Overview
We are taking a deep dive into a critical vulnerability in the NVIDIA Triton Inference Server for both Windows and Linux systems. Identified as CVE-2025-23316, this vulnerability could potentially compromise systems, leading to data leakage. It is specifically located within the Python backend of the server, affecting the model control APIs. This vulnerability is of utmost importance due to its severe impact on system integrity, confidentiality, and availability, as it can lead to remote code execution, denial of service, information disclosure, and data tampering.
Vulnerability Summary
CVE ID: CVE-2025-23316
Severity: Critical – 9.8 CVSS Score
Vector: Network
Privileges Required: None
User Interaction: None
Impact: Potential system compromise or data leakage, remote code execution, denial of service, information disclosure, and data tampering.
Affected Products
Escape the Surveillance Era
Most apps won’t tell you the truth.
They’re part of the problem.
Phone numbers. Emails. Profiles. Logs.
It’s all fuel for surveillance.
Ameeba Chat gives you a way out.
- • No phone number
- • No email
- • No personal info
- • Anonymous aliases
- • End-to-end encrypted
Chat without a trace.
Product | Affected Versions
NVIDIA Triton Inference Server | All versions before the patch
How the Exploit Works
The vulnerability lies in the Python backend of the NVIDIA Triton Inference Server. An attacker can manipulate the model name parameter in the model control APIs to trigger the vulnerability. This manipulation may cause a buffer overflow or other undefined behavior that could allow an attacker to execute arbitrary code remotely. As the server does not properly validate the model name parameter, a maliciously crafted model name could result in the execution of unintended instructions. This could lead to a range of outcomes, including denial of service, confidential information disclosure, data tampering, and even full system compromise.
Conceptual Example Code
Here’s a conceptual example demonstrating how an attacker might exploit this vulnerability. Note that this is a simplified representation and actual exploit might require more sophisticated techniques.
POST /v1/models/{malicious_model_name}/versions/1:predict HTTP/1.1
Host: target.example.com
Content-Type: application/json
{ "inputs": [...] }In the above example, the `{malicious_model_name}` would be replaced with a specially crafted string that exploits the vulnerability in the model name handling logic of the NVIDIA Triton Inference Server.
Mitigation
To mitigate this vulnerability, apply the vendor-provided patch as soon as possible. Until the patch can be applied, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) could be used as a temporary mitigation to block or alert on suspicious activities. Ensure these systems are configured correctly to detect and prevent the exploitation of this vulnerability. Also, consider limiting the exposure of the NVIDIA Triton Inference Server to the internet and restrict its access to trusted networks only.
