CVE-2026-24239 in NeMo Speech
Summary
by MITRE • 09/22/2026
NVIDIA NeMo Speech for all platforms contains a vulnerability where malicious data created by an attacker could cause remote code execution. 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 vulnerability within NVIDIA NeMo Speech represents a critical security flaw that allows attackers to achieve remote code execution through the ingestion of maliciously crafted input data. This issue stems from insufficient validation or sanitization mechanisms when processing speech-related inputs, which are central to the functionality of the NeMo framework across all supported platforms. The architecture of modern AI and machine learning systems often involves complex parsing logic for various media formats, including audio files and streaming data streams. When these parsers fail to properly bound-check memory operations or validate structural integrity before execution, they create an entry point for exploitation. An attacker who can deliver specially constructed speech data to a vulnerable instance of NVIDIA NeMo Speech can trigger this flaw, bypassing standard security controls that typically protect against unauthorized access.
The operational impact of successfully exploiting this vulnerability is severe and multifaceted. The primary consequence is remote code execution, which grants the adversary full control over the affected system or service running the compromised component. This level of access allows for complete compromise of the underlying operating environment. Beyond direct command execution, the vulnerability facilitates information disclosure, enabling attackers to exfiltrate sensitive data stored on the target machine, such as proprietary models, user credentials, or confidential speech recordings processed by the application. Furthermore, the ability to tamper with data introduces risks related to integrity violations, where an attacker could alter training datasets or inference results, potentially leading to model poisoning or skewed decision-making in downstream applications that rely on accurate speech processing outputs.
From a classification perspective, this vulnerability aligns with common weakness enumerations associated with improper input validation and buffer handling errors. It is consistent with CWE-20 Improper Input Validation and potentially CWE-119 Buffer Overflow if the exploit involves writing beyond allocated memory boundaries. In terms of tactical mapping within the MITRE ATT&CK framework, this scenario corresponds to techniques involving Initial Access via Spearphishing Attachment or Valid Accounts, followed by Execution through Command and Scripting Interpreter components embedded in the application logic. The attack vector leverages the trust placed in input data streams, highlighting a common pitfall in software development where convenience of integration outweighs rigorous security testing during the parsing phase.
Mitigation strategies must focus on both immediate remediation and long-term architectural improvements. NVIDIA should release an updated version of NeMo Speech that patches the specific parsing logic responsible for handling untrusted inputs. In the interim, organizations deploying this technology should implement strict input filtering at network boundaries to reject malformed or suspiciously structured speech data before it reaches the application layer. Additionally, running the service with least-privilege principles is essential; isolating the NeMo Speech process within a containerized environment with restricted file system and network access can limit the blast radius of any successful exploitation. Regular security audits focusing on third-party libraries used for audio processing are also recommended to ensure that underlying dependencies do not introduce similar vulnerabilities.