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VulnerabilityPublished

CVE-2025-49837: 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

  1. Immediately restrict access to GPT-SoVITS-WebUI instances to trusted internal networks or VPNs to reduce exposure.
  2. Implement strict input validation and sanitization on the model_choose parameter to prevent arbitrary file paths or untrusted inputs.
  3. Disable or replace the use of torch.load for loading models with safer alternatives that do not perform arbitrary deserialization, such as using torch.jit.load or custom deserialization methods that validate input.
  4. Monitor application logs for unusual or unexpected model loading requests or file access patterns.
  5. Employ application-layer firewalls or web application firewalls (WAFs) with rules to detect and block suspicious payloads targeting this vulnerability.
  6. Prepare for patch deployment by tracking vendor updates and applying them promptly once available.
  7. Conduct security reviews and code audits of any custom modifications to the GPT-SoVITS-WebUI to identify similar unsafe deserialization patterns.

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 AudioPre. 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 AudioPre 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 AudioPre 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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