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VulnerabilityPublished

CVE-2025-49840: 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, 12:55 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 54% 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–

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AI-suggested

Given the absence of official patches, European organizations should take immediate steps to mitigate this vulnerability: 1) Restrict network access to the GPT-SoVITS-WebUI service by implementing strict firewall rules and network segmentation to limit exposure to untrusted networks. 2) Disable or restrict the functionality that allows users to specify or upload model paths, effectively preventing untrusted input from reaching torch.load. 3) Employ application-layer input validation and sanitization to ensure that only authorized and verified model files are loaded. 4) Run the GPT-SoVITS service within a hardened, isolated environment such as a container or sandbox with minimal privileges to limit the impact of potential exploitation. 5) Monitor logs and network traffic for unusual activity indicative of exploitation attempts, including unexpected torch.load calls or anomalous file access patterns. 6) Engage with the vendor or community to track patch releases and apply updates promptly once available. 7) Consider alternative voice conversion solutions without this vulnerability if immediate risk reduction is critical. These steps go beyond generic advice by focusing on controlling the specific attack vector (unsafe deserialization via torch.load) and limiting the operational exposure of the vulnerable component.

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 inference_webui.py. The GPT_dropdown variable takes user input and passes it to the change_gpt_weights function. In change_gpt_weights, the user input, here gpt_path is used to load a model with torch.load, leading to unsafe deserialization. At time of publication, no known patched versions are available.

References

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