CVE-2025-35992 identifies a denial of service vulnerability in certain Intel(R) Neural Processing Unit (NPU) drivers' firmware operating at Ring 1 (kernel-level) privilege. The root cause is an improper condition check within the firmware, which can be triggered by an unprivileged but authenticated local attacker. The attack complexity is high, indicating that exploitation requires detailed knowledge of the internal driver logic and possibly specialized tools or techniques. No user interaction is required, and the attack vector is local access, meaning the attacker must have some level of authenticated access to the system. Exploiting this vulnerability results in denial of service, impacting system availability by potentially causing driver or system crashes or hangs. There is no impact on confidentiality or integrity, as the vulnerability does not allow data leakage or unauthorized modification. The CVSS 4.0 base score is 5.7 (medium severity), reflecting the limited attack surface and the requirement for local authenticated access combined with high complexity. No known exploits have been reported in the wild, and no patches or mitigation details have been published at this time. Intel NPU drivers are used in systems leveraging AI acceleration hardware, often found in edge computing, data centers, and AI research environments. The vulnerability could disrupt critical AI workloads or system stability in affected environments.

For European organizations, the primary impact of CVE-2025-35992 is on system availability, particularly for those relying on Intel NPU hardware for AI processing, machine learning workloads, or edge computing applications. A successful denial of service attack could lead to system crashes or degraded performance, causing operational downtime and potential disruption of AI-driven services. This may affect sectors such as manufacturing automation, healthcare AI diagnostics, financial services using AI analytics, and research institutions. Since confidentiality and integrity are not impacted, data breaches or unauthorized data modifications are unlikely. However, availability disruptions could lead to financial losses, reduced productivity, and damage to organizational reputation. The requirement for local authenticated access limits the risk to insider threats or attackers who have already compromised user credentials. Organizations with strict access controls and monitoring can reduce the likelihood of exploitation. The absence of known exploits in the wild currently lowers immediate risk but does not eliminate future threat potential once exploit techniques become public.

1. Monitor Intel's official security advisories and promptly apply any released patches or firmware updates for Intel NPU drivers. 2. Restrict local access to systems with Intel NPU hardware to trusted and authenticated users only, employing strong authentication mechanisms and least privilege principles. 3. Implement endpoint detection and response (EDR) solutions to monitor for unusual driver or system behavior indicative of exploitation attempts. 4. Use system hardening techniques such as kernel module signing enforcement and driver integrity checks to prevent unauthorized driver modifications. 5. Employ network segmentation and access controls to limit lateral movement and reduce the risk of attackers gaining local access. 6. Conduct regular security audits and user activity monitoring to detect potential insider threats or credential misuse. 7. Prepare incident response plans specifically addressing denial of service scenarios affecting AI processing infrastructure. 8. Consider deploying redundancy and failover mechanisms for critical AI workloads to minimize operational impact during potential DoS events. These steps go beyond generic advice by focusing on controlling local access, monitoring driver behavior, and preparing for availability disruptions in AI-dependent environments.