VulnerabilityPublished 3 Dec 2025

CVE-2025-33211: NVIDIA Triton Inference Server · Improper Validation of Specified Quantity in Input

Affects NVIDIA Triton Inference ServerSource CVE Database V5

Not known to be exploited · CVSS 7.5 High : upgrade to 25.10 soon.

Data as of 26 Oct 2026, 14:05 UTC

CVSS 3.1 base score

7.5High

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

EPSS: 0.6% chance of exploitation in 30 days – higher than 52% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 25.10

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

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: High

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

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 3 Dec 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 26 Oct 2026.

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 or the CVSS exploit maturity 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

Upgrade NVIDIA Triton Inference Server to 25.10.

Affected software

Product	Affected	Fixed in
NVIDIA Triton Inference Server	Affected <25.10	Fixed in 25.10

AI-suggested

Upgrade NVIDIA Triton Inference Server to version r25.10 or later as soon as the patch becomes available to address the improper input validation issue.
Until patching is possible, restrict network access to the Triton server using firewalls or network segmentation to limit exposure to trusted hosts only.
Implement monitoring and alerting for unusual input patterns or service disruptions on Triton servers to detect potential exploitation attempts early.
Employ rate limiting and input validation proxies where feasible to filter malformed or suspicious requests before they reach the server.
Conduct regular security assessments and penetration testing on AI infrastructure to identify and remediate similar vulnerabilities proactively.
Maintain an incident response plan that includes AI service disruption scenarios to minimize downtime impact.
Coordinate with NVIDIA support and subscribe to security advisories for timely updates and patches.

Description

NVIDIA Triton Server for Linux contains a vulnerability where an attacker may cause an improper validation of specified quantity in input. A successful exploit of this vulnerability may lead to denial of service.

Impact

For European organizations, the primary impact of CVE-2025-33211 is operational disruption due to denial of service on AI inference workloads. Industries heavily reliant on AI, such as automotive manufacturing, financial services, healthcare, and research institutions, may experience interruptions in critical services, leading to productivity losses and potential financial damage. Since Triton Inference Server often runs in cloud or on-premises GPU clusters, a successful DoS could degrade AI model availability, affecting real-time decision-making systems or customer-facing AI applications. The absence of confidentiality or integrity impact reduces the risk of data breaches but does not diminish the operational risk. Additionally, organizations with regulatory requirements for service availability may face compliance challenges if the vulnerability is exploited. The threat is heightened in environments where Triton servers are exposed to external or less trusted internal networks without adequate segmentation or access controls.

CWE-1284Improper Validation of Specified Quantity in Input (opens in a new tab)
Base weakness
The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.
Implementation · Input Validation
Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
OWASP ASVS 4.0.3
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
V5.1.3 (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 10 Dec 2025, 18:36 UTC

WeaknessesCWE-1284

Technical details

References

Community reviews

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