CVE-2026-54235
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.
Executive briefing
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Evidence confidence: Not assessed Evidence-derived, not an exploitability verdict
Severity & attack characteristics
CVSS vector:Not supplied
No CVSS vector is currently available in the source record.
Technical explanation & impact
Technical root-cause details are not available in the current source record.
Assess the impact using the published CVSS metrics and the affected vendor component.
Affected products and versions
NVD has not supplied machine-readable vulnerable CPE product/version entries for this CVE. This is an information gap, not proof that no products are affected. Check the vendor advisory references below.
Remediation & validation
- Identify exposure by comparing the affected product and version ranges with your asset inventory, SBOM and externally exposed services.
- Review the linked vendor security advisory or patch notes. Upgrade to a vendor-confirmed fixed release; do not infer a fixed version from the CVE description.
- Until patched, consider restricting network access or disabling the affected feature where operationally safe. These are temporary controls, not a substitute for a vendor fix.
- Validate the remediation with a version check and vulnerability rescan, then retain change evidence.
No fixed version is displayed unless it is explicitly established by a vendor advisory. Follow the vendor's release notes for exact product and branch applicability.
Vendor advisories, patches & exploit references
No external references are currently supplied in the CVE record.