CVE-2025-27779 in Applio
Summary
by MITRE • 03/19/2025
Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to unsafe deserialization in `model_blender.py` lines 20 and 21. `model_fusion_a` and `model_fusion_b` from voice_blender.py take user-supplied input (e.g. a path to a model) and pass that value to the `run_model_blender_script` and later to `model_blender` function, which loads these two models with `torch.load` in `model_blender.py (on lines 20-21 in 3.2.8-bugfix), which is vulnerable to unsafe deserialization. The issue can lead to remote code execution. A patch is available on the `main` branch of the Applio repository.
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Analysis
by VulDB Data Team • 08/01/2025
The vulnerability identified as CVE-2025-27779 affects Applio, a voice conversion tool that enables users to blend and fuse voice models for various applications. This security flaw resides within the model blending functionality where user-supplied inputs are processed without adequate sanitization, creating a critical pathway for malicious exploitation. The vulnerability manifests in the `model_blender.py` file at lines 20 and 21, where the application loads user-provided model files using PyTorch's `torch.load` function without proper validation mechanisms.
The technical implementation of this vulnerability follows a clear attack vector where the `model_fusion_a` and `model_fusion_b` functions in `voice_blender.py` accept user-provided paths to model files and pass these directly to the `run_model_blender_script` function. This function subsequently invokes the `model_blender` function which performs the actual loading operation using `torch.load`. The dangerous aspect occurs because PyTorch's loading mechanism does not perform adequate input validation, allowing attackers to craft malicious model files that contain serialized Python objects designed to execute arbitrary code during the deserialization process. This unsafe deserialization vulnerability represents a direct violation of secure coding practices and aligns with CWE-502, which specifically addresses unsafe deserialization of untrusted data.
The operational impact of this vulnerability is severe and potentially catastrophic for users of the affected Applio versions. Remote code execution capabilities mean that an attacker could potentially gain complete control over systems running vulnerable versions of Applio, allowing for data exfiltration, system compromise, and lateral movement within networks. The vulnerability affects all versions up to and including 3.2.8-bugfix, making it particularly concerning given the widespread use of voice conversion tools in audio processing workflows. Attackers could exploit this vulnerability by uploading malicious model files that, when loaded by the application, execute arbitrary commands on the target system with the privileges of the user running Applio.
Mitigation strategies for this vulnerability should focus on immediate patching of the affected software, as a fix is available in the main branch of the Applio repository. Organizations should also implement strict input validation measures to prevent user-supplied paths from being directly processed without sanitization. The remediation process should include verifying that all user-provided model files are validated against expected formats and that the application does not load untrusted model files without proper security checks. Additionally, system administrators should consider implementing network segmentation and monitoring to detect potential exploitation attempts, as this vulnerability could be used as a foothold for more extensive attacks. The fix addresses the core issue by ensuring that model loading operations properly validate input data and prevent the execution of malicious payloads during the deserialization process, aligning with ATT&CK technique T1059.001 for execution through command and scripting interpreter.