AQ22 — agentic threat model
AQ22 presents a high-risk profile due to its integration with core banking platforms and handling of sensitive KYC/KYB data. While its secure on-prem deployment options and audit trails offer mitigation, vulnerabilities in its orchestration could lead to financial fraud or severe compliance violations.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.60 | |
| 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 specific foundation models used are not disclosed. Adversarial prompt injection could manipulate underwriting decisions or bypass automated compliance checks.
Not certain from the listing — the exact database and RAG architectures are unspecified. However, processing sensitive KYC/KYB and financial ratio data introduces severe risks of data exfiltration and unauthorized PII access.
The agent utilizes 'modular orchestration' to automate underwriting and compliance. Insecure tool integration or prompt injection could allow unauthorized API calls to connected banking platforms.
Not certain from the listing — while it supports 'on-prem or in-cloud' deployment, specific containerization, network isolation, or sandboxing controls are not detailed.
The system features 'audit trails' to track decisions, providing a baseline for observability. However, real-time guardrails against drift or adversarial manipulation of financial ratios are not detailed.
Designed for highly regulated sectors (banking, fintech, PE) with built-in compliance automation (KYC/KYB). Security controls must align with strict financial regulations, though specific certifications are not listed.
Employs 'domain-specific AI agents' in a modular fashion. This multi-agent setup introduces risks of cascading logic failures or trust abuse between the compliance agent and the underwriting agent.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).