REDHAT-BUG-2491060: High severity vllm vulnerability
vLLM versions >= 0.10.2 and < 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed (negative or out-of-bounds) tensor indices, when the prompt-embeds feature is enabled, to trigger crashes or resource exhaustion (denial of service), with potential for out-of-bounds/write-what-where memory corruption. This continues CVE-2025-62164, whose prior fix only disabled the feature by default rather than addressing the root cause.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
vLLMto a version that resolves this vulnerability.Fixed in 0.13.0 - Upgrade
Upgrade
vLLMto a version that resolves this vulnerability.Fixed in 0.10.2
Event History
Frequently Asked Questions
What is the severity of REDHAT-BUG-2491060?
The severity of REDHAT-BUG-2491060 is classified as high with a score of 7.
What vulnerability does REDHAT-BUG-2491060 address?
REDHAT-BUG-2491060 addresses the lack of sparse tensor validation in multimodal embeddings processing in certain versions of vLLM.
How do I fix REDHAT-BUG-2491060?
To fix REDHAT-BUG-2491060, upgrade vLLM to a version greater than or equal to 0.13.0.
What are the affected versions in REDHAT-BUG-2491060?
The affected versions in REDHAT-BUG-2491060 are vLLM versions greater than or equal to 0.10.2 and less than 0.13.0.
What potential impact does REDHAT-BUG-2491060 have on systems?
The impact of REDHAT-BUG-2491060 allows an attacker to submit crafted embedding requests with malformed tensor indices, potentially leading to denial of service or other exploitation.