CVE-2025-23315 in NeMo Framework
Summary
by MITRE • 08/26/2025
NVIDIA NeMo Framework for all platforms contains a vulnerability in the export and deploy 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-2025-23315 resides within the NVIDIA NeMo Framework's export and deploy component, representing a critical security flaw that undermines the integrity of machine learning model deployment processes. This framework serves as a comprehensive toolkit for developing and deploying natural language processing models, making its security implications particularly severe given the widespread adoption across research institutions and enterprise environments. The vulnerability manifests when the framework processes maliciously crafted data during the export and deployment phases, creating a pathway for attackers to inject arbitrary code into the system.
The technical nature of this flaw stems from insufficient input validation and sanitization within the framework's deployment pipeline. When users attempt to export or deploy models, the system fails to properly validate the integrity of the input data, allowing attackers to craft malicious payloads that bypass normal security controls. This vulnerability aligns with CWE-94, which describes "Improper Control of Generation of Code ('Code Injection')" and represents a classic code injection vector that can be exploited through malformed data inputs. The weakness specifically impacts the framework's serialization and deserialization processes where model configurations and metadata are handled during deployment operations.
The operational impact of CVE-2025-23315 extends beyond simple code execution capabilities, presenting attackers with a comprehensive attack surface that includes privilege escalation, information disclosure, and data tampering. An attacker who successfully exploits this vulnerability could gain elevated privileges within the deployment environment, potentially accessing sensitive model artifacts, training data, or deployment credentials. The framework's role in handling sensitive AI models makes it particularly attractive to adversaries seeking to compromise intellectual property or manipulate deployed systems. Additionally, the vulnerability could enable data tampering operations where attackers modify model behavior or inject backdoors into deployed systems, creating persistent threats that could remain undetected for extended periods.
Security professionals should implement multiple layers of mitigation strategies to address this vulnerability effectively. Immediate remediation efforts should focus on updating to the latest version of the NVIDIA NeMo Framework where the vulnerability has been patched. Organizations should also establish strict input validation controls and implement automated scanning of deployment artifacts to detect potentially malicious code injections. The vulnerability's characteristics align with ATT&CK technique T1059.001, which covers "Command and Scripting Interpreter: PowerShell", suggesting that attackers may leverage PowerShell or similar scripting mechanisms to execute injected code. Network segmentation and principle of least privilege access controls should be enforced to limit the potential impact of successful exploitation, while regular security assessments of AI deployment pipelines should be conducted to identify similar vulnerabilities in other components of the machine learning infrastructure stack.