Description

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.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "7.8",
  "pubDate": "2026-09-22T15:17:10.013Z",
  "pubdate": "2026-09-22T15:17:10.013Z",
  "executiveSummary": "A critical security vulnerability has been identified in NVIDIA NeMo, a conversational AI toolkit. This vulnerability allows an unauthenticated, remote attacker to trigger remote code execution (RCE) by supplying specially crafted, malicious input data to the affected system.\nThe vulnerability stems from improper input validation or insecure deserialization processes within the framework. Successful exploitation grants the attacker the ability to execute arbitrary code within the context of the application process.\nThe impact of this vulnerability is severe, potentially resulting in full system compromise, unauthorized information disclosure, and illicit data tampering. All platforms utilizing NVIDIA NeMo are susceptible to this threat.\nThe risk is exacerbated by the capability for remote exploitation, requiring no prior authentication or specific user privileges. Organizations deploying NVIDIA NeMo should prioritize monitoring for anomalous input patterns and restrict network exposure of services leveraging the framework.",
  "technicalDetails": "The vulnerability resides within the data processing pipeline of NVIDIA NeMo, specifically where the framework handles untrusted or external input files during model training, inference, or data loading stages. The root cause is linked to the insecure handling of malicious data that triggers memory corruption, insecure deserialization, or arbitrary command injection during the parsing of input structures.\nThe exploitation flow begins when an attacker delivers a malformed data payload to an endpoint or interface that consumes inputs for NVIDIA NeMo processing. If the application performs deserialization on these payloads without sufficient integrity checks or sanitization, the underlying runtime may be manipulated into executing attacker-supplied code.\nIn scenarios involving insecure deserialization, the attacker embeds serialized objects into the input data. When the vulnerable component attempts to reconstruct these objects, it invokes arbitrary code specified within the payload. If the vulnerability is related to memory corruption, the attacker leverages specifically crafted inputs to overflow buffers or manipulate pointers, ultimately hijacking the control flow of the host process to redirect execution to malicious shellcode.\nBecause NVIDIA NeMo components often operate with high-level permissions to access GPU resources and storage, successful code execution allows the attacker to achieve persistence, escalate privileges within the host environment, and access sensitive data processed by the AI models.\nThe attack is network-exploitable, meaning it can be initiated remotely without existing user interaction or authentication. The vulnerability affects the core library components responsible for model configuration loading and data ingestion. Given that NeMo is often deployed in high-performance computing environments or cloud-based AI inference services, the potential for lateral movement post-exploitation is significant.\nThe post-exploitation phase typically involves the attacker establishing a command-and-control connection from the compromised machine, exfiltrating proprietary training data or model weights, and deploying further payloads to facilitate long-term surveillance or system-wide disruption."
}