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CVE-2025-23323: Integer Overflow Leads to Potential System Compromise in NVIDIA Triton Inference Server

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Overview

The vulnerability identified as CVE-2025-23323 poses a significant risk to systems running NVIDIA Triton Inference Server for both Windows and Linux. This flaw allows an attacker to cause an integer overflow or wraparound, leading to a segmentation fault. The importance of addressing this vulnerability cannot be overstated, as a successful exploit could lead to a system-wide denial of service, potential compromise, and data leakage.

Vulnerability Summary

CVE ID: CVE-2025-23323
Severity: High (7.5 CVSS Score)
Attack Vector: Remote
Privileges Required: None
User Interaction: None
Impact: System compromise and potential data leakage

Affected Products

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Product | Affected Versions

NVIDIA Triton Inference Server for Windows | All versions prior to patch
NVIDIA Triton Inference Server for Linux | All versions prior to patch

How the Exploit Works

The exploit targets a flaw in NVIDIA Triton Inference Server’s handling of certain requests. When an attacker sends an invalid request purposefully crafted to cause an integer overflow or wraparound, the system experiences a segmentation fault. This fault could lead to a denial of service. In some instances, the attacker might leverage this vulnerability to gain unauthorized access to the system and potentially access sensitive data.

Conceptual Example Code

POST /triton-inference-server/endpoint HTTP/1.1
Host: target.example.com
Content-Type: application/json
{ "request_size": "9223372036854775808" }

In this example, the `”request_size”` value is purposefully set to a value higher than what a 64-bit signed integer can handle, causing an integer overflow. This leads to a segmentation fault, resulting in a potential system compromise or data leakage.

Mitigation

The most effective way to resolve this vulnerability is by applying the vendor-provided patch. In cases where immediate patching is not possible, using a Web Application Firewall (WAF) or Intrusion Detection Systems (IDS) may serve as a temporary mitigation measure. These systems should be configured to detect and block abnormal request sizes that could trigger the integer overflow.

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Disclaimer:

The information and code presented in this article are provided for educational and defensive cybersecurity purposes only. Any conceptual or pseudocode examples are simplified representations intended to raise awareness and promote secure development and system configuration practices.

Do not use this information to attempt unauthorized access or exploit vulnerabilities on systems that you do not own or have explicit permission to test.

Ameeba and its authors do not endorse or condone malicious behavior and are not responsible for misuse of the content. Always follow ethical hacking guidelines, responsible disclosure practices, and local laws.

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