EasyFin AI — agentic threat model
EasyFin AI presents a moderate agentic risk profile, primarily acting as an analytical and advisory agent for investment research and portfolio optimization without direct transaction execution capabilities. The primary risks stem from potential financial data poisoning (RAG manipulation) and the generation of hallucinated or manipulated investment insights.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.50 |
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 — The underlying foundation models are not specified. Threats include adversarial prompt injection via manipulated financial reports or earnings transcripts, leading to biased or hallucinated investment advice.
The platform processes complex financial data, earnings calls, economic indicators, and curated research. This makes it highly susceptible to data poisoning (e.g., injecting fraudulent financial statements or malicious transcripts to skew portfolio optimization) and data exfiltration of proprietary user portfolio configurations.
Not certain from the listing — The orchestration framework is unspecified. Potential threats include insecure tool integration with backtesting engines and charting libraries, which could be exploited if the agent accepts untrusted inputs during portfolio optimization.
Not certain from the listing — No deployment or hosting details are provided. If backtesting tools allow user-defined code execution, lack of robust sandboxing could lead to container escape or host compromise.
Not certain from the listing — No evaluation or observability mechanisms are mentioned. Gaps in monitoring could allow subtle drift in financial data processing or adversarial manipulation of market insights to go undetected.
Not certain from the listing — Compliance controls (such as SEC/FINRA alignment for automated financial advice or SOC2 data protection) are not detailed, posing regulatory and compliance risks regarding automated investment recommendations.
Not certain from the listing — No multi-agent or marketplace ecosystem is described. The primary external dependency risk is limited to third-party financial data feeds and institutional research APIs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).