CVE-2025-1975 is a high-severity vulnerability affecting the Ollama server, specifically version 0.5.11. The vulnerability arises from improper validation of array index access (CWE-129) during the process of downloading a model via the /api/pull endpoint. An attacker can exploit this flaw by customizing the manifest content and spoofing a service, which leads to an out-of-bounds array access. This improper validation causes the server to crash, resulting in a Denial of Service (DoS) condition. The vulnerability does not require authentication or user interaction and can be exploited remotely over the network (AV:N, AC:L, PR:N, UI:N). The impact is limited to availability, with no direct confidentiality or integrity compromise reported. Although no known exploits are currently observed in the wild, the ease of exploitation and the potential to disrupt service make this a significant threat to organizations relying on the Ollama server for AI model management or deployment.

For European organizations using the Ollama server, this vulnerability poses a risk of service disruption. Organizations that depend on Ollama for AI model hosting or inference could experience downtime, affecting business continuity and potentially delaying critical AI-driven operations. The DoS attack could also be leveraged as part of a larger attack chain to distract or degrade defenses. In sectors such as finance, healthcare, or critical infrastructure where AI services are increasingly integrated, such disruptions could have cascading effects on operational efficiency and service delivery. Additionally, organizations with stringent uptime requirements or service-level agreements (SLAs) may face compliance and reputational risks if exploited.

To mitigate this vulnerability, European organizations should: 1) Immediately update the Ollama server to a patched version once available from the vendor, as no patch links are currently provided but should be prioritized upon release. 2) Implement network-level protections such as web application firewalls (WAFs) and intrusion prevention systems (IPS) to detect and block malformed requests targeting the /api/pull endpoint. 3) Restrict access to the Ollama server API to trusted internal networks or VPNs to reduce exposure to unauthenticated remote attacks. 4) Monitor server logs for unusual activity or repeated crashes related to model downloads, enabling rapid detection and response. 5) Employ rate limiting on API endpoints to reduce the risk of automated exploitation attempts. 6) Conduct regular security assessments and code reviews focusing on input validation to prevent similar vulnerabilities in custom or third-party AI infrastructure.