CVE Explorer
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
Known exploited
Not asserted
Disputed
No
Stale source
No
Conflicts
0
Affected products and versions
1 source assertion{"product":"vllm","vendor":"vllm-project","versions":[{"status":"affected","version":">= 0.5.5, < 0.18.0"}]}
- cve_program_cvelist_v5affectedurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/affected/0
Provider-owned CVSS observations
1 source assertion{"metric":{"attackComplexity":"HIGH","attackVector":"NETWORK","availabilityImpact":"LOW","baseScore":5.9,"baseSeverity":"MEDIUM","confidentialityImpact":"NONE","integrityImpact":"HIGH","privilegesRequired":"LOW","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L","version":"3.1"},"metric_type":"cvssV3_1"}
- cve_program_cvelist_v5cvssurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/metrics/0/cvssV3_1
CWE assertions
1 source assertion{"cweId":"CWE-20","description":"CWE-20: Improper Input Validation","lang":"en","type":"CWE"}
- cve_program_cvelist_v5cweurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/problemTypes/0/descriptions/0
Source references
4 source assertions{"name":"https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4"}
- cve_program_cvelist_v5referenceurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/references/2
{"name":"https://github.com/vllm-project/vllm/pull/37058","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/pull/37058"}
- cve_program_cvelist_v5referenceurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/references/1
{"name":"https://github.com/vllm-project/vllm/releases/tag/v0.18.0","tags":["x_refsource_MISC"],"url":"https://github.com/vllm-project/vllm/releases/tag/v0.18.0"}
- cve_program_cvelist_v5referenceurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/references/3
{"name":"https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8","tags":["x_refsource_CONFIRM"],"url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8"}
- cve_program_cvelist_v5referenceurn:baitaphish:normalized-source-record:v2:cd615a72ae6860611fbea8e15492794068b3522455e280c72d7d82eba0caa3d8 · sha256:6f2233c75ec54880… · /containers/cna/references/0
Attribution and limitations
- CVE Program CVEList V5: Reproduce the MITRE copyright designation and CVE license in copies. Source →
Provider severity values are preserved separately. Baitaphish does not convert them into a risk rating, infer affected products, or treat EPSS as observed exploitation.