Cleon — agentic threat model
Cleon is a voice-based AI agent designed for customer service, presenting moderate-to-high risk due to its direct public-facing telephony interface and potential access to internal business systems, which could be exploited for vishing or data exfiltration.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — Cleon likely relies on a pipeline of Speech-to-Text (STT), a Large Language Model (LLM), and Text-to-Speech (TTS). Threats include voice-based prompt injection (adversarial audio) and model reprogramming to output inappropriate content.
Not certain from the listing — The agent 'learns your business', implying a RAG system or fine-tuning on business documents. This introduces risks of knowledge-base poisoning or unauthorized data exfiltration of proprietary business data via voice queries.
Not certain from the listing — To 'handle customer calls efficiently', the agent likely integrates with booking systems, CRMs, or databases. Insecure tool integration could allow callers to manipulate backend systems via prompt injection.
Not certain from the listing — Deployment involves telephony infrastructure (SIP/VoIP) and audio processing servers. Threats include SIP trunk hijacking, eavesdropping on voice streams, and denial-of-service attacks on the voice gateway.
Not certain from the listing — Monitoring voice interactions requires transcription logging, which risks capturing sensitive customer PII (e.g., credit card numbers spoken over the phone) in plaintext logs without proper redaction guardrails.
Not certain from the listing — Handling customer calls requires compliance with telephony regulations (e.g., TCPA, GDPR/CCPA for voice recordings) and potentially PCI-DSS if payments are processed, but no compliance controls are detailed.
Not certain from the listing — The agent primarily interacts with human customers, but could potentially route calls to other agents or automated systems, introducing risks of cascading failures during call handoffs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).