CVE-2025-23254
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 TensorRT-LLM for any platform contains a vulnerability in python executor where an attacker may cause a data validation issue by local access to the TRTLLM server. A successful exploit of this vulnerability may lead to code execution, 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 confidenceNVIDIA TensorRT-LLM contains a data validation vulnerability in its python executor component. An attacker with local access to the TRTLLM server can exploit improper input validation to potentially achieve code execution, information disclosure, or data tampering. The vulnerability stems from insufficient validation of data processed by the python executor before use.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
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
- Local
- Complexity
- Low
- Privileges
- Low
- User interaction
- None
- Scope
- Changed
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/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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Identify if TensorRT-LLM is installedRun 'pip show tensorrt-llm' or check for the tensorrt_llm package in your Python environment using 'pip list | grep -i tensorrt'Affected if The package is not found, then not affected; if found, proceed to version check
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Determine the installed TensorRT-LLM versionRun 'pip show tensorrt-llm' and note the Version field, or use 'python -c "import tensorrt_llm; print(tensorrt_llm.__version__)"' if availableAffected if Compare your version against any official NVIDIA security advisories for CVE-2025-23254; if your version is older than the patched release, it may be affected
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Verify the python executor component is in useCheck your TensorRT-LLM server configuration files or runtime logs for references to the python executor (often invoked via 'tensorrt-llm-serve' or custom executor configurations)Affected if The python executor is explicitly enabled or configured in your deployment, making it a potential attack vector
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Assess local access exposure to the TRTLLM serverReview network configuration and access controls: check if the TRTLLM server is bound to localhost only (127.0.0.1) or exposed on a network interface, and verify which user accounts have local access to the hostAffected if The server is accessible to untrusted local users or exposed beyond localhost, combined with the vulnerable python executor component
You are likely affected if TensorRT-LLM with the python executor component is installed and accessible to untrusted local users, regardless of version, unless NVIDIA has released a specific patch for this CVE.
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.
From vendor dataImplement robust input validation and sanitization in the python executor component to ensure all data is properly validated before processing. Restrict local access to the TRTLLM server and follow least-privilege principles to reduce attack surface.
- Consultation6.0 h
- Implementation12.0 h
- Testing10.0 h
- Review / QA6.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $9,504.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2025-23254 — 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-2025-23254 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
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