Chicago Bull AI — agentic threat model
Chicago Bull AI is a read-only financial chatbot with low agentic risk, primarily vulnerable to prompt injection and data poisoning of upstream financial feeds, which could lead to the dissemination of inaccurate market advice.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| 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.
Not certain from the listing — likely utilizes a standard commercial LLM optimized for financial Q&A. It is vulnerable to prompt injection that could bypass financial disclaimer guardrails or generate biased stock recommendations.
Not certain from the listing — relies on real-time financial data feeds, news APIs, and stock screener databases. Vulnerable to upstream data poisoning where manipulated news or stock metrics could trick the agent into presenting false market trends.
Not certain from the listing — likely uses a basic tool-calling framework to trigger stock charts and screeners based on user queries. Vulnerable to indirect prompt injection if malicious payloads are embedded in the retrieved news articles or stock descriptions.
Not certain from the listing — hosted as a closed-source web application. Standard web application vulnerabilities apply, but direct infrastructure compromise risks are typical of standard SaaS setups.
Not certain from the listing — no mention of financial guardrails, hallucination filters, or output monitoring to prevent the generation of unauthorized financial advice.
Not certain from the listing — closed source, free tool with no mentioned compliance certifications (e.g., SEC/FINRA compliance, SOC2) or user authentication controls.
Not certain from the listing — operates as a standalone chatbot; no multi-agent or marketplace integrations are described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).