CVE-2026-108944
Received Received - Intake

Code Injection in RAE Config-Driven Model Instantiation

Publication date: 2026-10-13

Last updated on: 2026-10-13

Assigner: VulDB

Description
A security vulnerability has been detected in repository RAE up to a4d18c4db766419cbe7cb8c02cd9f7ceb0ec9041. Affected by this vulnerability is the function get_obj_from_str of the file src/utils/model_utils.py of the component Config-Driven Model Instantiation. Such manipulation of the argument Target leads to code injection. The attack must be carried out locally. This product utilizes a rolling release system for continuous delivery, and as such, version information for affected or updated releases is not disclosed. The project was informed of the problem early through an issue report but has not responded yet.

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Meta Information

Published
2026-10-13
Last Modified
2026-10-13
Generated
2026-10-13
AI Q&A
2026-10-13
EPSS Evaluated
N/A
NVD
CVE-2026-108944
EUVD
EUVD-2026-98203

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
repository RAE a4d18c4db766419cbe7cb8c02cd9f7ceb0ec9041

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-94 The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
CWE-74 The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component.

Attack-Flow Graph

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Executive Summary

This vulnerability is a code injection flaw in the RAE repository where YAML configuration files can be manipulated to execute arbitrary Python code. The issue occurs in the function get_obj_from_str in src/utils/model_utils.py, which dynamically imports and instantiates Python objects based on the Target argument in YAML configs without validation. Attackers can specify malicious module paths or parameters, leading to arbitrary code execution with the same privileges as the running process.

Detection Guidance

Check for suspicious YAML configuration files in directories used by RAE, particularly those with arbitrary module paths in the target field. Inspect logs for unexpected Python module imports or code execution events during config loading.

Impact Analysis

If you use RAE repository versions up to a4d18c4db766419cbe7cb8c02cd9f7ceb0ec9041, an attacker with local access could craft a malicious YAML config file. When loaded via any of the nine entry points accepting a --config path (e.g., training or sampling scripts), the system would execute arbitrary Python code without user confirmation. This could lead to data theft, system compromise, or further network infiltration depending on the privileges of the running process.

Compliance Impact

This vulnerability could lead to unauthorized code execution, potentially causing data breaches or unauthorized access to sensitive information. For GDPR, this may result in violations of data confidentiality and integrity requirements. For HIPAA, it could compromise protected health information integrity and confidentiality. Organizations using affected versions may face compliance violations, legal liabilities, and reputational damage if exploited.

Mitigation Strategies

Immediately stop using YAML configs from untrusted sources. Implement an allowlist for target fields in YAML configs. Update to a patched version if available. Use torch.load with weights_only=True for checkpoint loading.

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