Mitra AI Phone Calling — agentic threat model
Mitra AI presents a high-risk agentic profile due to its ability to autonomously initiate and conduct phone calls using the user's caller ID, creating significant vectors for automated social engineering, vishing, and telephony fraud if compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.90 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.80 | |
| 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 — likely utilizes advanced LLMs combined with text-to-speech (TTS) and speech-to-text (STT) models. Vulnerable to prompt injection via voice (over-the-air injection) during active calls, which could hijack the agent's behavior mid-conversation.
Not certain from the listing — requires access to contact lists, call history, and real-time information gathering. Risks include data exfiltration of sensitive call transcripts and poisoning of the real-time information retrieval mechanism.
The agent orchestrates call flows, navigates automated IVR systems, and dynamically manages conversations. Framework-level vulnerabilities could allow attackers to manipulate the call logic, leading to unauthorized outbound calls or tool misuse (e.g., dialing premium numbers).
Not certain from the listing — relies on cloud hosting and telephony API integrations (e.g., Twilio). Compromise of infrastructure or API keys could allow attackers to hijack the caller ID spoofing mechanism for large-scale vishing campaigns.
Not certain from the listing — requires robust real-time guardrails to prevent the agent from being used for harassment, spam, or financial fraud. A lack of transparent logging and observability creates significant abuse potential.
The use of the user's caller ID to make calls on their behalf introduces severe identity, authentication, and compliance risks (e.g., STIR/SHAKEN, TCPA, and GDPR). Without strict verification, the platform can be abused for impersonation and social engineering.
Not certain from the listing — primarily operates as a single-agent system interacting with human recipients or automated IVR systems. Risks include cascading failures or loop conditions when interacting with other automated voice agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.