GCD AI RADAR
incidents/AIR-2026-0081

CVE-2026-73558: vLLM data leakage vulnerability in activation kernels

Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerabilityData leak

An integer overflow in vLLM activation kernels allowed inference requests in the same batch to consume another user's input, leaking inference results. The issue was patched in version 0.27.0.

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 vulnerabilityprimary
    CVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
  • Data leak
    Training data, chat logs, system prompts, model weights or other AI-system data exposed.
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
13 Aug 2026
first reported
13 Aug 2026
origin
NVD
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-2026-73558 · vllm
record
created 2026-10-18 06:33Z · updated 2026-10-18 07:00Z · json

Sources · 2

  1. 2026-08-13
    CVE-2026-73558: vLLM is an inference and serving engine for large language models.
    NVD · nvd.nist.gov/vuln/detail/CVE-2026-73558
  2. 2026-09-08
    CVE-2026-73558: vLLM: Cross-User Data Leak Vulnerability
    GitHub Advisory Database · github.com/advisories/GHSA-7m6h-x95x-82q5

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