B2 AI — agentic threat model
B2 AI acts as an enterprise command center with high agentic risk due to its ability to execute automated, scheduled workflows and perform actions across multiple integrated business platforms. While it features configurable role-based access controls, its closed-source nature and deep integration footprint present a significant attack surface for unauthorized cross-platform actions.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.60 | |
| Multi-Agent Interactions | 0.40 | |
| Non-Determinism | 0.60 | |
| 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 — uses 'advanced large language model (LLM) technology' but specific models are not disclosed. Threats include prompt injection leading to unauthorized tool execution or data access.
Not certain from the listing — connects to 'various business tools and data sources' to extract insights, but the underlying vector database or RAG architecture is not detailed. Threats include data exfiltration and knowledge-base poisoning.
Not certain from the listing — orchestrates 'shareable, schedulable AI-powered workflows' and 'task automation', but the specific framework (e.g., LangChain, custom) is undisclosed. Threats include insecure tool integration and tool misuse.
Not certain from the listing — closed-source SaaS deployment. Threats include container compromise, lateral movement to connected business tools, and credential theft from integrated platforms.
Not certain from the listing — no mention of evaluation, monitoring, or guardrails in the public description. Threats include blind spots in agent execution and lack of auditability for automated actions.
B2 AI explicitly implements 'privacy-first data controls with configurable role-based access' to manage permissions across integrated platforms. Threats include RBAC bypass or misconfiguration leading to unauthorized privilege escalation.
Provides 'AI agents' (plural) that connect to 'popular business tools' and 'operational platforms', creating a multi-tool/multi-agent ecosystem. Threats include cascading failures across integrations and API trust abuse.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).