CVE-2026-56340
CVE-2026-56340: 1 tracked advisory record across Red Hat. Compare vendor sources and published fix guidance.
Compare the source-linked records below. Ratings and product/version details belong to each advisory; they are not a single CVE-wide score or proof that every listed product is affected. How VulniPulse collects and checks evidence.
Vendor advisory comparison
Red Hat
1 advisory- Advisory severityHigh8.8
High [CVE-2026-56340] Denial of service and potential arbitrary code execution via malformed multimodal embedding requests
CVE-2026-56340Source published Source updated
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. A flaw was found in vLLM. Red Hat rates this issue as having Important impact for affected Red Hat AI Inference Server images shipping vLLM 0.10.2 through 0.13.x when prompt-embeds multimodal embedding support is…
- Affected products in this advisory
- Red Hat AI Inference Server
- Source-reported affected versions
- Affected-version details not available in this record.
- Source-reported fixed versions
- No fixed-version detail extracted. This does not mean no fix exists.
- Mitigation guidance
- Disable prompt-embeds if not required. Restrict who can submit multimodal embedding requests. Apply authentication and rate limits on inference APIs. Upgrade to a fixed vLLM build when available from Red Hat.
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