The identified threat involves a Server-Side Request Forgery (SSRF) vulnerability within ChatGPT's custom GPT functionality. SSRF vulnerabilities allow attackers to induce the server-side application to make HTTP requests to arbitrary domains, potentially accessing internal resources or sensitive data. In this case, the vulnerability enables an attacker to retrieve an Azure access token, which is a critical credential used to authenticate and authorize access to Azure cloud resources. Possession of such a token could allow an attacker to enumerate or manipulate cloud infrastructure, leading to data exposure or further compromise. The vulnerability stems from insufficient validation or sanitization of URLs or requests made by the custom GPT feature, which interacts with backend Azure services. No specific affected versions or patches have been disclosed, and no active exploitation has been reported yet. The medium severity rating reflects the potential for significant impact if exploited, balanced against the complexity of successfully leveraging the SSRF to obtain tokens. This vulnerability highlights risks associated with integrating AI services with cloud infrastructure without robust input validation and access controls.

For European organizations, the impact of this vulnerability could be substantial, especially for those heavily reliant on Azure cloud services and integrating AI-driven tools like ChatGPT custom GPTs. Unauthorized access to Azure tokens could lead to exposure of sensitive corporate data, disruption of cloud-hosted services, and potential lateral movement within cloud environments. This could affect confidentiality, integrity, and availability of critical systems. Organizations in sectors such as finance, healthcare, and government, which often use Azure and AI services, may face regulatory and reputational damage if exploited. Additionally, the exposure of cloud infrastructure details could facilitate further targeted attacks. Although no active exploitation is known, the vulnerability represents a significant risk vector that could be leveraged by sophisticated threat actors targeting European enterprises.

To mitigate this threat, organizations should implement strict input validation and sanitization on any user-supplied URLs or data processed by AI services like custom GPTs. Network-level controls should restrict outbound requests from AI service components to only trusted endpoints, minimizing SSRF attack surfaces. Azure access tokens should be managed with the principle of least privilege, using short-lived tokens and monitoring token usage for anomalies. Organizations should apply any patches or updates released by OpenAI or Microsoft promptly once available. Additionally, implementing robust logging and alerting on unusual API calls or token usage can help detect exploitation attempts early. Conducting regular security assessments of AI integrations and cloud configurations will further reduce risk. Collaboration with cloud service providers to understand and secure AI-related interfaces is also recommended.