CVE-2025-23318
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 · uneditedNVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause an out-of-bounds write. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure.
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 confidenceNVIDIA Triton Inference Server contains an out-of-bounds write vulnerability in its Python backend for both Windows and Linux platforms. An attacker could exploit this memory corruption issue to achieve code execution, cause denial of service, tamper with data, or disclose information.
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< 25.07CVSS 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 checksWork through these to decide whether this CVE applies to you.
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Check if Triton Inference Server is installed or runningLook for triton-server process (ps aux | grep triton), check for /opt/tritonserver directory, or if running containerized, list running containers (docker ps) for tritonserver imagesAffected if Triton Inference Server is present in the environment
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Determine the installed Triton Inference Server versionIf binary: run tritonserver --version or check the executable's metadata. If container: inspect the image tag (docker images) or check /opt/tritonserver/version.json if accessible. Compare the version number to 25.07Affected if Version is lower than 25.07 (e.g., 25.06, 25.05, older releases)
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Verify the Python backend is in useCheck Triton model repository for Python model configurations (config.pbtxt files with backend: "python"), or query Triton metrics endpoint (http://localhost:8002/metrics) for python backend activity, or review model repository structureAffected if Python backend is configured or actively processing requests for any model
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Check network exposure of Triton inference endpointReview firewall rules or security groups allowing access to Triton HTTP/gRPC ports (typically 8000, 8001, 8002). Check if Triton is bound to 0.0.0.0 or an exposed interfaceAffected if Triton server is accessible from untrusted network segments (internet or less privileged zones)
Environment is affected if Triton Inference Server with version below 25.07 is running with the Python backend enabled and accessible to potential attackers.
Generated from the published advisory. Verify against your own configuration.
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 · scoped25.07
Apply the vendor patch when released by NVIDIA; until then, restrict network access to the Triton Inference Server and monitor for suspicious activity targeting the Python backend.
Triton Inference Server 25.07 or later
- Upgrade Triton Inference Server to version 25.07 or later
- For container deployments: Pull the updated NVIDIA Triton Inference Server image with tag 25.07 or newer (e.g., nvcr.io/nvidia/tritonserver:25.07-py3)
- For direct installations: Download and install Triton Inference Server version 25.07 or later from NVIDIA's official repositories
- Restart the Triton Inference Server service to apply the updated version
- Verify the running version matches 25.07 or later using the server's metadata endpoint or version check
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation4.0 h
- Implementation8.0 h
- Testing12.0 h
- Review / QA4.0 h
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Free · runs locallyCheck whether your project pulls in CVE-2025-23318 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2025-23318 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Verified mitigations, workarounds, and config changes
- Version or environment caveats, and links to real fixes
- No weaponised exploit code, or anything meant to cause harm
- No spam, self-promotion, credentials, or personal data