What is the CVSS score of CVE-2026-31218?

CVE-2026-31218 has a CVSS 3.1 base score of 8.8 (High). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H. EPSS exploitation probability: 0.1%.

Which versions of Optimate are affected by CVE-2026-31218?

CVE-2026-31218 in Optimate allows authenticated users to execute arbitrary code by uploading malicious PyTorch model files, creating insider risk and supply chain vulnerabilities in machine learning…

How to fix or mitigate CVE-2026-31218?

Within 24 hours: Disable or restrict model file upload functionality in Optimate to authorized personnel only; audit access logs for any model uploads in the past 90 days. Within 7 days: Implement network segmentation isolating Optimate instances from critical systems; require code review of all external model sources before loading. Within 30 days: Monitor vendor advisories for Optimate patch availability; evaluate migration to alternative ML training frameworks with native security-first deserialization (e.g., PyTorch 2.x with weights_only=True enforced by default).

Optimate CVE-2026-31218

EUVD-2026-29502 HIGH

Deserialization of Untrusted Data (CWE-502)

2026-05-12 mitre

GHSA-q2mf-qjjq-ghcc

Python RCE Deserialization N A

8.8

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

8.8 HIGH

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

High

Lifecycle Timeline

Analysis Generated

May 15, 2026 - 15:22 vuln.today

CVSS changed

May 15, 2026 - 15:22 NVD

8.8 (None) 8.8 (HIGH)

CVE Published

May 12, 2026 - 00:00 nvd

UNKNOWN (no severity yet)

DescriptionCVE.org

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When loading a model state dictionary from a state_dict.pt file via torch.load(), the function does not enable the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted state_dict.pt file within a directory specified via the --model argument, leading to arbitrary code execution during the deserialization process on the victim's system.

AnalysisAI

Remote code execution in Optimate's neural_magic_training.py script allows authenticated attackers to execute arbitrary code via malicious PyTorch model files. The vulnerability stems from unsafe deserialization when loading model state dictionaries without PyTorch's weights_only=True security flag, enabling pickle-based arbitrary object execution. With an EPSS score of 0.06% and no confirmed exploitation, this represents a moderate risk primarily in environments where users can upload or specify model files.

Technical ContextAI

The vulnerability exists in Optimate, a neural network optimization tool, specifically in the _load_model() function that processes PyTorch model files. PyTorch's torch.load() function uses Python's pickle serialization by default, which can deserialize arbitrary Python objects including those that execute code upon instantiation. The CWE-502 classification indicates this is a classic insecure deserialization vulnerability where untrusted data is processed without proper validation or sandboxing.

RemediationAI

No vendor-released patch identified at time of analysis. The primary mitigation is to modify the torch.load() call in _load_model() to include weights_only=True parameter, which restricts deserialization to tensor data only. As an immediate workaround, restrict access to the --model argument to trusted users only and validate that model directories come from trusted sources. Consider implementing input validation to ensure state_dict.pt files originate from known-good locations. Advisory details available at https://www.notion.so/CVE-2026-31218-35d1e139318881839bc8cf6007be2c76.