CVE-2025-23314 in NeMo Framework
Summary
by MITRE • 08/26/2025
NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. 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 • 08/29/2025
The vulnerability identified as CVE-2025-23314 resides within the NVIDIA NeMo Framework's natural language processing component, representing a critical security flaw that affects all supported platforms. This framework serves as a comprehensive toolkit for developing and deploying large language models and other NLP applications, making it a prime target for attackers seeking to compromise AI-powered systems. The vulnerability stems from insufficient input validation mechanisms within the NLP processing pipeline, where the framework fails to properly sanitize or validate data inputs that originate from external sources or user interactions.
The technical nature of this flaw manifests as a code injection vulnerability that operates through the NLP component's data processing workflows. When maliciously crafted data is fed into the framework's NLP processing modules, the insufficient sanitization allows attacker-controlled code to be executed within the framework's runtime environment. This vulnerability aligns with CWE-94, which describes weaknesses in code injection attacks, and represents a direct threat to the integrity and confidentiality of systems utilizing the NeMo Framework. The attack vector typically involves sending specially crafted text inputs, embeddings, or other NLP data structures that bypass the framework's normal validation procedures and instead trigger unintended code execution paths within the underlying processing engine.
The operational impact of this vulnerability extends far beyond simple code execution, creating a comprehensive attack surface that enables multiple malicious activities. Successful exploitation could lead to privilege escalation, allowing attackers to gain elevated system access and potentially compromise the entire underlying infrastructure. The vulnerability also facilitates information disclosure, where attackers could extract sensitive data from the framework's memory or processing states, and enables data tampering operations that could corrupt model outputs or manipulate training data. This makes the vulnerability particularly dangerous in enterprise environments where the NeMo Framework might be used for sensitive applications such as financial analysis, healthcare data processing, or security monitoring systems.
Mitigation strategies for CVE-2025-23314 should prioritize immediate patching of affected systems with the latest NVIDIA security updates, while implementing additional defensive measures to reduce the attack surface. Organizations should deploy input validation layers at multiple points within their NLP processing pipelines to prevent malicious data from reaching the core framework components. Network segmentation and access controls should be implemented to limit exposure of systems running the NeMo Framework, particularly in production environments where the framework processes sensitive data. The vulnerability's characteristics align with ATT&CK technique T1059, which covers command and script injection, and organizations should consider implementing behavioral monitoring to detect anomalous code execution patterns. Regular security assessments of NLP pipelines and comprehensive testing of input sanitization mechanisms should be conducted to ensure that similar vulnerabilities are not present in other components of the framework or related systems.