CVE-2025-23319: NVIDIA Triton Inference Server · Buffer Access with Incorrect Length Value
Affects NVIDIA Triton Inference ServerSource CVE Database V5
Not known to be exploited · CVSS 8.1 High : upgrade to 25.07 soon.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 1.5% chance of exploitation in 30 days – higher than 75% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 25.07
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:HExploitation 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.
What to do
Upgrade NVIDIA Triton Inference Server to 25.07.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIA Triton Inference Server | Affected
| Fixed in
|
AI-suggested
European organizations should prioritize upgrading the NVIDIA Triton Inference Server to version 25.07 or later, where this vulnerability is addressed. Until patching is possible, organizations should implement network-level controls to restrict access to the Triton server, such as firewall rules limiting inbound traffic to trusted sources and using VPNs or private networks for management interfaces. Monitoring and logging of Triton server requests should be enhanced to detect anomalous or malformed requests indicative of exploitation attempts. Employing runtime application self-protection (RASP) or endpoint detection and response (EDR) solutions can help identify suspicious behaviors related to this vulnerability. Additionally, organizations should review and harden the configuration of the Python backend, disabling unnecessary features or interfaces if feasible. Regular vulnerability scanning and penetration testing focused on AI infrastructure components can help identify exposure. Finally, integrating this vulnerability into incident response plans and ensuring teams are aware of the potential threat will improve readiness.
Description
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause an out-of-bounds write by sending a request. A successful exploit of this vulnerability might lead to remote code execution, denial of service, data tampering, or information disclosure.