BlockitAI — agentic threat model
BlockitAI presents a moderate-to-high risk profile due to its direct integration with sensitive calendar and communication APIs, where compromise could lead to unauthorized data exfiltration, social engineering, or operational disruption.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.70 | |
| Contextual Awareness | 0.60 | |
| 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 commercial LLMs to parse scheduling requests and draft emails. Vulnerable to prompt injection attacks that could manipulate scheduling logic or leak system instructions.
Not certain from the listing — stores user preferences and calendar patterns over time. Vulnerable to preference database poisoning or unauthorized extraction of historical meeting metadata.
Not certain from the listing — orchestrates actions between natural language processing and calendar APIs. Vulnerable to tool misuse where malicious inputs trigger unintended meeting creations, deletions, or invitations.
Not certain from the listing — hosted as a closed-source SaaS. Vulnerable to compromise of OAuth tokens used to access third-party calendar providers (e.g., Google Calendar, Microsoft Outlook).
Not certain from the listing — no details on monitoring or guardrails for scheduling actions. Vulnerable to blind spots in detecting anomalous scheduling behavior or automated spamming.
Not certain from the listing — requires high-privilege OAuth scopes to read/write calendars. Vulnerable to over-privileged access if the agent does not enforce strict least-privilege principles.
Not certain from the listing — primarily interacts with human users via email/calendar, but could interact with other scheduling agents. Vulnerable to cascading scheduling conflicts or automated denial-of-service style calendar flooding.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).