Magic Cloud — agentic threat model
Magic Cloud is an open-source, low-code/no-code AI agent framework, presenting high systemic risk due to its role in orchestrating downstream AI solutions and tool integrations without built-in, visible security guardrails.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.70 | |
| Non-Determinism | 0.70 | |
| 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's underlying foundation models are not specified, making it unclear how it mitigates model-level threats like prompt injection, adversarial reprogramming, or data poisoning.
Not certain from the listing — Details regarding RAG pipelines, vector database integrations, and training data lineage are omitted, leaving potential vulnerabilities to knowledge-base poisoning unaddressed.
As an AI agent framework and low-code platform, Magic Cloud directly orchestrates agent logic, tool execution, and planning. This introduces significant risks of insecure tool integration, framework-level vulnerabilities, and unauthorized tool execution if downstream user-configured flows are manipulated.
Not certain from the listing — The deployment architecture, sandboxing capabilities for executing generated code, and secrets management practices are not detailed in the public directory.
Not certain from the listing — It is unclear whether the platform provides built-in evaluation, logging, guardrails, or observability tools to detect drift, anomalies, or malicious agent behavior.
Not certain from the listing — No specific identity, access control, policy enforcement, or regulatory compliance frameworks (such as NIST or EU AI Act alignment) are mentioned.
Not certain from the listing — While designed for building AI solutions, the listing does not specify if it supports a multi-agent marketplace or external ecosystem integrations that could lead to cascading failures or agent-to-agent trust abuse.
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.