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CVE-2025-49841VulnerabilityPublished Updated

CVE-2025-49841: RVC-Boss GPT-SoVITS · Deserialization of Untrusted Data

Affects RVC-Boss GPT-SoVITSSource CVE Database V5

0

Not known to be exploited · CVSS 8.9 High.

Data as of 25 Oct 2026, 19:02 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: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  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), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

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. Immediate mitigation should include isolating GPT-SoVITS-WebUI instances from public networks to reduce exposure. 2. Implement strict input validation and sanitization on the SoVITS_dropdown input to prevent malicious payloads from being processed. 3. Employ application-layer firewalls or intrusion detection/prevention systems to monitor and block suspicious deserialization attempts targeting torch.load. 4. Consider disabling or restricting the use of torch.load for loading models from untrusted sources until a patch is available. 5. Monitor vendor communications and security advisories closely for updates or patches addressing this vulnerability. 6. As a longer-term solution, refactor the codebase to replace unsafe deserialization with safer alternatives, such as using secure serialization libraries or verifying the integrity and authenticity of model files before loading. 7. Conduct regular security audits and penetration testing focusing on deserialization vulnerabilities in machine learning model loading components.

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 process_ckpt.py. The SoVITS_dropdown variable takes user input and passes it to the load_sovits_new function in process_ckpt.py. In load_sovits_new, the user input, here sovits_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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