{"action":"Upgrade vllm to 0.30.0 or later.","affected":[{"fixed":"0.30.0","introduced":"0"}],"component":"vllm","cve_ids":["CVE-2026-93436"],"ecosystem":"PyPI","epss":0.00755,"exploited":false,"fixed_versions":["0.30.0"],"id":"tcs_01M5KH955QTNKTY8AF4SRPAQZQ","modified_at":"2026-09-29T09:00:02.990990531Z","published_at":"2026-09-17T23:18:54.710Z","references":["https://osv.dev/vulnerability/PYSEC-2026-3996","https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/nixl/push_worker.py#L162-L181","https://www.vulncheck.com/advisories/vllm-through-0.29.0-memory-exhaustion-via-rejected-requests","https://github.com/vllm-project/vllm/pull/55677","https://github.com/vllm-project/vllm"],"severity":{"label":"unknown"},"sources":[{"source":"osv","source_id":"PYSEC-2026-3996","url":"https://osv.dev/vulnerability/PYSEC-2026-3996"}],"summary":"vLLM through 0.29.0 fails to properly clean up decode-side metadata for rejected inference requests in prefill/decode disaggregated deployments. Remote attackers can submit requests with max_tokens=0"}