- Description: An attacker provides or substitutes a legitimate TTS model with a maliciously crafted one. This model could be trained to generate offensive or misleading speech under specific inputs, or potentially exploit vulnerabilities during model loading for code execution (though less likely in typical TTS usage, but theoretically possible). The attacker might distribute this malicious model through unofficial channels or compromise model repositories.
- Impact: Reputational damage due to offensive or inappropriate speech generation, dissemination of misinformation through manipulated audio, potential system compromise if model loading vulnerabilities are exploited.
- TTS Component Affected: Model loading mechanism, TTS model files.
- Risk Severity: High
- Mitigation Strategies:
- Model Source Control: Strictly use TTS models only from trusted and official sources like Coqui-AI or internally vetted and secured models.
- Model Validation: Implement robust validation mechanisms such as checksum or digital signature verification for all TTS models before loading them into the application.
- Input Sanitization (Indirect): While not directly preventing malicious models, sanitize input text to reduce the likelihood of triggering unintended or malicious behavior within a compromised model.
Threat: Model Corruption or Tampering
- Description: An attacker gains unauthorized access to the storage or transfer channels of TTS models and corrupts or tampers with them. This could occur through network interception during model download, or by compromising the server or storage system where models are hosted. Corruption can lead to unpredictable TTS behavior or failures, while tampering could introduce malicious functionalities similar to backdoored models.
- Impact: Service disruption due to TTS engine failures or unpredictable output, unreliable and potentially misleading audio generation, potential security compromise if tampering introduces malicious behavior execution.
- TTS Component Affected: Model storage, model loading mechanism, TTS model files.
- Risk Severity: High
- Mitigation Strategies:
- Secure Storage: Store TTS models in highly secure locations with strict access control lists and monitoring to prevent unauthorized access and modification.
- Integrity Checks: Implement mandatory integrity checks using strong checksums or cryptographic hashes to verify model integrity before loading and after transfer or storage.
- Secure Transfer: Enforce the use of HTTPS or other secure file transfer protocols for all model downloads and transfers to prevent interception and tampering during transit.
- Description: Coqui TTS relies on numerous external libraries, including PyTorch, ONNX Runtime, and various audio processing libraries. These dependencies may contain critical security vulnerabilities. If these vulnerabilities are not promptly patched in the application's environment, an attacker could exploit them to compromise the application or the underlying system. Exploitation could occur through crafted inputs processed by TTS or through network-based attacks targeting vulnerable dependency components.
- Impact: Full system compromise, data breaches, arbitrary code execution, denial of service, and other severe security breaches due to exploited vulnerabilities in underlying dependencies.
- TTS Component Affected: Underlying dependencies of Coqui TTS (PyTorch, ONNX Runtime, etc.).
- Risk Severity: High
- Mitigation Strategies:
- Dependency Scanning and Management: Implement automated dependency scanning using vulnerability scanning tools to continuously monitor for known vulnerabilities in Coqui TTS dependencies.
- Proactive Dependency Updates: Establish a process for promptly updating Coqui TTS and all its dependencies to the latest versions, especially security patches, as soon as they are released.
- Dependency Pinning and Review: Utilize dependency pinning to ensure consistent and controlled dependency versions. Regularly review and audit dependencies for security and maintainability. Consider using Software Bill of Materials (SBOM) to track and manage dependencies effectively.