-34760 is a medium-severity vulnerability in Vllm with a CVSS 3.x base score of 5.9. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-20.

Key facts

Severity: Medium (CVSS 3.x base score 5.9)
EPSS exploit prediction: 0% (18th percentile)
Actively exploited: Not listed in CISA KEV
EU (EUVD) id: EUVD-2026-18522
Weakness: CWE-20
Affected product: Vllm
Published: 2026-04-02
Last modified: 2026-06-17

Description

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.

Frequently asked questions

What is CVE-2026-34760?: 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.
How severe is CVE-2026-34760?: CVE-2026-34760 has a CVSS 3.x base score of 5.9, rated medium severity. It is exploitable over network with high attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity high, and availability low.
Is CVE-2026-34760 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (18th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2026-34760?: CVE-2026-34760 affects Vllm. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2026-34760?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
Does CVE-2026-34760 have an EU (EUVD) identifier?: Yes. CVE-2026-34760 is tracked in the ENISA EU Vulnerability Database (EUVD) as EUVD-2026-18522.
When was CVE-2026-34760 published?: CVE-2026-34760 was published on 2026-04-02 and last updated on 2026-06-17.

References

Affected products (1)

cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*

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