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CVE-2025-23311VulnerabilityPublished

CVE-2025-23311: NVIDIA Triton Inference Server · Stack-based Buffer Overflow

Affects NVIDIA Triton Inference ServerSource CVE Database V5

0

Not known to be exploited · CVSS 9.8 Critical : upgrade to 25.07 as a priority.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.1 base score
9.8Critical
How severe the flaw is on the 0–10 CVSS scale.
EPSS
2.6% chance of exploitation in 30 days – higher than 85% 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:L/PR:N/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 2026-10-26.

What to do

Upgrade NVIDIA Triton Inference Server to 25.07.

Affected software

ProductAffectedFixed in
NVIDIA Triton Inference ServerAffected
  • <25.07
Fixed in
  • 25.07

AI-suggested

1. Immediate upgrade to NVIDIA Triton Inference Server version 25.07 or later, where the vulnerability is patched, is the most effective mitigation. 2. Until patching is possible, restrict network access to the Triton Inference Server to trusted internal networks and implement strict firewall rules to block untrusted HTTP traffic. 3. Employ Web Application Firewalls (WAFs) or intrusion prevention systems (IPS) with custom rules to detect and block malformed HTTP requests targeting the inference server. 4. Monitor server logs and network traffic for unusual or suspicious HTTP requests that could indicate exploitation attempts. 5. Conduct regular security assessments and penetration testing focused on AI infrastructure to identify and remediate similar vulnerabilities. 6. Implement network segmentation to isolate AI inference servers from critical business systems to limit potential lateral movement if compromised. 7. Ensure robust incident response plans are in place to quickly contain and remediate any exploitation events.

Description

NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a stack overflow through specially crafted HTTP requests. A successful exploit of this vulnerability might lead to remote code execution, denial of service, information disclosure, or data tampering.

References

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