NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP component, where malicious data created by an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and data tampering.
NVIDIA Megatron-LM for all platforms contains a vulnerability in the tools component, where an attacker may exploit a code injection issue. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.
NVIDIA Megatron-LM for all platforms contains a vulnerability in the megatron/training/
arguments.py component where an attacker could cause a code injection issue by providing a malicious input. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.
NVIDIA Apex for all platforms contains a vulnerability in a Python component where an attacker could cause a code injection issue by providing a malicious file. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and data tampering.
NVIDIA NeMo Framework for all platforms contains a vulnerability where a user could cause a deserialization of untrusted data by remote code execution. A successful exploit of this vulnerability might lead to code execution and data tampering.
NVIDIA NeMo library for all platforms contains a vulnerability in the model loading component, where an attacker could cause code injection by loading .nemo files with maliciously crafted metadata. A successful exploit of this vulnerability may lead to remote code execution and data tampering.
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause an out-of-bounds read by manipulating shared memory data. A successful exploit of this vulnerability might lead to information disclosure.
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause an out-of-bounds read by sending a request. A successful exploit of this vulnerability might lead to information disclosure.
NVIDIA Triton Inference Server for Windows and Linux and the Tensor RT backend contain a vulnerability where an attacker could cause an underflow by a specific model configuration and a specific input. A successful exploit of this vulnerability might lead to denial of service.
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where a user could cause an integer overflow or wraparound, leading to a segmentation fault, by providing an invalid request. A successful exploit of this vulnerability might lead to denial of service.