VllmApplication

CVE-2026-25960

CRITICAL · 9.8 CVSS v3.1 Published 2026-03-09
Fix available
A fix is available. Upgrade to 0.17.0 or later.
See remediation →
100/100
Remediation priority · Urgent
Public exploit Remotely reachable No privileges Zero-click Patch available

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
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.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

This is an SSRF bypass vulnerability in vLLM's load_from_url_async method. The fix for CVE-2026-24779 used urllib3.util.parse_url() to validate URLs, but the actual HTTP requests are made using aiohttp which internally uses the yarl library for URL parsing. Due to inconsistent URL parsing behavior between these two libraries, specially crafted URLs can pass validation but be interpreted differently by aiohttp, allowing attackers to access internal services that should be protected by SSRF controls.

MitigationUntil an official patch is released, avoid using load_from_url_async with untrusted user-provided URLs. Consider implementing additional network-level controls to restrict outbound connections from the inference server.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
VllmApplication
Affected:>= 0.15.1, < 0.17.0

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

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

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Check installed vLLM version
    Run `pip show vllm` or `pip list | grep vllm` to see the installed version number
    Affected if The version is >= 0.15.1 and < 0.17.0 (including any 0.16.x release)
  2. Identify usage of load_from_url_async
    Search codebase or configuration files for references to `load_from_url_async` method, particularly in model loading or data loading contexts
    Affected if The method is actively used or exposed in the deployment configuration
  3. Verify URL-based model loading is enabled
    Inspect configuration files (e.g., config.yaml, environment variables) for settings that enable loading models or data from HTTP/HTTPS URLs
    Affected if URL-based loading is enabled and the service can accept external URLs for model or data input
  4. Check network exposure of the vLLM service
    Review network configuration to determine if the vLLM service has access to internal network resources or if there are firewall/network policies restricting outbound connections
    Affected if The service can make outbound HTTP connections to internal network targets (e.g., internal APIs, metadata services, intranet resources)

You are affected if vLLM version is 0.15.1 through 0.16.x AND the load_from_url_async functionality is in use, allowing potentially malicious URLs to bypass SSRF protection and access internal resources.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 0.17.0 or later
Fixed in 0.17.0
Vendor patch github.com →
Interim mitigation

Until an official patch is released, avoid using load_from_url_async with untrusted user-provided URLs. Consider implementing additional network-level controls to restrict outbound connections from the inference server.

Recommended fix High confidence

vLLM 0.17.0

  1. Upgrade vLLM to version 0.17.0 or later to resolve the SSRF vulnerability
  2. Verify the upgrade by checking the vLLM version with: `vllm --version`
  3. Ensure any custom URL loading configurations are tested after upgrade
Caveat Review vLLM 0.17.0 release notes for any breaking changes between your current version and 0.17.0

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Vllm Scoped from the published advisory
  • Consultation4.0 h
  • Implementation12.0 h
  • Testing6.0 h
  • Review / QA3.0 h
25.0 hours of engineering $4,400
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-25960 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
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