Lobby Studio — agentic threat model
Lobby Studio presents a moderate-to-high risk profile due to its support for task automation and API integrations on a closed-source, no-code platform, where the lack of transparent security controls or sandboxing details could expose private data to exfiltration via prompt injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| 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 | 0.60 | |
| 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 — the platform does not specify the underlying foundation models used for its customizable bots, leaving them potentially vulnerable to standard LLM threats like adversarial prompt injection or model reprogramming depending on the provider.
Not certain from the listing — while 'private data handling' is claimed, the exact mechanisms for vector storage, data isolation between tenants, and protection against data exfiltration or knowledge-base poisoning are unspecified.
Not certain from the listing — the orchestration framework for task automation and API integration is proprietary. This introduces risks of insecure tool integration or tool misuse if API keys and execution paths are not strictly sandboxed.
Not certain from the listing — hosting and sandboxing details are undisclosed. Multi-platform deployment and website embedding expose the bots to cross-site scripting (XSS) and clickjacking if frontend integration is insecure.
Not certain from the listing — there is no mention of built-in guardrails, real-time monitoring, or evaluation frameworks to detect drift, prompt injection, or anomalous bot behavior.
Not certain from the listing — although 'private data handling' is highlighted, specific compliance certifications (e.g., SOC 2, GDPR) or granular role-based access controls (RBAC) for team collaboration are not detailed.
Not certain from the listing — while users can deploy multiple bots, it is unclear if there is an active multi-agent orchestration ecosystem or marketplace, which could introduce cascading failure risks if bots interact.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).