Convinco — agentic threat model

Not certain from the listing — likely relies on a combination of speech-to-text (STT) and LLMs for delivery analysis. Threats include prompt injection via spoken audio (indirect injection) to manipulate feedback metrics, and potential model bias against diverse accents or speech patterns.

Not certain from the listing — processes real-time audio streams and generates text transcripts and performance metrics. Threats include unauthorized access to stored audio recordings or transcripts containing highly sensitive, unreleased business ideas or intellectual property.

Not certain from the listing — likely uses a linear pipeline rather than a complex agentic framework. Threats are minimal but include insecure parsing of transcription outputs and lack of input validation on the text sent to the evaluation module.

Not certain from the listing — requires high-bandwidth infrastructure for real-time audio processing. Threats include denial-of-service (DoS) attacks targeting the real-time analysis API and insecure temporary storage of audio files on the server.

Not certain from the listing — requires monitoring of transcription accuracy and feedback alignment. Threats include a lack of observability into LLM hallucinations during qualitative feedback generation, leading to misleading coaching advice.

Not certain from the listing — handles sensitive voice biometrics and proprietary business plans. Threats include non-compliance with biometric data privacy laws (e.g., BIPA, GDPR) and lack of explicit user consent mechanisms for voice processing.

The listing describes Convinco as a standalone, single-user coaching tool. It does not feature multi-agent collaboration or marketplace integrations, making ecosystem-level threats negligible.