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Credit Card Generator — agentic threat model

4.3AIVSS 4.3 · Medium

The Credit Card Generator is a deterministic utility tool rather than an active AI agent, presenting minimal agentic risk. Its primary security considerations are standard web application vulnerabilities and the potential misuse of generated mock data for low-level fraud testing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.0AARS uplift 0.32Factor sum 0.6/10Threat ×0.9Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.00
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.00
Contextual Awareness
0.10
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.20
Opacity & Reflexivity
0.10

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 — The description mentions a 'modern web technology stack' and does not explicitly mention using an LLM or foundation model. If an LLM is used, it would be highly susceptible to prompt injection, but it is highly likely a standard deterministic algorithm.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No RAG, vector stores, or training data pipelines are mentioned. The tool generates mock data based on standard card specifications (BINs, Luhn algorithm) rather than retrieving or learning from sensitive datasets.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — There is no evidence of an agent orchestration framework (like LangChain or AutoGen). It appears to be a standard web application with static generation logic.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Hosted as a web tool. Standard web infrastructure threats apply (XSS, dependency vulnerabilities, server compromise), but specific hosting, sandboxing, or deployment details are not provided.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No mention of AI-specific evaluation, guardrails, or LLM monitoring. Standard application logging may exist but is not detailed.

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

Not certain from the listing — Open source tool. No mention of enterprise security controls, compliance certifications, or access management.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — Does not interact with other agents or marketplaces; operates as a standalone utility.

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