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VulnerabilityPublished

CVE-2025-49838: RVC-Boss GPT-SoVITS · Deserialization of Untrusted Data

Affects RVC-Boss GPT-SoVITSSource CVE Database V5

0

Public exploit available · CVSS 8.9 High.

Data as of 26 Oct 2026, 14:05 UTC

CVSS 4.0 base score
8.9High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.7% chance of exploitation in 30 days – higher than 55% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 15 Jul 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: evidence found.

    CVSS exploit maturity: proof of concept public

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), CVSS vector, the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
GitHubrvc-boss/GPT-SoVITSpkg:github/rvc-boss/GPT-SoVITSOther threatsAffected
  • <=20250228v3
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

European organizations should implement immediate mitigations to reduce risk. First, restrict access to the GPT-SoVITS-WebUI service to trusted networks or VPNs to limit exposure. Employ network-level controls such as firewalls and intrusion detection systems to monitor and block suspicious requests targeting model loading functionality. Validate and sanitize all user inputs rigorously, especially those specifying model paths, to prevent arbitrary file loading. Where possible, disable or restrict the use of torch.load on untrusted inputs or replace it with safer deserialization methods that do not allow code execution. Implement application-level sandboxing or containerization to isolate the GPT-SoVITS-WebUI environment, limiting the impact of potential exploitation. Monitor logs for unusual activity related to model loading or file access. Maintain an inventory of affected versions and plan for rapid patch deployment once a fix becomes available. Engage with the vendor or open-source community to track patch releases and security advisories. Finally, conduct security awareness training for developers and administrators on the risks of unsafe deserialization and secure coding practices.

Description

GPT-SoVITS-WebUI is a voice conversion and text-to-speech webUI. In versions 20250228v3 and prior, there is an unsafe deserialization vulnerability in vr.py AudioPreDeEcho. The model_choose variable takes user input (e.g.a path to a model) and passes it to the uvr function. In uvr, a new instance of AudioPreDeEcho class is created with the model_path attribute containing the aforementioned user input (here called locally model_name). Note that in this step the .pth extension is added to the path. In the AudioPreDeEcho class, the user input, here called model_path, is used to load the model on that path with torch.load, which can lead to unsafe deserialization. At time of publication, no known patched versions are available.

References

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