Triton Inference ServerApplication · Nvidia

CVE-2025-23316

CRITICAL · 9.8 CVSS v3.1 Published 2025-09-17
Fix available
A fix is available. Upgrade to 25.08 or later.
See remediation →
100/100
Remediation priority · Urgent
Remotely reachable No privileges Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause a remote code execution by manipulating the model name parameter in the model control APIs. A successful exploit of this vulnerability might lead to remote code execution, denial of service, information disclosure, and data tampering.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

NVIDIA Triton Inference Server's Python backend has a code injection vulnerability in the model control APIs. By manipulating the model name parameter, an attacker can inject and execute arbitrary code on the server. This stems from insufficient validation/sanitization of the model name input before it's used in backend processing operations.

MitigationUpgrade to the NVIDIA-provided patch which implements proper input validation and sanitization for model name parameters in the Python backend. If immediate patching is not possible, restrict network access to the model control APIs and implement additional authentication layers.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
Triton Inference ServerApplication
Affected:< 25.08

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify installed Triton Inference Server version
    Check the Triton server version by querying the server's API endpoint (typically GET /v2/health/ready or checking server logs/containers) or by running 'tritonserver --version' if accessible
    Affected if The installed version is any release prior to 25.08 (e.g., 25.03, 24.x, earlier)
  2. Verify Python backend is enabled
    Check the Triton server configuration (config.pbtxt) for the 'python' backend or inspect running backend processes/containers to confirm the Python backend is loaded
    Affected if The Python backend is loaded and actively processing model requests
  3. Confirm model control API accessibility
    Inspect Triton server network configuration and firewall settings to determine if the model control endpoints (typically under /v2/models/) are exposed to network access
    Affected if The model control APIs are reachable over the network without additional authentication or network segmentation
  4. Check for custom model name validation
    Review any custom middleware, preprocessing scripts, or proxy configurations that sit in front of Triton to see if model name parameters are validated before reaching the Python backend
    Affected if No custom input validation exists on model name parameters passing to the Python backend

The environment is affected if running any Triton Inference Server version prior to 25.08 with the Python backend enabled and its model control APIs accessible over the network.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 25.08 or later
Fixed in 25.08
Interim mitigation

Upgrade to the NVIDIA-provided patch which implements proper input validation and sanitization for model name parameters in the Python backend. If immediate patching is not possible, restrict network access to the model control APIs and implement additional authentication layers.

Recommended fix Moderate confidence

25.08

  1. Upgrade Triton Inference Server to version 25.08 or later
  2. Verify the upgrade by checking the server version after installation
  3. Test that model control APIs function correctly with the updated version

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Triton Inference Server Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing6.0 h
  • Review / QA4.0 h
22.0 hours of engineering $3,860
Get the upgrade done

An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $6,176.

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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-23316 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
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  • No spam, self-promotion, credentials, or personal data