FKIE_CVE-2026-25960
Vulnerability from fkie_nvd - Published: 2026-03-09 21:16 - Updated: 2026-07-21 12:17
Severity
7.1 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
7.1 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
9.8 (Critical) - CVSS:3.1/
7.1 (High) - CVSS:3.1/
Summary
vLLM is an inference and serving engine for large language models (LLMs). The SSRF protection fix for CVE-2026-24779 add in 0.15.1 can be bypassed in the load_from_url_async method due to inconsistent URL parsing behavior between the validation layer and the actual HTTP client. The SSRF fix uses urllib3.util.parse_url() to validate and extract the hostname from user-provided URLs. However, load_from_url_async uses aiohttp for making the actual HTTP requests, and aiohttp internally uses the yarl library for URL parsing. This vulnerability in 0.17.0.
References
{
"affected": [
{
"affectedData": [
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"vendor": "vllm-project",
"versions": [
{
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"version": "\u003e= 0.15.1, \u003c 0.17.0"
}
]
}
],
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},
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"version": "1783998774",
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}
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"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
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"configurations": [
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"nodes": [
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"cveTags": [],
"descriptions": [
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"lang": "en",
"value": "vLLM is an inference and serving engine for large language models (LLMs). The SSRF protection fix for CVE-2026-24779 add in 0.15.1 can be bypassed in the load_from_url_async method due to inconsistent URL parsing behavior between the validation layer and the actual HTTP client. The SSRF fix uses urllib3.util.parse_url() to validate and extract the hostname from user-provided URLs. However, load_from_url_async uses aiohttp for making the actual HTTP requests, and aiohttp internally uses the yarl library for URL parsing. This vulnerability in 0.17.0."
},
{
"lang": "es",
"value": "vLLM es un motor de inferencia y servicio para modelos de lenguaje grandes (LLMs). La correcci\u00f3n de protecci\u00f3n contra SSRF para CVE-2026-24779 a\u00f1adida en 0.15.1 puede ser eludida en el m\u00e9todo load_from_url_async debido a un comportamiento inconsistente de an\u00e1lisis de URL entre la capa de validaci\u00f3n y el cliente HTTP real. La correcci\u00f3n de SSRF utiliza urllib3.util.parse_url() para validar y extraer el nombre de host de las URL proporcionadas por el usuario. Sin embargo, load_from_url_async utiliza aiohttp para realizar las solicitudes HTTP reales, y aiohttp utiliza internamente la biblioteca yarl para el an\u00e1lisis de URL. Esta vulnerabilidad en 0.17.0."
}
],
"id": "CVE-2026-25960",
"lastModified": "2026-07-21T12:17:46.680",
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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| Author | Source | Type | Date | Other |
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Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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