Vulnerability in vllm (CVE-2026-105760)
Summary
Vulnerability in vllm (CVE-2026-105760). Risk of unauthorized operations or information disclosure. Exploitable via media_io_kwargs. Mitigation: upgrade to 0.30.0 or later.
Original description
The description as published by the source.
Summary
The OpenAI-compatible chat endpoint accepts request-level video loader options through media_io_kwargs. A caller can select the GLMGA sampler and provide large fps and max_frames values. GLMGA first constructs an attacker-sized Python index list and then deduplicates it, even when the supplied video contains only a few frames. This work occurs in the shared media-loading executor before frame reads, allowing a tiny valid video and compact JSON options to consume disproportionate CPU time and memory and delay unrelated media requests.
The demonstrated impact is partial denial of service. No memory corruption, data disclosure, or code execution is claimed.
Affected configuration
The server must expose chat completions for a video-capable model and accept request-level media_io_kwargs. The model does not need to use GLMGA by default because the request value overrides the model's loader mapping. The proof of concept uses an inline two-frame video and explicitly selects the OpenCV decoder, so no external media host or GPU decoder is required.
The request is reachable without vLLM credentials when no API key is configured. With API-key authentication enabled, any caller holding a valid key can reach the same path.
Attack surface
A remote caller submits a valid chat-completion request with a small video and the following request-level options:
{
"media_io_kwargs": {
"video": {
"video_backend": "glmga",
"backend": "opencv",…
Source: NIST National Vulnerability Database NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-105760 has been found in vllm.
Attackers can target a specific entry point like media_io_kwargs over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: 5.3/10.
What to do: upgrade vllm to 0.30.0 or later.
If unsure, ask your IT team or search "vllm CVE-2026-105760" on the vendor's site.
CVE-2026-105760 (vllm) — CWE-400 / CVSS v3 5.3
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Attack surface: media_io_kwargs / fps / max_frames / ChatCompletionRequest
Patched: 0.30.0 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
A vulnerability (CWE-400) exists in vllm. Attackers reach the vulnerable code path via media_io_kwargs without authentication.
Check the vendor advisory for the affected versions of vllm. Attack surface: media_io_kwargs / fps / max_frames / ChatCompletionRequest.
Severity: Medium (CVSS 5.3/10). Risk of unauthorized operations or information disclosure.
Update to 0.30.0.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'vllm' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
grep -r 'vllm' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
vllmを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade vllm to 0.30.0ステージング環境で 0.30.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。