CVE-2025-33202: NVIDIA Triton Inference Server · Stack-based Buffer Overflow
Affects NVIDIA Triton Inference ServerSource CVE Database V5
Not known to be exploited · CVSS 6.5 Medium : upgrade to 25.09 when convenient.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 0.4% chance of exploitation in 30 days – higher than 40% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 25.09
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HExploitation evidence
Disclosed: evidence found.
CVE published 11 Nov 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 25.09.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIA Triton Inference Server | Affected
| Fixed in
|
AI-suggested
1. Apply the official patch or upgrade to NVIDIA Triton Inference Server version 25.09 or later as soon as it becomes available. 2. Until patches are deployed, restrict network access to the Triton server using firewalls or network segmentation to limit exposure to trusted users and systems only. 3. Implement input validation and payload size restrictions at the network perimeter or application gateway to block abnormally large requests. 4. Monitor server logs and network traffic for unusual payload sizes or repeated malformed requests that could indicate exploitation attempts. 5. Employ runtime protections such as stack canaries or address space layout randomization (ASLR) if supported by the deployment environment to mitigate buffer overflow impacts. 6. Conduct regular security assessments and penetration testing focused on AI infrastructure to identify and remediate similar vulnerabilities proactively. 7. Establish incident response plans specific to AI service disruptions to minimize downtime in case of exploitation.
Description
NVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where an attacker could cause a stack overflow by sending extra-large payloads. A successful exploit of this vulnerability might lead to denial of service.