CVE-2025-33243 in NeMo Framework
Summary
by MITRE • 02/18/2026
NVIDIA NeMo Framework contains a vulnerability where an attacker could cause remote code execution in distributed environments. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and data tampering.
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Analysis
by VulDB Data Team • 02/18/2026
The vulnerability identified as CVE-2025-33243 resides within the NVIDIA NeMo Framework, a comprehensive toolkit designed for developing and deploying large language models and speech processing applications. This framework operates in distributed computing environments where multiple nodes communicate and coordinate to execute machine learning workloads. The flaw manifests as a remote code execution vulnerability that specifically impacts distributed deployments, making it particularly concerning for enterprise environments where such frameworks are commonly deployed across clusters of servers. The vulnerability's presence in a widely-used machine learning framework means that organizations relying on NVIDIA's ecosystem for AI workloads face significant risk when operating in distributed configurations.
The technical implementation of this vulnerability stems from inadequate input validation and sanitization mechanisms within the framework's distributed communication protocols. When the NeMo Framework processes requests or data from remote nodes in a distributed setup, it fails to properly validate or sanitize certain parameters that are passed between components. This allows an attacker positioned outside the network to craft malicious inputs that can be executed within the context of the framework's running processes. The vulnerability is particularly dangerous because it leverages the legitimate communication channels that are necessary for distributed operations, making it difficult to detect through traditional network monitoring approaches. Attackers can exploit this weakness by sending specially crafted payloads through the framework's inter-node communication mechanisms, potentially gaining unauthorized access to the underlying system resources.
The operational impact of CVE-2025-33243 extends far beyond simple code execution capabilities, presenting a comprehensive threat landscape for affected organizations. Successful exploitation could enable attackers to escalate privileges to the highest levels of system access, potentially compromising entire distributed clusters. The vulnerability's ability to facilitate information disclosure means that sensitive training data, model parameters, and system configurations could be exfiltrated from the environment. Data tampering capabilities further compound the risk, allowing attackers to modify model outputs or corrupt training datasets, potentially leading to degraded AI performance or malicious behavior in deployed systems. Organizations utilizing the NeMo Framework in production environments face the risk of complete system compromise, particularly when the framework is deployed across multiple nodes without proper isolation measures.
Mitigation strategies for this vulnerability should focus on implementing multiple layers of defense to protect against exploitation attempts. Network segmentation and access control measures should be strengthened to limit communication between nodes within the distributed framework, reducing the attack surface available to potential adversaries. Regular updates and patches should be prioritized, with organizations monitoring NVIDIA's security advisories for remediation guidance. The implementation of network intrusion detection systems with signature-based detection for known exploit patterns can provide early warning capabilities. Additionally, organizations should consider implementing application-level firewalls and input validation mechanisms that can intercept and block malicious payloads before they reach the framework's core components. Compliance with industry standards such as those outlined in CWE-77 and ATT&CK techniques T1059.007 for remote code execution should be considered when developing defensive strategies, ensuring that mitigation efforts align with established security frameworks and best practices.