GCD AI RADAR
incidents/AIR-2025-0374

CVE-2025-62372: vLLM vulnerable to denial of service via multimodal embedding inputs

Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerability

Users could crash the vLLM inference engine serving multimodal models by supplying embedding inputs with incorrect shapes. The issue allowed unauthenticated denial of service attacks against the engine.

disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why

Details

type
Attack on AI
An AI model, agent or AI-powered product was the thing exploited, abused or leaked.
categories
  • Infrastructure vulnerability
    CVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
owasp llm top 10
mitre atlas
no technique for these categories
Both rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
severity
2 · Disclosed vulnerability
CVE or vendor advisory, patched or patchable, no confirmed exploitation.
targets
Framework / tooling
products
vLLM
incident date
20 Nov 2025
first reported
20 Nov 2025
origin
GitHub Advisory Database
Vulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
classifier confidence
0.95 · published at or above 0.80; see the methodology
tags
CVE-2025-62372 · vllm · dos
record
created 2026-10-18 07:00Z · updated 2026-10-18 10:04Z · json

Sources · 2

  1. 2025-11-20
    CVE-2025-62372: vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs
    GitHub Advisory Database · github.com/advisories/GHSA-pmqf-x6x8-p7qw
  2. 2025-11-21
    CVE-2025-62372: vLLM is an inference and serving engine for large language models (LLMs).
    NVD · nvd.nist.gov/vuln/detail/CVE-2025-62372

Titles and links belong to their publishers. The summary above is written by GCD AI RADAR in its own words; data is CC BY-SA 4.0.

Related incidents