detecting-deepfake-audio-in-vishing-attacks

No explicit malicious code or covert data theft/exfiltration is evident in this module. The main security concern is the optional loading of a user-supplied joblib model via joblib.load(model_path). Because joblib deserializes the artifact, providing an attacker-controlled .joblib file can lead to arbitrary code execution during loading. If model artifacts are strictly trusted and protected (e.g., obtained from a secure, immutable source and not attacker-writable), the remaining behavior is consistent with offline local audio analysis and JSON reporting.