CVE-2025-33202: About NVIDIA Triton Inference Server (14th Nov 2025)

Official Updated 11/10/2025 05:39 AM

Preface: Clients can communicate with Triton using either an HTTP/REST protocol, a GRPC protocol, or by an in-process C API or its C++ wrapper. Triton supports HTTP/REST and gRPC, both of which involve complex header parsing.

In the context of the Open Inference Protocol (OIP), also known as KServe V2 Protocol. The protocol defines a standardized interface for model inference, which implies that compliant inference servers must be capable of parsing incoming requests and serializing outgoing responses according to the protocol’s defined message formats.

Background: To define a parser that filters the payload for Triton using the KServe V2 (Open Inference Protocol), you need to handle the following:

Key Considerations

1.Protocol Compliance – The parser must understand the OIP message format:

-Inference Request: Includes inputs, outputs, parameters.

-Inference Response: Includes model_name, outputs, parameters.

-Data can be in JSON (for REST) or Protobuf (for gRPC).

2.Filtering Logic – Decide what you want to filter:

-Specific tensor names?

-Certain data types (e.g., FP32, INT64)?

-Large payloads (e.g., skip tensors above a size threshold)?

-Security checks (e.g., reject malformed headers)?

3.Shared Memory Handling – If shared memory is used, the parser should:

-Validate shared_memory_region references.

-Ensure the payload does not redundantly include tensor data when shared memory is specified.

Vulnerability details: NVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where an attacker could cause a stack overflow by sending extra-large payloads. A successful exploit of this vulnerability might lead to denial of service.

Official announcement: Please see the official link for details –

https://nvidia.custhelp.com/app/answers/detail/a_id/5723

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