CVE-2024-0088

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.

CVE-2024-0100

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.

CVE-2024-53880

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...

CVE-2024-0087

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,...

CVE-2023-31036

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 ...

CVE-2024-0103

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.

CVE-2024-0095

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 privile...

CVE-2024-0116

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.

CVE-2025-23319

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 infor...

CVE-2025-23310

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 tamperin...

CVE-2025-23311

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.

CVE-2025-23320

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.

CVE-2025-23317

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 di...

CVE-2025-23318

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.

CVE-2025-23334

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.

CVE-2025-23316

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause a remote code execution by manipulating the model name parameter in the model control APIs. A successful exploit of this vulnerability might lead to remote code executi...

CVE-2025-23324

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.

CVE-2025-23327

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause an integer overflow through specially crafted inputs. A successful exploit of this vulnerability might lead to denial of service and data tampering.

CVE-2025-23331

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where a user could cause a memory allocation with excessive size value, leading to a segmentation fault, by providing an invalid request. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23322

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where multiple requests could cause a double free when a stream is cancelled before it is processed. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23323

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.

CVE-2025-23325

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause uncontrolled recursion through a specially crafted input. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23329

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause memory corruption by identifying and accessing the shared memory region used by the Python backend. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23326

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause an integer overflow through a specially crafted input. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23328

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause an out-of-bounds write through a specially crafted input. A successful exploit of this vulnerability might lead to denial of service.

CVE-2025-23333

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.

CVE-2025-23335

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.

CVE-2025-23321

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.

CVE-2025-23336

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause a denial of service by loading a misconfigured model. A successful exploit of this vulnerability might lead to denial of service.