CVE-2025-23323VulnerabilityPublished 6 Aug 2025

CVE-2025-23323: NVIDIA Triton Inference Server · Integer Overflow or Wraparound

Affects NVIDIA Triton Inference ServerSource CVE Database V5

Not known to be exploited · CVSS 7.5 High : upgrade to 25.05 soon.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score

7.5High

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

EPSS: 0.5% chance of exploitation in 30 days – higher than 46% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 25.05

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 6 Aug 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 2026-10-25.

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

Upgrade NVIDIA Triton Inference Server to 25.05.

Affected software

Product	Affected	Fixed in
NVIDIA Triton Inference Server	Affected <25.05	Fixed in 25.05

AI-suggested

To mitigate this vulnerability effectively, European organizations should prioritize upgrading the NVIDIA Triton Inference Server to version 25.05 or later, where the issue is resolved. Until patching is possible, organizations should implement strict input validation and filtering at network boundaries to block malformed or suspicious requests targeting the inference server. Deploying Web Application Firewalls (WAFs) or Intrusion Prevention Systems (IPS) with custom rules to detect anomalous request patterns can reduce exposure. Network segmentation should be employed to isolate the Triton server from less trusted networks and limit access to only necessary clients. Monitoring and alerting on server crashes or unusual behavior can provide early detection of exploitation attempts. Additionally, organizations should review their AI deployment architectures to ensure redundancy and failover mechanisms are in place, minimizing service disruption if a DoS occurs. Finally, maintaining up-to-date threat intelligence feeds and collaborating with NVIDIA's security advisories will help organizations stay informed about any emerging exploits or patches.

Description

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where a user could cause an integer overflow or wraparound, leading to a segmentation fault, by providing an invalid request. A successful exploit of this vulnerability might lead to denial of service.

Impact

For European organizations, the impact of this vulnerability can be substantial, especially for those leveraging AI and machine learning services in critical sectors such as finance, healthcare, automotive, and manufacturing. The Triton Inference Server is often integrated into AI pipelines for real-time decision-making, predictive analytics, and automation. A denial of service caused by this vulnerability could interrupt these services, leading to operational downtime, loss of productivity, and potential financial losses. In healthcare, for example, AI models used for diagnostics or patient monitoring could become unavailable, affecting patient care. In finance, disruption of AI-driven fraud detection or trading algorithms could increase risk exposure. Additionally, organizations relying on cloud or edge deployments of Triton may face cascading effects if the server is part of a larger distributed system. Given the vulnerability requires no privileges or user interaction, attackers could exploit it remotely, increasing the risk of widespread disruption. While no data breach risk is present, the availability impact alone warrants urgent attention in environments where AI services are business-critical.

CWE-190Integer Overflow or Wraparound (opens in a new tab)
Base weaknessLikelihood of exploit: Medium
The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.
Requirements
Ensure that all protocols are strictly defined, such that all out-of-bounds behavior can be identified simply, and require strict conformance to the protocol.
Requirements · Language Selection
Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
Architecture and Design · Libraries or Frameworks
Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
OWASP ASVS 4.0.3
V5.4.3 (opens in a new tab)
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
Attack patterns
Forced Integer Overflow (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

Community reviews

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 6 Aug 2025, 13:18 UTC

WeaknessesCWE-190

Technical details

References

Community reviews

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