CVE-2025-33249 in NeMo Framework
Summary
by MITRE • 02/18/2026
NVIDIA NeMo Framework for all platforms contains a vulnerability in a voice-preprocessing script, where malicious input created by an attacker could cause a code injection. 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-2025-33249 resides within the NVIDIA NeMo Framework, a comprehensive toolkit designed for developing and deploying speech processing applications across multiple platforms. This framework serves as a critical component in artificial intelligence and machine learning workflows specifically focused on voice and speech recognition tasks. The vulnerability manifests in a voice-preprocessing script that handles audio data transformation and feature extraction processes essential for subsequent neural network training and inference operations. The affected component represents a core functionality within the framework's data pipeline, making it a prime target for exploitation given its central role in processing user-provided audio inputs.
The technical flaw stems from insufficient input validation and sanitization within the voice-preprocessing script, creating a code injection vulnerability that allows attackers to inject malicious code through crafted audio files or processing parameters. This weakness operates at the intersection of improper input validation and code execution mechanisms, aligning with CWE-74 and CWE-94 classifications that address injection flaws and code injection vulnerabilities respectively. The vulnerability does not require elevated privileges to exploit, as the preprocessing script typically operates with standard user permissions, making it particularly dangerous in environments where audio files are processed automatically or in batch modes. Attackers can leverage this vulnerability by crafting specially formatted audio data or metadata that bypasses normal validation checks and executes unintended commands within the processing context.
The operational impact of this vulnerability extends beyond simple code execution, creating a comprehensive threat vector that can lead to privilege escalation, information disclosure, and data tampering within systems utilizing the NeMo Framework. When successfully exploited, an attacker could gain unauthorized access to sensitive system resources, potentially compromising the entire machine or network segment where the framework is deployed. The vulnerability affects all platforms supported by NVIDIA NeMo Framework, indicating a widespread exposure across different operating systems and hardware architectures, including desktop environments, cloud platforms, and edge computing deployments. This broad platform compatibility increases the attack surface significantly, as organizations using the framework across diverse computing environments face identical risk profiles regardless of their specific deployment targets.
Mitigation strategies for CVE-2025-33249 should prioritize immediate patch application from NVIDIA, as the vulnerability represents a critical security flaw that requires vendor-level remediation. Organizations should implement strict input validation measures at network boundaries and application interfaces to prevent malicious audio files from reaching the vulnerable preprocessing scripts. Network segmentation and privilege separation techniques can limit the potential impact of successful exploitation by restricting access to sensitive system resources. Additionally, implementing runtime monitoring and anomaly detection systems can help identify suspicious processing patterns that may indicate exploitation attempts. Security teams should conduct comprehensive vulnerability assessments across all systems utilizing the NeMo Framework, particularly focusing on automated processing pipelines where the vulnerability could be exploited without human intervention. The ATT&CK framework classification for this vulnerability would likely map to T1059.007 for command and scripting interpreter and T1566 for credential access, reflecting the exploitation techniques and post-exploitation capabilities associated with code injection vulnerabilities in AI/ML processing frameworks.