CVE-2025-53767 is a critical Server-Side Request Forgery (SSRF) vulnerability identified in Microsoft Azure Open AI services. SSRF vulnerabilities allow an attacker to induce the server-side application to make HTTP requests to arbitrary domains, potentially bypassing firewall rules and accessing internal or protected resources. This specific vulnerability is classified under CWE-918, indicating a weakness in server-side request handling. The CVSS 3.1 base score of 10.0 reflects the highest severity, with an attack vector that is network-based (AV:N), requiring no privileges (PR:N) and no user interaction (UI:N). The scope is changed (S:C), meaning the vulnerability affects resources beyond the initially vulnerable component, and it impacts confidentiality and integrity at a high level (C:H/I:H), though availability is not affected (A:N). In the context of Azure Open AI, this SSRF vulnerability could allow an unauthenticated attacker to craft malicious requests that the Azure Open AI backend processes, potentially enabling them to access internal Azure infrastructure, sensitive metadata services, or other protected endpoints within the cloud environment. This could lead to unauthorized data disclosure, manipulation of AI model inputs or outputs, or lateral movement within the cloud environment. The elevation of privilege aspect suggests that the attacker could gain higher access rights than normally permitted, potentially compromising the confidentiality and integrity of data and services hosted on Azure Open AI. Although no known exploits are currently reported in the wild, the critical severity and ease of exploitation make it a significant threat that requires immediate attention. The absence of specified affected versions indicates that the vulnerability may affect all current deployments of Azure Open AI until patched. No patch links are provided yet, indicating that remediation may still be pending or in progress.

For European organizations leveraging Microsoft Azure Open AI services, this vulnerability poses a severe risk. Confidential data processed or stored within Azure Open AI could be exposed or manipulated by attackers exploiting this SSRF flaw. Given the critical nature of the vulnerability and the cloud-native architecture of Azure services, attackers could potentially access internal cloud resources, leading to data breaches, intellectual property theft, or disruption of AI-driven business processes. The integrity of AI models and their outputs could be compromised, affecting decision-making processes reliant on these models. Additionally, unauthorized access to internal Azure infrastructure could facilitate further attacks against other cloud services or customer environments. This risk is heightened for sectors with stringent data protection requirements under GDPR, such as finance, healthcare, and government agencies in Europe, where data confidentiality and integrity are paramount. The lack of required authentication and user interaction means attacks could be automated and widespread, increasing the threat surface for European enterprises using Azure Open AI.

European organizations should immediately review their use of Azure Open AI services and monitor for any unusual network activity or unexpected outbound requests from these services. Until an official patch is released by Microsoft, organizations should consider implementing network-level controls such as restricting outbound traffic from Azure Open AI instances to only trusted endpoints using Azure Firewall or Network Security Groups (NSGs). Employing strict egress filtering can limit the ability of SSRF attacks to reach internal or sensitive resources. Additionally, organizations should enable and review Azure Monitor and Azure Security Center logs for anomalous request patterns indicative of SSRF exploitation attempts. It is also advisable to apply the principle of least privilege to Azure Open AI service accounts and segregate workloads to minimize potential impact. Once Microsoft releases a patch or update, organizations must prioritize its deployment. Finally, organizations should conduct internal penetration testing and vulnerability assessments focused on SSRF to identify any residual risks in their cloud environments.