CVE-2025-43847
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 ckpt_path2 variable takes user input (e.g. a path to a model) and passes it to the extract_small_model function in process_ckpt.py, which uses it 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 contain an unsafe deserialization vulnerability in process_ckpt.py. The ckpt_path2 parameter, which accepts user-supplied file paths, is passed directly to torch.load() in the extract_small_model function without validation, allowing malicious pickle payloads to execute arbitrary code.
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 installed RVC WebUI versionCheck the version file or git tag in the installation directory. Look for version markers such as a version.py file, __init__.py with version info, or git tags. Compare the version to 2.2.231006.Affected if The installed version is 2.2.231006 or any version prior to it.
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Locate the vulnerable process_ckpt.py fileSearch the RVC WebUI installation directory for the file process_ckpt.py. This file is part of the core processing modules.Affected if The file exists in the installation, indicating the vulnerable component is present.
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Inspect the extract_small_model function for unsafe torch.load()Open process_ckpt.py and locate the extract_small_model function. Check if torch.load() is called without the weights_only=True parameter and without custom unpickler validation.Affected if torch.load() is called without weights_only=True and accepts the ckpt_path2 parameter directly.
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Verify if ckpt_path2 parameter accepts user-supplied pathsExamine the function signature of extract_small_model and trace how ckpt_path2 is populated. Check if this parameter can be controlled through API endpoints, CLI arguments, or web interface inputs.Affected if The ckpt_path2 parameter can be influenced by user input without validation.
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Check for exposure to untrusted model inputsReview the application's configuration and usage patterns to determine if users can provide their own model checkpoint files. Look for model upload functionality or configuration that accepts external model paths.Affected if The application accepts model files from untrusted sources or allows arbitrary file paths to be specified.
A user is affected if they run RVC WebUI version 2.2.231006 or earlier, have the process_ckpt.py module present, and the extract_small_model function uses unsafe torch.load() with user-controllable ckpt_path2 input.
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 · scopedImplement strict path validation to ensure ckpt_path2 only points to trusted/model files within expected directories, and modify torch.load() calls to use weights_only=True or implement custom unpickler that restricts dangerous operations. Network isolation and avoiding untrusted model inputs are temporary workarounds.
- This vulnerability has no documented fix as of the publication date.
- The project maintainers have not released a patch or security update to address the unsafe deserialization in torch.load.
- Monitor the official GitHub repository (Retrieval-based-Voice-Conversion-WebUI) for future security updates.
- Consider disabling or restricting access to the affected functionality (model loading via ckpt_path2) until a fix is available.
- As a defensive measure, ensure the application is not exposed to untrusted users/networks since no patch exists.
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation6.0 h
- Implementation12.0 h
- Testing8.0 h
- Review / QA4.0 h
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Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2025-43847 — 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-2025-43847 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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