GreyLabs AI — agentic threat model
GreyLabs AI operates in the high-stakes banking sector, where voice-driven agentic capabilities present significant risks of financial fraud, unauthorized transactions, and PII exposure if voice-based prompt injection or API integrations are compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.20 | |
| 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 — Likely utilizes speech-to-text (STT), LLMs, and text-to-speech (TTS) models. Primary threats include voice-based prompt injection, adversarial audio inputs, and model reprogramming to bypass financial guardrails.
Not certain from the listing — Must handle highly sensitive banking data, customer profiles, and transaction histories. Risks include unauthorized data exfiltration, training data poisoning, and lack of secure data lineage for financial compliance.
Not certain from the listing — Orchestrates voice interactions and translates them into banking API calls. Threats include insecure tool integration where voice commands trigger unauthorized financial transactions or account modifications.
Not certain from the listing — Requires highly secure hosting (potentially PCI-DSS compliant) and secure telephony/SIP integration. Vulnerabilities could lead to call interception, infrastructure compromise, or lateral movement into core banking networks.
Not certain from the listing — Requires real-time audio/transcript monitoring and strict guardrails to prevent unauthorized financial advice or transaction execution. Lack of observability could lead to undetected fraudulent activities.
Not certain from the listing — Must align with strict financial regulations (e.g., GLBA, PCI-DSS, GDPR). Strong identity verification (such as voice biometrics or multi-factor authentication) is critical to prevent identity theft and unauthorized access.
Not certain from the listing — May interact with internal banking systems, payment gateways, or customer service routing agents. Risks involve cascading failures or trust abuse when interacting with external financial APIs.
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.