CVE-2026-24252 in NeMo Framework
Summary
by MITRE • 07/27/2026
NVIDIA NeMo for Linux contains a vulnerability where an attacker may cause OS command injection. A successful exploit of this vulnerability may lead to code execution, data tampering, escalation of privileges and information disclosure.
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Analysis
by VulDB Data Team • 07/27/2026
The vulnerability in NVIDIA NeMo for Linux represents a critical command injection flaw that fundamentally undermines the security posture of systems utilizing this machine learning framework. This vulnerability exists within the software's handling of user-supplied input that is subsequently executed as operating system commands without proper sanitization or validation. The flaw creates an attack vector where malicious actors can inject arbitrary commands that execute with the privileges of the affected application, potentially compromising the entire underlying system.
The technical nature of this vulnerability aligns with common weakness enumerations such as CWE-78 and CWE-88, which specifically address improper neutralization of special elements used in OS commands and command injection respectively. These weaknesses fall under the broader category of software vulnerabilities that enable attackers to execute unintended code sequences on target systems. The operational impact extends beyond simple code execution to encompass privilege escalation capabilities, as the injected commands may leverage elevated permissions granted to the NeMo application process. This creates a pathway for adversaries to manipulate system configurations, access sensitive data stores, and potentially establish persistent backdoors within the compromised environment.
From an attack framework perspective, this vulnerability maps directly to multiple tactics and techniques outlined in the ATT&CK methodology including privilege escalation through command injection, execution via valid accounts, and defense evasion by leveraging legitimate system tools. The exploitability of this flaw means that an attacker with access to the NeMo application interface or any input mechanism that feeds into command execution can craft malicious payloads that execute arbitrary code on the target system. The implications for information disclosure are particularly severe as attackers could potentially access configuration files, training data, or other sensitive information processed by the NeMo framework.
The operational impact of this vulnerability extends to organizations deploying NVIDIA NeMo in production environments where it may be exposed to untrusted input sources or where administrative privileges are not properly segregated. Organizations utilizing this framework for machine learning workflows that process external data inputs face significant risk if proper input validation controls are not implemented. The vulnerability creates a persistent threat vector that remains active until mitigations are applied, potentially allowing attackers to maintain access and continue exfiltrating information over extended periods.
Recommended mitigation strategies include implementing comprehensive input sanitization measures that validate and escape all user-supplied data before it is processed by the application. Organizations should deploy proper privilege separation techniques ensuring that the NeMo application operates with minimal required privileges rather than elevated system permissions. Network segmentation and access controls should limit exposure of the NeMo framework to trusted networks only, while regular security assessments and penetration testing should verify that no other injection vectors exist within the broader application ecosystem. Additionally, implementing runtime monitoring solutions can help detect anomalous command execution patterns that may indicate exploitation attempts against this vulnerability.