Threats Tagged 'cve-2025-62164'
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Threats Tagged 'cve-2025-62164'
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GCVE Database | 08/04/2026, 16:11:20 UTC Added: 05/26/2026, 20:58:34 UTC | |
GCVE Database | 07/09/2026, 14:48:40 UTC Added: 05/26/2026, 20:58:12 UTC | |
Red Hat® AI Inference Server Join the discussion | GCVE Database | 06/25/2026, 19:29:10 UTC Added: 06/29/2026, 22:10:29 UTC |
Release of RHOAI 3.3.3 provides these changes: Join the discussion | GCVE Database | 05/20/2026, 15:49:06 UTC Added: 05/26/2026, 20:57:56 UTC |
Release of RHOAI 2.25.1 provides these changes: Join the discussion | GCVE Database | 12/17/2025, 15:17:16 UTC Added: 05/27/2026, 21:15:07 UTC |
Red Hat® AI Inference Server Join the discussion | GCVE Database | 12/15/2025, 15:50:15 UTC Added: 05/26/2026, 20:58:28 UTC |
Red Hat® AI Inference Server Join the discussion | GCVE Database | 12/15/2025, 15:38:07 UTC Added: 05/26/2026, 20:58:28 UTC |
Red Hat® AI Inference Server Join the discussion | GCVE Database | 12/15/2025, 15:38:04 UTC Added: 05/26/2026, 20:58:28 UTC |
vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potentially remote code execution (RCE), exists in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. This issue has been patched in version 0.11.1. Join the discussion | CVE Database V5 | 11/21/2025, 01:18:38 UTC Added: 11/21/2025, 01:44:31 UTC |
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