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CVE-2025-33195: CWE-119 Improper Restriction of Operations within the Bounds of a Memory Buffer in NVIDIA DGX Spark

0
Medium
VulnerabilityCVE-2025-33195cvecve-2025-33195cwe-119
Published: Tue Nov 25 2025 (11/25/2025, 17:59:42 UTC)
Source: CVE Database V5
Vendor/Project: NVIDIA
Product: DGX Spark

Description

NVIDIA DGX Spark GB10 contains a vulnerability in SROOT firmware, where an attacker could cause unexpected memory buffer operations. A successful exploit of this vulnerability might lead to data tampering, denial of service, or escalation of privileges.

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 02/27/2026, 06:34:25 UTC

Technical Analysis

CVE-2025-33195 is a vulnerability identified in the SROOT firmware of NVIDIA DGX Spark GB10, a high-performance computing platform used primarily for AI and data-intensive workloads. The flaw is categorized under CWE-119, indicating improper restriction of operations within the bounds of a memory buffer. This type of vulnerability typically arises from insufficient validation of memory operations, which can lead to buffer overflows or out-of-bounds memory access. In this case, an attacker with local privileges (AV:L - local attack vector) and low complexity (AC:L) can exploit the vulnerability without requiring user interaction (UI:N). The vulnerability allows unexpected memory buffer operations that may lead to data tampering, denial of service (DoS), or escalation of privileges, potentially compromising the integrity and availability of the system. The CVSS 3.1 base score is 4.4, reflecting medium severity, with no confidentiality impact but some integrity and availability impacts. The vulnerability affects all versions of the DGX Spark firmware prior to the OTA0 update. No public exploits have been reported yet, but the risk remains significant due to the critical nature of the affected systems. The lack of a patch link suggests that remediation is pending or that users must await the official OTA0 update. Given the specialized nature of the DGX Spark platform, exploitation would require local access, which may limit widespread exploitation but poses a serious risk in environments where multiple users have system access or where attackers can gain foothold through other means.

Potential Impact

The potential impact of CVE-2025-33195 is significant for organizations relying on NVIDIA DGX Spark systems, which are commonly deployed in AI research, high-performance computing, and data centers. Successful exploitation can lead to data tampering, undermining the integrity of critical computations and datasets. Denial of service could disrupt ongoing AI model training or inference workloads, causing operational downtime and financial loss. Privilege escalation could allow attackers to gain higher-level control over the system, potentially leading to further compromise of the infrastructure. Since the vulnerability requires local access, insider threats or attackers who have already breached perimeter defenses pose the greatest risk. The impact is particularly critical in environments where DGX Spark systems handle sensitive or proprietary data, such as research institutions, technology companies, and government agencies. The medium CVSS score reflects moderate risk, but the specialized nature of the platform and the potential for privilege escalation warrant serious attention.

Mitigation Recommendations

To mitigate CVE-2025-33195, organizations should: 1) Monitor NVIDIA’s official channels closely for the release of the OTA0 firmware update and apply it promptly once available. 2) Restrict local access to DGX Spark systems to trusted personnel only, implementing strict access controls and user authentication mechanisms. 3) Employ network segmentation to isolate DGX Spark systems from less secure network zones to reduce the risk of lateral movement. 4) Use host-based intrusion detection systems (HIDS) to monitor for unusual memory operations or privilege escalation attempts on these systems. 5) Conduct regular audits of user privileges and system logs to detect potential misuse or early signs of exploitation. 6) Consider deploying endpoint protection solutions that can detect anomalous firmware or memory behavior. 7) Educate administrators and users about the risks of local exploits and enforce the principle of least privilege. These steps go beyond generic advice by focusing on controlling local access and monitoring firmware-level behavior, which is critical given the attack vector and nature of the vulnerability.

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Technical Details

Data Version
5.2
Assigner Short Name
nvidia
Date Reserved
2025-04-15T18:51:03.729Z
Cvss Version
3.1
State
PUBLISHED

Threat ID: 6925f0bc94b153c6e1167ea8

Added to database: 11/25/2025, 6:09:00 PM

Last enriched: 2/27/2026, 6:34:25 AM

Last updated: 3/22/2026, 11:05:22 AM

Views: 89

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