SolverGenie — agentic threat model
SolverGenie is a low-risk, utility-focused AI assistant for solving math and physics problems via OCR. Its primary security risks are standard web application vulnerabilities, privacy of student data, and potential payment processing issues as it transitions to a subscription model, rather than agentic threats.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
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.
Uses vision-language or LLM models to perform OCR and solve math/physics problems. Vulnerable to adversarial image inputs (AI Lens) designed to break the solver, cause denial of service, or generate offensive/misaligned outputs.
Handles user-uploaded images for OCR processing. Risks include data exfiltration of sensitive user documents, lack of image sanitization, and potential privacy violations if student data is stored without consent.
Not certain from the listing — likely uses simple API wrappers rather than complex agentic orchestration frameworks, but insecure tool integration for OCR processing could be a threat.
Deployed as a React.js/TypeScript mobile UI and HTML desktop UI. Vulnerable to standard frontend exploits (XSS, CSRF) and potential server-side vulnerabilities in the backend hosting the OCR and solver APIs.
Not certain from the listing — no mention of evaluation, monitoring, or guardrails for math/physics accuracy or content filtering.
Transitioning to a subscription model ($0.99/mo). Requires robust payment security (PCI-DSS) and compliance with student privacy regulations (e.g., COPPA, GDPR) which are not detailed in the listing.
Not certain from the listing — operates as a standalone solver with no apparent multi-agent or ecosystem integrations.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).