Moody's Research Assistant — agentic threat model
Moody's Research Assistant presents a moderate agentic risk profile, primarily acting as an analytical and data-retrieval assistant over highly sensitive proprietary financial data. The primary security risks involve potential data exfiltration of proprietary datasets via prompt injection and financial decision-making errors due to LLM hallucinations.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| 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 — Uses generative AI and large language models, making it susceptible to adversarial prompt injection, model reprogramming, and hallucinated financial outputs, though the specific underlying models are not disclosed.
Integrates Moody's extensive proprietary data with advanced AI. This presents a high-value target for data exfiltration, knowledge-base poisoning, or unauthorized access to proprietary credit and risk datasets.
Not certain from the listing — Automates routine tasks and data workflows, which implies an orchestration framework. Threats include insecure tool integration with internal databases and prompt injection leading to unauthorized data retrieval.
Not certain from the listing — Delivered as a closed-source enterprise platform. Threats include potential multi-tenant isolation failures, unauthorized API access, and lack of secure sandboxing for data processing.
Not certain from the listing — No specific details on evaluation, monitoring, or guardrails are provided. Gaps here could lead to undetected drift in financial analysis or failure to catch adversarial manipulation of inputs.
Not certain from the listing — While operating in a highly regulated financial domain, specific compliance certifications (e.g., SOC2, ISO) or identity/access management controls are not detailed in the public listing.
Not certain from the listing — No multi-agent or marketplace interactions are described. The primary threat is limited to cascading failures if the assistant's outputs are directly integrated into automated downstream financial systems.
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.