Vulnerability-Lookup

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

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

URL	Tags
security-advisories@github.com	https://github.com/vllm-project/vllm/commit/6f3b2047abd4a748e3db4a68543f8221358002c0	Patch
security-advisories@github.com	https://github.com/vllm-project/vllm/pull/34743	Issue Tracking, Patch
security-advisories@github.com	https://github.com/vllm-project/vllm/security/advisories/GHSA-qh4c-xf7m-gxfc	Not Applicable
security-advisories@github.com	https://github.com/vllm-project/vllm/security/advisories/GHSA-v359-jj2v-j536	Exploit, Patch, Vendor Advisory
0b0ca135-0b70-47e7-9f44-1890c2a1c46c	https://access.redhat.com/errata/RHSA-2026:24977
0b0ca135-0b70-47e7-9f44-1890c2a1c46c	https://access.redhat.com/errata/RHSA-2026:42644
0b0ca135-0b70-47e7-9f44-1890c2a1c46c	https://access.redhat.com/security/cve/CVE-2026-25960
0b0ca135-0b70-47e7-9f44-1890c2a1c46c	https://bugzilla.redhat.com/show_bug.cgi?id=2445892
0b0ca135-0b70-47e7-9f44-1890c2a1c46c	https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-25960.json

Impacted products

	Vendor	Product	Version
	vllm	vllm	*

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "vllm",
          "vendor": "vllm-project",
          "versions": [
            {
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              "criteria": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*",
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              "versionEndExcluding": "0.17.0",
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              "vulnerable": true
            }
          ],
          "negate": false,
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      ]
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  ],
  "cveTags": [],
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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",
  "metrics": {
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          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "LOW",
          "baseScore": 7.1,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L",
          "version": "3.1"
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        "impactScore": 4.2,
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          "baseScore": 9.8,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
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}

CVE-2026-25960 (GCVE-0-2026-25960)

Vulnerability from cvelistv5 – Published: 2026-03-09 21:01 – Updated: 2026-07-21 12:04

Title

SSRF Protection Bypass in vLLM

Summary

Severity

7.1 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-03-10 15:01 UTC

CWE

CWE-918 - Server-Side Request Forgery (SSRF)
CWE-474 - Use of Function with Inconsistent Implementations

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7595 records in the last 180 days details

References

9 references

URL	Tags
https://github.com/vllm-project/vllm/security/adv…	x_refsource_CONFIRM
https://github.com/vllm-project/vllm/security/adv…	x_refsource_MISC
https://github.com/vllm-project/vllm/pull/34743	x_refsource_MISC
https://github.com/vllm-project/vllm/commit/6f3b2…	x_refsource_MISC
https://access.redhat.com/security/cve/CVE-2026-25960	vdb-entryx_refsource_REDHAT
https://bugzilla.redhat.com/show_bug.cgi?id=2445892	issue-trackingx_refsource_REDHAT
https://security.access.redhat.com/data/csaf/v2/v…	x_sadp-csaf-vex
https://access.redhat.com/errata/RHSA-2026:42644	vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/errata/RHSA-2026:24977	vendor-advisoryx_refsource_REDHAT

Impacted products

7 products

Vendor	Product	Version
vllm-project	vllm	Affected: >= 0.15.1, < 0.17.0
Red Hat	Red Hat OpenShift AI 2.25	Unaffected: 1780069069 , < * (rpm) cpe:/a:redhat:openshift_ai:2.25::el9
Red Hat	Red Hat OpenShift AI 2.25	Unaffected: 1783998774 , < * (rpm) cpe:/a:redhat:openshift_ai:2.25::el9
Red Hat	Red Hat OpenShift AI 2.25	Unaffected: 1783998857 , < * (rpm) cpe:/a:redhat:openshift_ai:2.25::el9
Red Hat	Red Hat AI Inference Server	cpe:/a:redhat:ai_inference_server:3
Red Hat	Red Hat Enterprise Linux AI (RHEL AI) 3	cpe:/a:redhat:enterprise_linux_ai:3
Red Hat	Red Hat OpenShift AI (RHOAI)	cpe:/a:redhat:openshift_ai

Show details on NVD website

JSON

To clipboard

{
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    "adp": [
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        "metrics": [
          {
            "other": {
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                "id": "CVE-2026-25960",
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                  },
                  {
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                "role": "CISA Coordinator",
                "timestamp": "2026-03-10T15:01:11.202728Z",
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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

FKIE_CVE-2026-25960

CVE-2026-25960 (GCVE-0-2026-25960)

Tags

Sightings

Nomenclature

Related by attack behaviour