What is the CVSS score of CVE-2026-24232?

CVE-2026-24232 has a CVSS 3.1 base score of 4.3 (Medium). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:L. EPSS exploitation probability: 0.1%.

Is there a patch available for CVE-2026-24232?

Yes, a patch is available for CVE-2026-24232. Update the affected software to the latest version immediately.

NVIDIA Transformers4Rec CVE-2026-24232

EUVD-2026-46308 MEDIUM

Deserialization of Untrusted Data (CWE-502)

2026-07-21 nvidia

GHSA-8xrf-7ww8-gcv9

RCE Information Disclosure Deserialization Nvidia Tranformers4Rec

4.3

CVSS 3.1 · Vendor: nvidia

Severity by source

Vendor (nvidia) PRIMARY

4.3 MEDIUM

AV:L/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:L

vuln.today AI

9.3 CRITICAL

CWE-502 deserialization yielding code execution warrants C:H/I:H/A:H; official C:N/I:N is inconsistent with described RCE impact and appears erroneous.

3.1 AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H

4.0 AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (nvidia).

CVSS VectorVendor: nvidia

Attack Vector

Local

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Changed

Confidentiality

None

Integrity

None

Availability

Low

Lifecycle Timeline

Patch available

Jul 21, 2026 - 19:03 EUVD

Analysis Generated

Jul 21, 2026 - 16:46 vuln.today

DescriptionCVE.org

NVIDIA Tranformers4Rec contains a vulnerability where an attacker could cause improper deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering, and information disclosure.

AnalysisAI

Improper deserialization of untrusted data in NVIDIA Transformers4Rec (all versions per CPE wildcard) exposes systems running the library to code execution, data tampering, and information disclosure via a local attack path. The official CVSS vector assigns C:N/I:N/A:L - a score of 4.3 - which is materially inconsistent with the vendor's own description of potential remote code execution and data tampering; this discrepancy warrants independent verification with NVIDIA's product security team. No public exploit code has been identified at time of analysis, and KEV status is not confirmed.

Technical ContextAI

Transformers4Rec is an NVIDIA Merlin library that extends Hugging Face Transformers for sequential and session-based recommendation modeling. CWE-502 (Deserialization of Untrusted Data) describes a class of vulnerability where an application deserializes attacker-controlled data - commonly via Python pickle, PyYAML, or similar mechanisms - without integrity validation, allowing arbitrary object instantiation and code execution at parse time. The affected product is identified as cpe:2.3:a:nvidia:tranformers4rec:*:*:*:*:*:*:*:* (wildcard version), meaning no version is known to be safe. In ML frameworks, deserialization vulnerabilities commonly arise when loading model checkpoints, configuration files, or dataset objects from untrusted sources, since formats like pickle natively support executable callables.

RemediationAI

Consult the NVIDIA product security advisory at https://github.com/NVIDIA/product-security/tree/main/2026/5869 for the official fixed version; no specific patched version number is independently confirmed from the available data, so citing an exact upgrade target is not possible at this time. As a compensating control, restrict the library to deserializing only trusted, internally generated data sources and avoid loading model checkpoints, configuration objects, or dataset artifacts from untrusted or user-controlled paths - this directly addresses the attack surface for CWE-502. If the library is used in a pipeline that ingests external model files, isolate the deserialization step in a sandboxed environment (e.g., a restricted container with no network egress and read-only filesystem mounts) to limit blast radius. Monitoring for anomalous subprocess spawning or outbound connections from ML training processes can provide detection coverage until a patch is applied.