financial-data-collector — agentic threat model
This agent presents a moderate-to-high risk due to its ability to write JSON files directly to the host system without explicit sandboxing, combined with its role as an upstream data provider for other financial agents.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.40 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.20 |
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 specific foundation model driving this skill is not disclosed. Standard LLM risks like prompt injection could theoretically manipulate the ticker inputs or parameters passed to yfinance.
Gathers public financial data via yfinance. Risk of data poisoning if upstream yfinance sources are manipulated, but no vector DB or RAG is indicated.
Executes yfinance API calls and writes JSON files. Risk of tool misuse or injection if ticker inputs are not sanitized, potentially leading to command injection on the host.
Writes JSON directly to the host system. Without sandboxing, this poses a risk of local file write vulnerabilities, path traversal, or host compromise if the output path is manipulable.
Not certain from the listing — No evaluation, guardrails, or observability mechanisms are described for this community skill.
Not certain from the listing — No authentication, authorization, or compliance controls are specified for this open-source skill.
Designed to feed downstream agents (DCF, comps, earnings). A compromise or data poisoning here propagates cascading failures to downstream financial analysis agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).