LevelFields AI — agentic threat model
LevelFields AI is primarily an analytical and alerting tool with low agentic autonomy, posing minimal direct operational risk but presenting moderate financial risk to users if its forecasting data or news alerts are manipulated via data poisoning or prompt injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.50 | |
| 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.
Not certain from the listing — likely uses LLMs for news summarization and sentiment analysis. Threats include prompt injection that could skew stock sentiment analysis, leading to incorrect alerts.
Not certain from the listing — relies heavily on financial data feeds, historical stock databases, and real-time news sources. Vulnerable to data poisoning of news feeds or historical data to manipulate stock alerts.
Not certain from the listing — likely uses a simple retrieval and alerting pipeline rather than a complex agentic orchestration framework. Vulnerable to insecure tool integration if the screener or alert system can be manipulated.
Not certain from the listing — hosted as a web application/SaaS. Vulnerable to standard web application vulnerabilities, container compromise, or unauthorized access to user alert configurations.
Not certain from the listing — requires strict monitoring to prevent drift in forecasting accuracy and to detect anomalous alert patterns that could indicate system compromise.
Not certain from the listing — requires robust access controls to protect paid user accounts and subscription tiers, as well as compliance with financial advisory regulations if applicable.
Not certain from the listing — operates primarily as a standalone SaaS tool with no explicit multi-agent or marketplace interactions described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).