Cubeo AI — agentic threat model
Cubeo AI presents a moderate-to-high security risk due to its multi-agent orchestration and integration capabilities, where a compromise in one agent or ingested document could trigger cascading unauthorized actions across connected business systems.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.80 | |
| 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 specific foundation models powering the Cubeo AI platform are not disclosed, leaving potential vulnerabilities to model-specific adversarial attacks or data leakage unverified.
Cubeo AI ingests documents, videos, and integration data to ground its agents. This creates risks of data poisoning via malicious document uploads and potential data exfiltration through unauthorized access to the vector database or connected integrations.
The platform uses a no-code builder to orchestrate agents. Risks include insecure tool integration and tool misuse, such as an automated email writer being manipulated to send spam or phishing emails using connected integrations.
Not certain from the listing — The hosting infrastructure, sandboxing of execution environments for integrations, and secrets management practices for third-party API keys are not detailed in the public listing.
Not certain from the listing — There is no mention of built-in evaluation frameworks, real-time monitoring, guardrails, or logging mechanisms to detect anomalous agent behavior or drift.
Not certain from the listing — The listing does not specify compliance certifications (e.g., SOC 2, ISO 27001), identity and access management (IAM) controls, or enterprise governance policies.
Cubeo AI relies heavily on multi-agent orchestration where agents trigger each other. This introduces threats of agent-to-agent trust abuse, cascading failures, and lateral movement where a compromise in a 'competitor analyst' agent propagates to a 'sales enablement' agent.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).