CVE-2025-33194 is a vulnerability identified in the SROOT firmware of NVIDIA DGX Spark GB10 systems, specifically in all versions prior to the OTA0 update. The root cause is an incorrect behavior order related to input data processing, classified under CWE-180: Validate Before Canonicalize. This means the firmware validates input data before converting it into a canonical form, which can lead to improper processing of certain crafted inputs. Such mishandling can cause unintended behavior, including information disclosure or denial of service conditions. The vulnerability has a CVSS 3.1 base score of 5.7, indicating medium severity. The attack vector is local (AV:L), requiring no privileges (PR:N) and no user interaction (UI:N), but the scope is changed (S:C), meaning exploitation can affect components beyond the vulnerable code. The impact is limited to confidentiality (C:L) and availability (A:L), with no impact on integrity. No public exploits or active exploitation have been reported to date. The affected product, NVIDIA DGX Spark, is a high-performance computing platform used primarily for AI and data-intensive workloads, making the vulnerability relevant to organizations relying on these systems. The lack of a patch link suggests that a fix is either pending or distributed through official OTA updates. Proper canonicalization after validation is critical to prevent such vulnerabilities, as it ensures input is normalized before security checks.

For European organizations utilizing NVIDIA DGX Spark systems, this vulnerability poses a risk of limited information disclosure and denial of service, potentially disrupting critical AI and HPC workloads. Although the attack requires local access, compromised internal systems or insider threats could exploit this flaw to degrade system availability or leak sensitive data processed by DGX Spark nodes. This could impact research institutions, technology companies, and data centers relying on these platforms. The medium severity indicates moderate risk, but the strategic importance of AI infrastructure in Europe elevates the operational impact. Disruptions could delay AI model training, data analysis, or other compute-intensive tasks, affecting business continuity and competitive advantage. Confidentiality impact, while limited, could expose proprietary datasets or model parameters. The absence of known exploits reduces immediate risk but does not eliminate the threat, especially as attackers often develop exploits post-disclosure.

1. Apply the official OTA0 firmware update from NVIDIA as soon as it becomes available to remediate the vulnerability. 2. Restrict local access to DGX Spark systems strictly to authorized personnel and enforce strong physical and network access controls. 3. Monitor system logs and firmware behavior for anomalies indicative of exploitation attempts or unexpected input processing errors. 4. Implement network segmentation to isolate DGX Spark nodes from less trusted network zones, minimizing the risk of local exploitation via lateral movement. 5. Conduct regular security audits and firmware integrity checks to detect unauthorized modifications. 6. Educate system administrators and operators about the vulnerability and the importance of timely patching. 7. Coordinate with NVIDIA support for guidance on interim mitigations if patch deployment is delayed. 8. Consider deploying host-based intrusion detection systems (HIDS) tailored to detect unusual activity on DGX Spark firmware components.