CVE-2025-23304 is a high-severity vulnerability identified in the NVIDIA NeMo Framework, a library widely used for building and deploying AI models across multiple platforms. The vulnerability stems from improper limitation of a pathname to a restricted directory (CWE-22), specifically in the model loading component of the framework. An attacker can exploit this flaw by crafting malicious .nemo files containing specially designed metadata. When these files are loaded by the vulnerable versions of the NeMo Framework (all versions prior to 2.3.2), the attacker can trigger code injection, leading to remote code execution (RCE) and potential data tampering. The CVSS 3.1 score of 7.8 reflects the high impact of this vulnerability, with an attack vector requiring local access (AV:L), low attack complexity (AC:L), and low privileges (PR:L), but no user interaction (UI:N). The vulnerability affects confidentiality, integrity, and availability (all rated high), making it a critical concern for organizations relying on NVIDIA NeMo for AI model development or deployment. Although no known exploits are currently reported in the wild, the potential for exploitation is significant given the nature of the flaw and the widespread use of the framework in AI workflows. The lack of available patches at the time of publication further increases the urgency for mitigation and risk management.

For European organizations, the impact of CVE-2025-23304 can be substantial, especially those involved in AI research, development, and deployment using the NVIDIA NeMo Framework. Successful exploitation could allow attackers to execute arbitrary code remotely, leading to unauthorized access to sensitive AI models, manipulation of model outputs, or disruption of AI-driven services. This could compromise intellectual property, degrade service reliability, and result in data breaches affecting personal data protected under GDPR. Industries such as automotive (autonomous driving AI), healthcare (medical imaging AI), finance (fraud detection AI), and manufacturing (predictive maintenance AI) are particularly at risk due to their reliance on AI models. The vulnerability’s local attack vector implies that attackers need some level of access to the environment where NeMo is deployed, which could be achieved through insider threats, compromised developer machines, or lateral movement after initial network intrusion. The high impact on confidentiality, integrity, and availability means that exploitation could lead to severe operational disruptions and regulatory consequences for European entities.

European organizations should implement a multi-layered mitigation approach: 1) Immediate upgrade to NVIDIA NeMo Framework version 2.3.2 or later once available, as this will contain the official patch addressing the vulnerability. 2) Restrict access to systems running NeMo to trusted personnel only, enforcing strict access controls and monitoring for suspicious activity to reduce the risk of local exploitation. 3) Implement file integrity monitoring and validation mechanisms to detect and block loading of untrusted or suspicious .nemo files, including scanning metadata for anomalies. 4) Employ network segmentation to isolate AI development and deployment environments from broader corporate networks, limiting lateral movement opportunities. 5) Conduct thorough code reviews and security assessments of AI model pipelines to identify and remediate potential injection vectors. 6) Enhance endpoint security controls on developer and deployment machines, including application whitelisting and behavior-based detection to prevent execution of unauthorized code. 7) Prepare incident response plans specifically addressing AI framework compromise scenarios, ensuring rapid containment and recovery. These targeted actions go beyond generic advice by focusing on the unique aspects of the NeMo Framework and AI model handling.