CVE-2025-23329: NVIDIA Triton Inference Server · CWE-284
Affects NVIDIA Triton Inference ServerSource CVE Database V5
Not known to be exploited · CVSS 7.5 High : upgrade to 25.08 soon.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 0.3% chance of exploitation in 30 days – higher than 28% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 25.08
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HExploitation evidence
Disclosed: evidence found.
CVE published 17 Sep 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.
What to do
Upgrade NVIDIA Triton Inference Server to 25.08.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIA Triton Inference Server | Affected
| Fixed in
|
AI-suggested
To mitigate this vulnerability, European organizations should immediately upgrade NVIDIA Triton Inference Server to version 25.08 or later, where the vulnerability is patched. If you cannot patch yet, organizations should restrict network access to the Triton Inference Server, ensuring it is not exposed to untrusted or public networks. Implement network segmentation and firewall rules to limit access only to trusted hosts and internal networks. Additionally, monitor server logs and network traffic for unusual access patterns to the shared memory region or unexpected crashes that could indicate exploitation attempts. Employ host-based intrusion detection systems (HIDS) to detect anomalous behavior in the Triton server process. Where possible, disable or restrict the Python backend if it is not required for the deployment to reduce the attack surface. Finally, enforce strict access controls and permissions on shared memory resources at the operating system level to prevent unauthorized access.
Description
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause memory corruption by identifying and accessing the shared memory region used by the Python backend. A successful exploit of this vulnerability might lead to denial of service.