Cyber Resilience

CVE-2025-33253

High

Published: 18 February 2026

Published
18 February 2026
Modified
20 February 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 0.0010 27.7th percentile
Risk Priority 16 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2025-33253 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Nvidia Nemo. Its CVSS base score is 7.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 27.7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified are NIST 800-53 SI-10 (Information Input Validation) and SI-2 (Flaw Remediation).

Deeper analysis

CVE-2025-33253 is a vulnerability in the NVIDIA NeMo Framework, stemming from CWE-502 (Deserialization of Untrusted Data). It allows an attacker to potentially achieve remote code execution by convincing a user to load a maliciously crafted file. The issue carries a CVSS v3.1 base score of 7.8 (High), with vector AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H, indicating high impacts on confidentiality, integrity, and availability.

An attacker with local access and low privileges can exploit this vulnerability after tricking a user into loading the malicious file, leading to arbitrary code execution, denial of service, information disclosure, or data tampering. The low attack complexity and lack of required user interaction beyond the initial file load make it feasible for targeted exploitation in environments using the affected framework.

For mitigation details, security practitioners should consult official advisories, including the NVIDIA security bulletin at https://nvidia.custhelp.com/app/answers/detail/a_id/5762, the NVD entry at https://nvd.nist.gov/vuln/detail/CVE-2025-33253, and the CVE record at https://www.cve.org/CVERecord?id=CVE-2025-33253, which provide patch information and workarounds.

As part of NVIDIA's NeMo Framework for developing generative AI models, this vulnerability holds relevance for AI/ML practitioners securing training and inference pipelines against deserialization attacks. No public evidence of real-world exploitation has been reported.

EU & UK References

Vulnerability details

NVIDIA NeMo Framework contains a vulnerability where an attacker could cause remote code execution by convincing a user to load a maliciously crafted file. A successful exploit of this vulnerability might lead to code execution, denial of service, information disclosure,…

more

and data tampering.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1203 Exploitation for Client Execution Execution
Adversaries may exploit software vulnerabilities in client applications to execute code.
T1204.002 Malicious File Execution
An adversary may rely upon a user opening a malicious file in order to gain execution.
Why these techniques?

Deserialization of untrusted data in a crafted file directly enables client-side code execution (T1203) after a user loads the malicious file (T1204.002).

Confidence: HIGH · MITRE ATT&CK Enterprise v18.1

CVEs Like This One

CVE-2025-33252Same product: Nvidia Nemo
CVE-2025-33241Same product: Nvidia Nemo
CVE-2025-33245Same product: Nvidia Nemo
CVE-2026-24159Same product: Nvidia Nemo
CVE-2025-33243Same product: Nvidia Nemo
CVE-2026-24157Same product: Nvidia Nemo
CVE-2025-33250Same product: Nvidia Nemo
CVE-2026-24151Same vendor: Nvidia
CVE-2025-33251Same product: Nvidia Nemo
CVE-2025-33236Same product: Nvidia Nemo

Affected Assets

nvidia
nemo
≤ 2.6.1

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

prevent

Applying vendor-provided patches for the deserialization flaw in NVIDIA NeMo Framework directly prevents exploitation by maliciously crafted files.

prevent

Validating the content and structure of files before deserialization in the framework blocks processing of untrusted data leading to RCE.

preventdetect

Verifying the integrity of framework components and loaded files using cryptographic mechanisms detects and prevents tampering or malicious deserialization payloads.

References