CVE-2025-23325 is a high-severity vulnerability affecting NVIDIA Triton Inference Server versions prior to 25.05 on both Windows and Linux platforms. The vulnerability is classified under CWE-674, which pertains to uncontrolled recursion. In this case, an attacker can craft a malicious input that triggers uncontrolled recursive calls within the Triton Inference Server. This recursive behavior can exhaust system resources such as stack memory, leading to a denial of service (DoS) condition. The vulnerability does not impact confidentiality or integrity directly but severely affects availability by potentially crashing or rendering the inference server unresponsive. The CVSS 3.1 score of 7.5 reflects a network attack vector (AV:N) with low attack complexity (AC:L), no privileges required (PR:N), and no user interaction (UI:N), indicating that exploitation can be performed remotely and easily without authentication or user involvement. The scope is unchanged (S:U), meaning the impact is limited to the vulnerable component itself. Although no known exploits are currently reported in the wild, the nature of the vulnerability and the critical role of Triton Inference Server in AI model deployment make it a significant risk. The lack of available patches at the time of publication necessitates immediate attention to mitigation strategies.

For European organizations, the impact of this vulnerability can be substantial, especially for those relying on NVIDIA Triton Inference Server to deploy AI and machine learning models in production environments. Industries such as automotive, healthcare, finance, and manufacturing increasingly use AI inference servers for critical decision-making and automation. A successful DoS attack could disrupt business operations, cause downtime in AI-driven services, and potentially lead to financial losses and reputational damage. Given the remote and unauthenticated nature of the exploit, attackers could launch attacks from anywhere, increasing the threat landscape. Additionally, organizations with AI infrastructure exposed to the internet or insufficiently segmented internal networks are at higher risk. The disruption of AI inference services might also affect compliance with data processing regulations if service availability is mandated. Therefore, the vulnerability poses a direct threat to operational continuity and service reliability within European enterprises leveraging NVIDIA’s AI inference technology.

To mitigate this vulnerability, European organizations should prioritize upgrading NVIDIA Triton Inference Server to version 25.05 or later once the patch is released. Until then, organizations should implement network-level protections such as restricting access to the inference server to trusted internal networks and using firewalls or VPNs to limit exposure. Deploying Web Application Firewalls (WAFs) or Intrusion Prevention Systems (IPS) with custom rules to detect and block anomalous recursive input patterns may help reduce risk. Monitoring server logs and resource usage for unusual spikes indicative of recursion attacks is advisable. Additionally, organizations should conduct thorough security assessments of their AI infrastructure, including penetration testing focused on input validation and resource exhaustion scenarios. Implementing rate limiting and input validation at the application layer can further reduce the attack surface. Finally, maintaining an incident response plan that includes AI infrastructure components will help organizations respond swiftly to potential exploitation attempts.