Math AI — agentic threat model
Math AI is a low-risk, user-directed educational tool with minimal agentic capabilities, posing virtually no threat of autonomous external action or data modification. Its primary security risks are limited to model hallucinations, prompt injection, and potential client-side rendering or image-parsing vulnerabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.00 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.00 |
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 models or LLMs to parse math images and text. Vulnerable to adversarial examples (e.g., subtle image perturbations that trick the solver) and prompt injection to bypass tutoring constraints.
Not certain from the listing — No details on RAG or vector stores are provided. The agent appears to operate statelessly on user-provided inputs without a persistent knowledge base.
Orchestration is highly restricted, likely consisting of a simple single-turn prompt-response loop. There are no complex planning frameworks, tool-calling mechanisms, or agentic memory systems to exploit.
Not certain from the listing — Hosted as a browser-based service. Potential infrastructure risks include server-side image processing vulnerabilities (e.g., during photo upload analysis) or client-side XSS via LaTeX/Markdown rendering.
Not certain from the listing — No mention of output validation, mathematical verification guardrails, or logging. The primary operational risk is undetected mathematical hallucinations.
Not certain from the listing — No details on user authentication, session management, or compliance (such as COPPA, which is highly relevant for educational tools targeting learners).
The agent operates in complete isolation with no multi-agent coordination, marketplace integrations, or external ecosystem dependencies, rendering ecosystem-level threats negligible.
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 — every score is re-derived by the same automated method as an agent's public evidence changes.