{"answers":{"affected":"It affects 1 product.","exploited":"There is no known exploitation of CVE-2025-49837 in the wild and no public exploit code.","fix":"No fix has been published for CVE-2025-49837 yet. Limit exposure of the affected software until one is available.","what":"CVE-2025-49837 is a high-severity unsafe deserialization vulnerability in RVC-Boss GPT-SoVITS, published on 15 Jul 2025. An attacker can exploit it over the internet without logging in, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2025-49837 and fix it if it is affected.\n\nWhat it is: CVE-2025-49837 is a high-severity unsafe deserialization vulnerability in RVC-Boss GPT-SoVITS, published on 15 Jul 2025. An attacker can exploit it over the internet without logging in, with no action from the victim.\nExploitation: There is no known exploitation of CVE-2025-49837 in the wild and no public exploit code.\n\nAffected product: RVC-Boss GPT-SoVITS. No package-level version data is available, so check the vendor advisory linked from the reference page.\n\nTask:\n1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.\n2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.\n3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.\n4. Run the tests and summarise what changed and why.\n5. If nothing in the project is affected, say so and change nothing.\n\nReference: https://insights.sbomify.com/CVE-2025-49837/ (Markdown: https://insights.sbomify.com/CVE-2025-49837/index.md)","id":"CVE-2025-49837","markdown":"https://insights.sbomify.com/CVE-2025-49837/index.md","name":"CVE-2025-49837","record":{"aliases":[],"analysis":{"component_type":"web_application","fix_type":"no_fix_stated","impacts":["code_execution"],"network_reachable":"yes","non_default_config":false,"product_category":"GPT-SoVITS WebUI","requires_auth":"none","summary":"An attacker can execute arbitrary code by providing a malicious model path to the GPT-SoVITS WebUI, which triggers unsafe deserialization via torch.load.","user_interaction":"not_required","vuln_class":"deserialization"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"gpt-sovits-webui","vendor":"rvc-boss"}],"cvss":{"score":8.9,"severity":"high","source":"cna","vector":"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","version":"4.0"},"cwes":[{"id":"CWE-502","name":"Deserialization of Untrusted Data"}],"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.","ecosystems":[],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"none_known"},"has_fix":false,"headline":"GHSL-2025-049: GPT-SoVITS Deserialization of Untrusted Data vulnerability","id":"CVE-2025-49837","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":null,"product":null,"products":[],"type":"deserialization","year":"2025"},"n_packages":0,"n_references":5,"next":{"headline":"GHSL-2025-050: GPT-SoVITS Deserialization of Untrusted Data vulnerability","id":"CVE-2025-49838"},"packages":[],"prev":{"headline":"GHSL-2025-048: GPT-SoVITS Command Injection vulnerability","id":"CVE-2025-49836"},"products":["GPT-SoVITS"],"published":"2025-07-15","related":[{"cvss_score":8.9,"headline":"GHSL-2025-045: GPT-SoVITS Command Injection vulnerability","id":"CVE-2025-49833","kev_date_added":null,"published":"2025-07-15"},{"cvss_score":8.9,"headline":"GHSL-2025-046: GPT-SoVITS Command Injection vulnerability","id":"CVE-2025-49834","kev_date_added":null,"published":"2025-07-15"},{"cvss_score":8.9,"headline":"GHSL-2025-047: GPT-SoVITS Command Injection vulnerability","id":"CVE-2025-49835","kev_date_added":null,"published":"2025-07-15"},{"cvss_score":8.9,"headline":"GHSL-2025-048: GPT-SoVITS Command Injection vulnerability","id":"CVE-2025-49836","kev_date_added":null,"published":"2025-07-15"},{"cvss_score":8.9,"headline":"GHSL-2025-050: GPT-SoVITS Deserialization of Untrusted Data vulnerability","id":"CVE-2025-49838","kev_date_added":null,"published":"2025-07-15"},{"cvss_score":8.9,"headline":"GHSL-2025-051: GPT-SoVITS Deserialization of Untrusted Data vulnerability","id":"CVE-2025-49839","kev_date_added":null,"published":"2025-07-15"}],"sources":[{"class":"attribution","licence":"CVE Terms of Use (MITRE)","name":"CVE List","prefix":"CVE"},{"class":"attribution","licence":"US public information, NVD API terms","name":"NVD"},{"class":"attribution","licence":"CWE Terms of Use","name":"CWE (MITRE)"},{"class":"attribution","licence":"FIRST CVSS licence","name":"CVSS (FIRST)"}],"ssvc":{"automatable":"yes","exploitation":"none","technical_impact":"total"},"state":"PUBLISHED","updated":"2025-07-16","vendors":["RVC-Boss"]},"summary":"An attacker can execute arbitrary code by providing a malicious model path to the GPT-SoVITS WebUI, which triggers unsafe deserialization via torch.load.","url":"https://insights.sbomify.com/CVE-2025-49837/"}