{
 "id": "AIR-2026-0555",
 "slug": "cve-2026-34755-vllm-denial-of-service-via-unbounded-base64-f",
 "title": "CVE-2026-34755: vLLM Denial of Service via Unbounded Base64 Frames",
 "summary": "An out-of-memory vulnerability in vLLM allows attackers to crash the server via an unbounded base64-encoded video frame input. The vendor was notified and the issue is documented in a security advisory.",
 "type": "attack_on_ai",
 "categories": [
  "infra_vuln"
 ],
 "severity": 2,
 "targets": [
  "framework_or_tooling"
 ],
 "products": [
  "vLLM"
 ],
 "incident_date": "2026-04-03",
 "incident_date_precision": "day",
 "first_reported": "2026-04-03",
 "sources": [
  {
   "url": "https://github.com/advisories/GHSA-pq5c-rjhq-qp7p",
   "publisher": "GitHub Advisory Database",
   "title": "CVE-2026-34755: vLLM: Denial of Service via Unbounded Frame Count in video/jpeg Base64 Processing",
   "published_at": "2026-04-03"
  },
  {
   "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34755",
   "publisher": "NVD",
   "title": "CVE-2026-34755: vLLM is an inference and serving engine for large language models (LLMs).",
   "published_at": "2026-04-06"
  }
 ],
 "source_count": 2,
 "confidence": 0.95,
 "status": "published",
 "origin": "seed_ghsa",
 "tags": [
  "CVE-2026-34755",
  "dos",
  "vllm"
 ],
 "created_at": "2026-10-18T07:00:14.101Z",
 "updated_at": "2026-10-18T10:04:21.885Z"
}