CVE-2026-24141

CVE-2026-24141 is a high-severity vulnerability with a CVSS 3.x base score of 7.8. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-502.

Key facts

Description

NVIDIA Model Optimizer for Windows and Linux contains a vulnerability in the ONNX quantization feature, where a user could cause unsafe deserialization by providing a specially crafted input file. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, data tampering, and information disclosure.

Frequently asked questions

What is CVE-2026-24141?
NVIDIA Model Optimizer for Windows and Linux contains a vulnerability in the ONNX quantization feature, where a user could cause unsafe deserialization by providing a specially crafted input file. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, data tampering, and information disclosure.
How severe is CVE-2026-24141?
CVE-2026-24141 has a CVSS 3.x base score of 7.8, rated high severity. It is exploitable over local access with low attack complexity, requires no privileges and user interaction. Impact on confidentiality is high, integrity high, and availability high.
Is CVE-2026-24141 being actively exploited?
It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (11th percentile), an estimate of the probability of exploitation in the next 30 days.
How do I fix CVE-2026-24141?
Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its high severity, prioritise patching exposed systems.
Does CVE-2026-24141 have an EU (EUVD) identifier?
Yes. CVE-2026-24141 is tracked in the ENISA EU Vulnerability Database (EUVD) as EUVD-2026-15003.
When was CVE-2026-24141 published?
CVE-2026-24141 was published on 2026-03-24 and last updated on 2026-06-17.

References

Other CWE-502 (Deserialization of Untrusted Data) vulnerabilities

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