Cyber Resilience

CVE-2026-24228

High

Published: 16 June 2026

Published
16 June 2026
Modified
16 June 2026
KEV Added
Patch
CVSS Score v3.1 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS Score 0.0016 5.7th percentile
Risk Priority 16 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2026-24228 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Nvidia Nemo. Its CVSS base score is 7.8 (High).

Operationally, ranked at the 5.7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

NVIDIA NeMo Framework for Linux contains a vulnerability where an attacker may cause deserialization of untrusted data. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, data tampering, and information disclosure.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

nvidia
nemo
≤ 2.7.3

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-502

Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.

addresses: CWE-502

Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.

addresses: CWE-502

Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.

addresses: CWE-502

Validates or rejects untrusted serialized data before deserialization occurs.

addresses: CWE-502

Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.

addresses: CWE-502

Integrity verification of serialized information can detect tampering before deserialization occurs.

addresses: CWE-502

Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.

References