CVE-2025-33199VulnerabilityPublished 25 Nov 2025

CVE-2025-33199: NVIDIA DGX Spark · Always-Incorrect Control Flow Implementation

Affects NVIDIA DGX SparkSource CVE Database V5

Not known to be exploited · CVSS 3.2 Low.

Data as of 26 Oct 2026, 07:57 UTC

CVSS 3.1 base score

3.2Low

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.1% chance of exploitation in 30 days – higher than 3% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:C/C:N/I:L/A:N

Attack Vector: Local
Attack Complexity: Low
Privileges Required: High
User Interaction: None
Scope: Changed
Confidentiality: None
Integrity: Low
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: High: The attacker is authorized with (i.e., requires) privileges that provide significant (e.g., administrative) control over the vulnerable component that could affect component-wide settings and files.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Changed: An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 25 Nov 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

AI-suggested

Organizations should prioritize the deployment of the OTA0 firmware update from NVIDIA as soon as it becomes available to remediate this vulnerability. Until the patch is applied, strict access controls must be enforced to limit local high-privilege access to trusted and vetted personnel only. Implement robust monitoring and auditing of privileged user activities on DGX Spark systems to detect any anomalous behavior indicative of exploitation attempts. Segmentation of AI infrastructure networks can reduce the risk of lateral movement by attackers with local access. Employ hardware and firmware integrity verification tools where possible to detect unauthorized modifications. Additionally, organizations should review and harden their insider threat detection programs, given the requirement for high privilege local access. Coordination with NVIDIA support channels for timely updates and advisories is recommended. Finally, maintaining an up-to-date asset inventory of DGX Spark deployments will aid in rapid response and patch management.

Description

NVIDIA DGX Spark GB10 contains a vulnerability in SROOT firmware, where an attacker could cause incorrect control flow behavior. A successful exploit of this vulnerability might lead to data tampering.

Impact

For European organizations, especially those engaged in AI research, data analytics, and high-performance computing using NVIDIA DGX Spark systems, this vulnerability poses a risk to data integrity. Data tampering could lead to corrupted AI model training, inaccurate analytics results, or compromised research outputs, potentially affecting decision-making and operational reliability. Although the vulnerability does not expose sensitive data or cause system downtime, the integrity compromise can have cascading effects in environments where data accuracy is critical. The requirement for high privilege local access limits the risk to insider threats or attackers who have already breached perimeter defenses. However, organizations with lax internal access controls or shared computing environments may be more vulnerable. The absence of known exploits reduces immediate risk but does not eliminate the threat, especially as attackers may develop exploits post-disclosure. The impact is more pronounced in sectors relying heavily on DGX Spark for critical AI workloads, such as research institutions, technology companies, and data centers across Europe.

References

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 2 Dec 2025, 18:49 UTC

WeaknessesCWE-670

Technical details

References

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