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TutorGPT — agentic threat model

6.9AIVSS 6.9 · Medium

TutorGPT presents a low-to-moderate risk profile as an educational and productivity assistant. Its primary security concerns stem from its reliance on multiple third-party LLMs and the lack of visible data privacy controls for student and educator data.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.3AARS uplift 1.55Factor sum 3.3/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.20
Goal-Driven Planning
0.30
Self-Modification
0.10
Dynamic Tool Use
0.40
Persistent Memory
0.30
Contextual Awareness
0.40
Dynamic Identity
0.10
Multi-Agent Interactions
0.20
Non-Determinism
0.70
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.

L1 · Foundation Models✓ mapped

Integrates multiple external foundation models (GPT-5.5, Claude 4.7, Gemini 3.1, DeepSeek V4). Primary threats include prompt injection bypassing educational guardrails, model misalignment, and reliance on third-party API availability and security.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No details are provided regarding data storage, RAG pipelines, or vector databases. General threats include potential data exfiltration of uploaded student/educator documents and lack of data lineage controls.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework for the 'AI Tutor Tools' and 'task automation' is unspecified. General threats include insecure tool integration and prompt injection leading to unintended tool execution.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Hosting, sandboxing, and API credential management details are absent. General threats include the exposure of API keys for the integrated LLM providers and lack of tenant isolation.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No monitoring, logging, or guardrail mechanisms are described. General threats include a lack of observability into toxic, biased, or highly inaccurate educational outputs (hallucinations).

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

Not certain from the listing — No compliance certifications (such as COPPA/FERPA for educational tools or GDPR) or identity management controls are mentioned. General threats include unauthorized access to user accounts and data privacy violations.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — No multi-agent marketplace or agent-to-agent communication protocols are described. General threats are limited to potential future integrations of untrusted third-party educational plugins.

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