CVE-2025-43851
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 · uneditedRetrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The model_choose variable takes user input (e.g. a path to a model) and passes it to the uvr function in vr.py. In uvr , a new instance of AudioPre class is created with the model_path attribute containing the aformentioned user input. In the AudioPre class, the user input, is used to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist.
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 · high confidenceRetrieval-based-Voice-Conversion-WebUI versions 2.2.231006 and prior are vulnerable to unsafe deserialization leading to remote code execution. The vulnerability exists because user-controlled input (model_path) is passed to the uvr function and subsequently used in the AudioPre class with torch.load without safe loading options, allowing attackers to deserialize malicious payloads.
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<= 2.2.231006CVSS 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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Identify RVC WebUI installation and versionLocate the Retrieval-based-Voice-Conversion-WebUI installation directory and check the version file or git tag. Common locations include /home/user/RVC or C:\RVC. Look for a version indicator in the main script or README file.Affected if The installed version is 2.2.231006 or any version prior to it.
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Verify torch.load usage in AudioPre classSearch the codebase for the AudioPre class definition and examine how torch.load is called. Look for the uvr function that handles the model_path parameter and trace how it flows to torch.load.Affected if The code uses torch.load without the weights_only=True parameter, allowing unsafe deserialization.
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Confirm application network exposureCheck the application launch script or configuration to determine if the web interface is bound to a network interface (0.0.0.0) versus localhost only. Look at the --share flag or similar web server configuration.Affected if The application is exposed to network access, allowing remote attackers to supply malicious model_path values.
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Inspect external input handling for model_pathExamine the API endpoints or web routes that accept the model_path parameter. Determine if user-supplied values can directly reach the vulnerable uvr function without validation.Affected if User-controlled input for model_path is accepted and passed directly to the vulnerable code path without sanitization.
A user is affected if they are running RVC WebUI version 2.2.231006 or earlier with the application network-exposed and the torch.load call lacking weights_only=True protection.
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 dataAs no vendor patch exists, immediately restrict network access to the application, implement input validation on model_path to only allow trusted paths, and modify torch.load calls to use weights_only=True parameter to prevent unsafe deserialization.
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- Review / QA4.0 h
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Free · runs locallyCheck whether your project pulls in CVE-2025-43851 — 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-2025-43851 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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- Version or environment caveats, and links to real fixes
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