CVE-2025-33178 in NeMo Framework
Summary
by MITRE • 11/11/2025
NVIDIA NeMo Framework for all platforms contains a vulnerability in the bert services component where malicious data created by an attacker may cause a code injection. A successful exploit of this vulnerability may lead to Code execution, Escalation of privileges, Information disclosure, and Data tampering.
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Analysis
by VulDB Data Team • 11/11/2025
The vulnerability identified as CVE-2025-33178 resides within the NVIDIA NeMo Framework's bert services component, representing a critical security flaw that enables attackers to manipulate the system through crafted malicious data inputs. This framework serves as a comprehensive platform for developing and deploying natural language processing models, with the bert services component specifically handling transformer-based language model operations. The vulnerability stems from insufficient input validation and sanitization mechanisms within the service handling pipeline, creating a pathway for attackers to inject malicious code that can be executed within the framework's operational environment. The affected component processes user inputs through various API endpoints and internal service calls, where the lack of proper data filtering allows attackers to craft inputs that bypass normal validation checks and execute arbitrary commands.
The technical implementation of this vulnerability aligns with CWE-94, which describes improper control of generation of code, and CWE-79, which addresses improper neutralization of input during web output. The flaw manifests when the bert services component receives user-provided data through API interfaces or internal processing workflows without adequate sanitization of special characters, escape sequences, or command injection patterns. Attackers can leverage this weakness by crafting inputs containing malicious payloads that exploit the framework's parsing mechanisms, potentially triggering code execution in the context of the running service. The vulnerability's impact extends beyond simple code injection as it can be leveraged for privilege escalation, allowing attackers to gain elevated system access that may not be available through normal user operations. The exploitation chain typically involves crafting specific input patterns that can bypass existing security controls and trigger the execution of attacker-controlled code within the framework's execution environment.
The operational implications of this vulnerability are severe and multifaceted, affecting organizations that rely on NVIDIA NeMo Framework for their artificial intelligence and machine learning workloads. Successful exploitation can result in complete system compromise, enabling attackers to execute arbitrary code with the privileges of the framework service account, which may have elevated access to system resources and data. The vulnerability can be exploited for information disclosure, allowing attackers to extract sensitive data, model parameters, or training datasets that could contain proprietary information or confidential business data. Data tampering capabilities provide attackers with the means to modify training data, corrupt model outputs, or manipulate system behavior in ways that could compromise the integrity of AI applications. The impact is particularly concerning given that NeMo Framework is used across various industries including healthcare, finance, and technology sectors where AI model integrity and data security are paramount.
Mitigation strategies for CVE-2025-33178 should focus on implementing comprehensive input validation and sanitization measures within the bert services component. Organizations should deploy strict data validation protocols that filter and sanitize all user inputs before processing, implementing proper escape sequence handling and command injection prevention mechanisms. The framework should be updated to include robust input sanitization routines that can detect and neutralize malicious patterns before they reach the core processing logic. Network segmentation and access controls should be implemented to limit exposure of the affected services, while monitoring systems should be deployed to detect anomalous behavior patterns that may indicate exploitation attempts. Security patches should be applied immediately upon availability, and organizations should consider implementing runtime application self-protection measures that can detect and prevent code injection attempts. Additionally, regular security assessments and penetration testing should be conducted to identify potential attack vectors and ensure that the implemented mitigations remain effective against evolving threat landscapes. The vulnerability's classification as a high-severity issue places it within the ATT&CK framework's code injection techniques, specifically targeting the execution phase of the attack lifecycle where adversaries seek to run malicious code within the target environment.