Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support
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Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
In `examples/complete_voice_engine.py`, the WebSocket endpoint reads outsider-supplied audio bytes (`websocket.iter_bytes()`), which the pipeline transcribes into `transcription.message` and then passes into the LLM agent (`GeminiAgent.process()` → `generate_response(transcription.message)`), so free text produced from user input is ingested at runtime without selecting a specific trusted item.
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