CVE-2025-33178 is a vulnerability identified in the NVIDIA NeMo Framework, specifically within the bert services component, which is used for natural language processing tasks. The vulnerability is classified under CWE-94, indicating improper control over the generation of code, commonly known as code injection. This flaw allows an attacker who can supply malicious input data to the vulnerable component to inject arbitrary code that the system subsequently executes. The vulnerability affects all versions of the NeMo Framework prior to 2.5.0 across all platforms. The CVSS v3.1 base score of 7.8 reflects a high severity, with an attack vector limited to local access (AV:L), low attack complexity (AC:L), requiring privileges (PR:L), but no user interaction (UI:N). The scope is unchanged (S:U), and the impact on confidentiality, integrity, and availability is high (C:H/I:H/A:H). Exploiting this vulnerability could allow attackers to execute arbitrary code, escalate privileges beyond their current level, disclose sensitive information, and tamper with data. Although no exploits have been reported in the wild, the vulnerability poses a significant risk in environments where the NeMo Framework is used, particularly in AI and machine learning development settings. The lack of available patches at the time of disclosure necessitates immediate risk mitigation strategies. The vulnerability was reserved in April 2025 and published in November 2025, indicating a recent discovery and disclosure timeline.

For European organizations, the impact of CVE-2025-33178 can be substantial, especially those engaged in AI research, development, and deployment using the NVIDIA NeMo Framework. Successful exploitation could lead to unauthorized code execution on critical systems, potentially compromising intellectual property, sensitive research data, and operational integrity. The ability to escalate privileges may allow attackers to gain broader access within affected networks, increasing the risk of lateral movement and further compromise. Information disclosure could expose confidential data, including proprietary AI models and datasets, while data tampering could undermine the integrity of AI outputs and decision-making processes. Given the high confidentiality, integrity, and availability impacts, organizations may face operational disruptions, reputational damage, and regulatory consequences under GDPR if personal data is involved. The local attack vector and requirement for some privileges limit remote exploitation but do not eliminate risk in environments where multiple users or processes interact with the NeMo Framework. This vulnerability is particularly critical in shared or multi-tenant environments, research labs, and cloud platforms hosting AI workloads.

1. Immediately restrict access to systems running vulnerable versions of the NVIDIA NeMo Framework, ensuring only trusted users have local access. 2. Implement strict privilege management to minimize the number of users with local privileges capable of exploiting this vulnerability. 3. Monitor logs and system behavior for unusual or unauthorized code execution attempts within the bert services component. 4. Employ application whitelisting and runtime application self-protection (RASP) tools to detect and block unauthorized code injection attempts. 5. Isolate AI development environments to contain potential breaches and prevent lateral movement. 6. Once NVIDIA releases patches or updates (version 2.5.0 or later), prioritize their deployment across all affected systems. 7. Conduct security awareness training for developers and system administrators about the risks of code injection vulnerabilities and safe handling of input data. 8. Review and harden configurations of the NeMo Framework and related components to reduce attack surface. 9. Consider implementing endpoint detection and response (EDR) solutions capable of identifying exploitation attempts targeting local privilege escalation and code injection.