CVE-2026-65111 in NeMo Speech
Summary
by MITRE • 09/22/2026
NVIDIA NeMo Speech for all platforms contains a vulnerability where malicious input created by an attacker could cause a code injection. A successful exploit of this vulnerability might lead to code execution, information disclosure, and data tampering.
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Analysis
by VulDB Data Team • 09/22/2026
The identified security flaw within NVIDIA NeMo Speech represents a critical risk vector associated with the processing of untrusted speech inputs across all supported platforms. This vulnerability stems from an insufficient validation mechanism when handling maliciously crafted audio or text-based input designed to exploit parsing logic errors. The core technical deficiency lies in the application's failure to properly sanitize or escape special characters and control sequences embedded within the processed data stream, allowing an attacker to inject arbitrary commands that are subsequently interpreted by the underlying system components. This lack of rigorous input validation creates a pathway for code injection attacks, where external inputs bypass expected execution boundaries and interact directly with internal functions in unintended ways.
From a technical perspective, this issue aligns closely with CWE-94 Improper Control of Generation of Code or Script, commonly known as code injection. The vulnerability allows an adversary to manipulate the input data such that it is treated not merely as passive content but as executable logic by the NeMo framework's processing engine. When the system processes these malformed inputs, it fails to distinguish between legitimate speech data and malicious payloads, leading to the execution of attacker-supplied instructions within the context of the application process. This behavior mirrors patterns observed in ATT&CK technique T1059 Command and Scripting Interpreter, where adversaries use built-in tools or scripts to execute commands on a target system without deploying additional malware binaries directly.
The operational impact of successfully exploiting this vulnerability is severe and multifaceted. A successful attack could result in remote code execution, granting the attacker full control over the affected host machine depending on the privileges under which the NeMo service operates. Beyond direct execution capabilities, the flaw facilitates information disclosure by allowing attackers to exfiltrate sensitive data processed or stored within the application's memory space. Furthermore, it enables data tampering, where critical datasets used for model training or inference can be altered, compromising the integrity of AI-driven decisions and potentially leading to biased or malicious outputs in downstream applications that rely on NeMo Speech services.
Mitigation strategies must focus on implementing robust input validation and sanitization protocols at multiple layers of the software stack. Developers should enforce strict type checking and length limits for all incoming speech data streams, ensuring that only expected character sets and formats are processed. Utilizing parameterized queries or safe API calls where applicable can prevent injection attempts from being interpreted as executable code. Additionally, deploying runtime application self-protection mechanisms and web application firewalls configured to detect anomalous input patterns can provide an additional layer of defense against exploitation attempts. Regular security audits and penetration testing focused on natural language processing components are essential to identify and remediate similar vulnerabilities before they can be leveraged by malicious actors in production environments.