n8n — agentic threat model
n8n presents a high agentic risk profile due to its combination of custom code execution (JS/Python), 350+ third-party integrations, and AI orchestration via LangChain. A compromise or successful prompt injection could lead to arbitrary code execution or unauthorized actions across a vast ecosystem of connected enterprise applications.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.50 | |
| Multi-Agent Interactions | 0.50 | |
| 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 — n8n integrates with external foundation models via LangChain nodes, making it susceptible to upstream model vulnerabilities, adversarial prompt injection, and misaligned outputs depending on the chosen LLM provider.
Supports integration with vector databases for RAG. Threats include vector database poisoning, unauthorized data retrieval via prompt injection, and lack of fine-grained access control over retrieved context.
Highly vulnerable to tool misuse and insecure tool integration due to 350+ integrations and custom JS/Python code execution nodes. LangChain orchestration can be manipulated via prompt injection to execute unintended workflows.
Self-hosting provides control but shifts infrastructure security to the user. Key threats include container escape via custom code execution (JS/Python nodes) and exposure of API keys/secrets stored within the workflow manager.
Not certain from the listing — n8n's native execution logging may capture workflow states, but dedicated AI evaluation, drift detection, and real-time LLM guardrails are not explicitly detailed in the provided features.
Not certain from the listing — While self-hosting allows users to enforce their own compliance and network boundaries, the listing does not specify built-in RBAC, enterprise identity federation, or compliance certifications.
High ecosystem risk due to the ability to share and import custom nodes, which could introduce malicious code or backdoors. Multi-agent coordination is possible via chained workflows, risking cascading failures.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).