CVE-2025-23327: 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 26 Oct 2026, 10:12 UTC
- EPSS
- 0.5% chance of exploitation in 30 days – higher than 44% 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:H/PR:L/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 26 Oct 2026.
What to do
Upgrade NVIDIA Triton Inference Server to 25.05.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIA Triton Inference Server | Affected
| Fixed in
|
AI-suggested
- Immediate upgrade to NVIDIA Triton Inference Server version 25.05 or later once the patch is officially released to remediate the integer overflow vulnerability.
- Implement strict input validation and sanitization at the application layer to detect and reject malformed or suspicious inference requests that could trigger the overflow.
- Employ network segmentation and firewall rules to restrict access to the Triton Inference Server only to trusted internal systems and authenticated users, minimizing exposure to external attackers.
- Monitor server logs and network traffic for anomalous patterns indicative of exploitation attempts, such as unusual input sizes or repeated failed requests.
- Apply the principle of least privilege for accounts interacting with the inference server to reduce the risk posed by compromised credentials.
- Use runtime application self-protection (RASP) or host-based intrusion detection systems (HIDS) to detect and block abnormal behavior at runtime.
- Establish incident response procedures specific to AI infrastructure to quickly isolate and remediate compromised inference servers.
- Coordinate with NVIDIA support and subscribe to security advisories to receive timely updates on patches and exploit developments.
Description
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability where an attacker could cause an integer overflow through specially crafted inputs. A successful exploit of this vulnerability might lead to denial of service and data tampering.