Skip to main content
VulnerabilityPublished

CVE-2025-23327: NVIDIA Triton Inference Server · Integer Overflow or Wraparound

Affects NVIDIA Triton Inference ServerSource CVE Database V5

0

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

Data as of 26 Oct 2026, 17:16 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 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:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 6 Aug 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq 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

ProductAffectedFixed in
NVIDIA Triton Inference ServerAffected
  • <25.05
Fixed in
  • 25.05

AI-suggested

  1. Immediate upgrade to NVIDIA Triton Inference Server version 25.05 or later once the patch is officially released to remediate the integer overflow vulnerability.
  2. Implement strict input validation and sanitization at the application layer to detect and reject malformed or suspicious inference requests that could trigger the overflow.
  3. 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.
  4. Monitor server logs and network traffic for anomalous patterns indicative of exploitation attempts, such as unusual input sizes or repeated failed requests.
  5. Apply the principle of least privilege for accounts interacting with the inference server to reduce the risk posed by compromised credentials.
  6. Use runtime application self-protection (RASP) or host-based intrusion detection systems (HIDS) to detect and block abnormal behavior at runtime.
  7. Establish incident response procedures specific to AI infrastructure to quickly isolate and remediate compromised inference servers.
  8. 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.

References

Community reviews

Loading reviews…