Stephen Quant — agentic threat model
Stephen Quant presents a moderate agentic risk profile; while it lacks direct transactional capabilities like wallet execution, its 'Self-Evolving Analysis' and Telegram integration expose users to potential financial manipulation or misinformation if its data feeds or model outputs are compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.50 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| 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 — The underlying foundation model is unspecified due to its closed-source nature. It is vulnerable to adversarial prompt injection that could distort its 'unbiased' technical analysis or reprogram it to favor specific tokens.
Not certain from the listing — The data pipeline for ingestion of real-time chart data and macro context is unspecified. It faces threats of data poisoning where manipulated price feeds could force the agent to output false buy/sell signals.
Not certain from the listing — The orchestration framework is unspecified. The 'Self-Evolving Analysis' feature suggests dynamic prompt adjustments or memory updates, which could be vulnerable to state manipulation or persistent memory poisoning.
Not certain from the listing — Hosting and sandboxing details are unspecified, but the agent utilizes Telegram Integration. This integration exposes an external API surface that could be targeted for session hijacking or webhook manipulation.
Not certain from the listing — There is no mention of real-time monitoring, output guardrails, or drift detection to ensure the 'Self-Evolving Analysis' does not degrade or begin outputting highly erratic financial advice.
Not certain from the listing — No compliance frameworks (e.g., SOC2) or access control policies are mentioned. The lack of transparent audit logs for its self-evolution steps poses a compliance challenge in financial contexts.
Not certain from the listing — No multi-agent orchestration or marketplace interactions are described. The primary ecosystem risk is localized to the Telegram platform where it interacts with human traders.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.