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Ditto — agentic threat model

8.2AIVSS 8.2 · High

Ditto presents a high-consequence data privacy risk due to its handling of sensitive personal health information (PHI) combined with a low-to-moderate agentic profile focused on document parsing and sharing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 0.65Factor sum 2.6/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.20
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.30
Persistent Memory
0.60
Contextual Awareness
0.50
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.40
Opacity & Reflexivity
0.40

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely relies on third-party LLMs for document understanding. Key threats include prompt injection leading to medical misinterpretation or diagnostic hallucination.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — processes highly sensitive health documents and appointment data. Key threats include unauthorized data exfiltration of PHI and lack of secure local/cloud vector storage encryption.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestration is required to parse documents and manage sharing workflows. Key threats include insecure tool integration with calendar APIs or sharing mechanisms.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — likely hosted as a mobile application with cloud backend support. Key threats include insecure local storage on mobile devices and API endpoint exposure.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no mention of medical-grade guardrails or output verification. Key threats include silent failures in document parsing and lack of clinical accuracy monitoring.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — handling health data demands strict compliance (e.g., HIPAA, GDPR), but no specific compliance certifications or access controls are detailed.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — sharing features imply user-to-user or user-to-provider data flows. Key threats include unauthorized data sharing or interception by external entities.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).