interface.ai — agentic threat model
interface.ai presents a high-risk profile due to its integration into sensitive financial services and call center automation, where compromise could lead to financial fraud, PII exfiltration, and social engineering at scale, despite likely compliance-driven guardrails.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.50 | |
| 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 uses proprietary or fine-tuned LLMs optimized for financial terminology and voice synthesis. Threats include adversarial prompt injection to bypass banking guardrails or extract system prompts.
Not certain from the listing — likely integrates with core banking databases, CRMs, and vector stores for RAG. Threats include data exfiltration of customer PII/financial records and unauthorized database queries via manipulated inputs.
Not certain from the listing — uses proprietary orchestration for voice, chat, and co-pilot experiences. Threats include insecure tool integration with banking APIs and manipulation of dialogue state to execute unauthorized actions.
Not certain from the listing — presumably hosted in secure, private cloud environments compliant with banking standards. Threats include container compromise, API gateway vulnerabilities, or denial of service on critical call center infrastructure.
Not certain from the listing — likely employs conversation logging and compliance monitoring. Threats include blind spots in detecting sophisticated prompt injection or drift in voice synthesis quality leading to social engineering.
Not certain from the listing — must align with strict financial regulations (e.g., GLBA, PCI-DSS). Threats include compliance failures, lack of robust audit trails for AI-driven transactions, and identity spoofing during voice authentication.
Not certain from the listing — operates primarily as a standalone banking assistant/co-pilot. Threats include rogue handoffs to external systems or API trust abuse during third-party integrations.
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.