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The CVE-2025-33201 vulnerability in the NVIDIA Triton Inference Server stems from an improper check for unusual or exceptional conditions when processing inference requests. Specifically, the server’s request handling logic fails to adequately validate the size of incoming payloads before allocating necessary buffers or proceeding with processing. An attacker can exploit this flaw by sending a specifically crafted, extra-large HTTP/gRPC request payload to a vulnerable Triton server endpoint. This oversized payload triggers an erroneous condition where the server attempts to allocate excessive memory or enters an unstable state while parsing the request headers or body. This condition is not properly caught by the server’s error handling routines, leading to a critical failure in the request handling thread or process. Consequently, the server may experience a segmentation fault, an abort, or a catastrophic resource exhaustion, resulting in a complete denial of service (DoS) for all subsequent inference requests. The attack is network-exploitable and does not require user privileges, allowing an unauthenticated remote attacker to repeatedly crash the service.
Platform: NVIDIA Triton Inference Server
Version: Affected versions
Vulnerability: Denial of Service
Severity: Medium
Date: 2025-12-03
Prediction: 2025-12-17
What Undercode Say:
curl -X POST http://<target>:8000/v2/models/<model>/infer -H "Content-Type: application/octet-stream" --data-binary @large_payload.bin
import tritonclient.http as httpclient
client = httpclient.InferenceServerClient(url='<target>:8000')
large_input = httpclient.InferInput('INPUT', [1000000, 1000], "INT32")
... assign impossibly large tensor data ...
client.infer(model_name="<model>", inputs=[bash])
How Exploit:
- Attacker identifies a vulnerable, publicly exposed Triton Inference Server instance.
- Attacker crafts an HTTP POST request to the `/v2/models//infer` endpoint with a massively oversized body, exceeding normal operational parameters.
- The Triton server receives the request and fails to properly check the payload size during initial parsing or buffer allocation.
- This triggers an unhandled exceptional condition (e.g., integer overflow, failed large allocation, or parsing error), causing the serving process or thread to crash.
- The crash leads to a denial of service, making the inference server unavailable until manually restarted.
Protection from this CVE:
Apply NVIDIA security update.
Implement request size limiting.
Use network ingress filtering.
Deploy behind a WAF.
Impact:
Service disruption.
Loss of availability.
Resource exhaustion.
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Sources:
Reported By: nvd.nist.gov
Extra Source Hub:
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