CVE intelligence and bounded remediation

CVE-2026-25960 — vLLM is an inference and serving engine for large language models (LLMs)

Critical CVSS 9.8

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.

Severity
Critical
CVSS
9.8 (3.1)
Published
2026-03-09
CISA KEV
Not currently listed
Ecosystem
software/application
Weaknesses
CWE-918, CWE-474

Affected products

  • vllm / vllm

Matched remediation archetype

Server-side request forgery and unintended proxying

This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.

Check exposure

  • Inventory server-side URL fetchers, webhooks, importers, previews, redirects, proxies, and protocol handlers reachable from untrusted input.
  • Map egress paths to internal services, metadata endpoints, loopback, private address space, and privileged control planes.
  • Review DNS resolution, redirect, proxy, credential-forwarding, and URL parsing behavior without requesting sensitive targets.

Remediate safely

  • Replace arbitrary destinations with named integrations or a strict allowlist of schemes, hosts, ports, and paths.
  • Resolve and validate every destination and redirect hop, then enforce egress policy independently of application checks.
  • Remove ambient credentials and sensitive headers from fetchers; apply response size, time, and content limits.

Authoritative sources

Complete CVE record and remediation plan

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