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CSCA AI Assistant — agentic threat model

5.6AIVSS 5.6 · Medium

The CSCA AI Assistant is a low-risk, informational agent focused on educational advising, with primary risks centered around prompt injection leading to misinformation (e.g., fraudulent scholarship links) rather than active system compromise.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.8AARS uplift 0.83Factor sum 1.6/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.20
Persistent Memory
0.10
Contextual Awareness
0.30
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely uses a standard commercial or open-source LLM. Vulnerable to prompt injection that could manipulate course recommendations or redirect students to malicious scholarship links.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — relies on syllabus data and university directories. Vulnerable to knowledge-base poisoning if the directories or syllabus files are fetched dynamically from untrusted external sources.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely uses a simple RAG or orchestration framework. Vulnerable to insecure tool integration if directory search tools or web scrapers are not properly sanitized.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — as an open-source tool, deployment is unspecified. Standard web hosting and containerization vulnerabilities apply depending on how the user hosts the application.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no mention of monitoring, guardrails, or evaluation frameworks to prevent hallucinated academic advice or toxic outputs.

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

Not certain from the listing — no mention of authentication, authorization, or compliance with student data privacy standards (such as FERPA) if student queries are logged.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a standalone assistant with no indicated multi-agent or marketplace integrations.

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