CVE-2025-33204 is a vulnerability classified under CWE-94 (Improper Control of Generation of Code) found in the NVIDIA NeMo Framework, a toolkit widely used for natural language processing (NLP) and large language model (LLM) development. This vulnerability affects all versions prior to 2.5.1 and allows an attacker to inject malicious code through specially crafted input data processed by the NLP and LLM components. The flaw arises because the framework improperly controls the generation or execution of code based on input data, enabling code injection attacks. Successful exploitation can lead to arbitrary code execution within the context of the NeMo process, escalation of privileges (since the attacker requires at least local privileges), unauthorized disclosure of sensitive information, and tampering with data integrity. The CVSS v3.1 score is 7.8, indicating a high severity with the vector AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H, meaning the attack requires local access and privileges but no user interaction, and impacts confidentiality, integrity, and availability severely. Although no exploits have been reported in the wild yet, the vulnerability's nature and impact make it a critical concern for organizations using NeMo in AI workflows. The vulnerability was reserved in April 2025 and published in November 2025, with no official patches linked yet, but upgrading to version 2.5.1 or later is recommended once available.

For European organizations, the impact of CVE-2025-33204 can be substantial, especially those engaged in AI research, development, and deployment using NVIDIA NeMo. The vulnerability enables attackers with local access to execute arbitrary code, potentially leading to full system compromise within the NeMo environment. This can result in unauthorized access to sensitive AI models, training data, and intellectual property, which are critical assets. Data tampering could undermine the integrity of AI outputs, affecting decision-making processes and automated systems relying on these models. Information disclosure risks threaten privacy compliance under GDPR, as sensitive personal or proprietary data could be exposed. The escalation of privileges further increases the attack surface, potentially allowing attackers to move laterally within networks. Given the increasing adoption of AI technologies in European industries such as automotive, finance, healthcare, and government, the vulnerability could disrupt critical services and damage reputations. The lack of known exploits currently provides a window for proactive mitigation, but the threat remains significant due to the high impact and the widespread use of NVIDIA technologies in Europe.

1. Upgrade to NVIDIA NeMo Framework version 2.5.1 or later as soon as it becomes available, as this version addresses the vulnerability. 2. Restrict access to systems running NeMo to trusted users only, enforcing strict local access controls and minimizing the number of users with local privileges. 3. Implement rigorous input validation and sanitization for all data fed into the NLP and LLM components to prevent malicious code injection attempts. 4. Monitor NeMo environments for unusual or unauthorized code execution behaviors using endpoint detection and response (EDR) tools tailored for AI workloads. 5. Employ network segmentation to isolate AI development and deployment environments from broader enterprise networks to limit lateral movement in case of compromise. 6. Conduct regular security audits and code reviews of AI pipelines to detect potential misuse of input data or suspicious activity. 7. Educate AI developers and operators about secure coding practices and the risks associated with code injection vulnerabilities in AI frameworks. 8. Prepare incident response plans specific to AI infrastructure compromise scenarios to enable rapid containment and recovery.