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NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where a user could cause a divide by zero issue by issuing an invalid request. A successful exploit of this vulnerability might lead to denial of service.

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause the shared memory limit to be exceeded by sending a very large request. 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 write by sending a request. A successful exploit of this vulnerability might lead to remote code execution, denial of service, data tampering, or 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 write. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure.

NVIDIA Triton Inference Server contains a vulnerability in the HTTP server, where an attacker could start a reverse shell by sending a specially crafted HTTP request. A successful exploit of this vulnerability might lead to remote code execution, denial of service, data tampering, or information disclosure.

NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a stack overflow through specially crafted HTTP requests. A successful exploit of this vulnerability might lead to remote code execution, denial of service, information disclosure, or data tampering.

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause stack buffer overflow by specially crafted inputs. A successful exploit of this vulnerability might lead to remote code execution, denial of service, information disclosure, and data tampering.

NVIDIA Triton Inference Server contains a vulnerability in the model loading API, where a user could cause an integer overflow or wraparound error by loading a model with an extra-large file size that overflows an internal variable. A successful exploit of this vulnerability might lead to denial of service.

NVIDIA Triton Inference Server contains a vulnerability where a user may cause an out-of-bounds read issue by releasing a shared memory region while it is in use. A successful exploit of this vulnerability may lead to denial of service.

NVIDIA Triton Inference Server for Linux contains a vulnerability where a user may cause an incorrect Initialization of resource by network issue. A successful exploit of this vulnerability may lead to information disclosure.

NVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where a user can inject forged logs and executable commands by injecting arbitrary data as a new log entry. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disc

NVIDIA Triton Inference Server for Linux contains a vulnerability in the tracing API, where a user can corrupt system files. A successful exploit of this vulnerability might lead to denial of service and data tampering.

NVIDIA Triton Inference Server for Linux contains a vulnerability in shared memory APIs, where a user can cause an improper memory access issue by a network API. A successful exploit of this vulnerability might lead to denial of service and data tampering.

NVIDIA Triton Inference Server for Linux contains a vulnerability where a user can set the logging location to an arbitrary file. If this file exists, logs are appended to the file. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosu

NVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where, when it is launched with the non-default command line option --model-control explicit, an attacker may use the model load API to cause a relative path traversal. A successful exploit of this vulnerability may lead to code execution, de