N8N has been growing as a trend in the automation world. Being a self-hosted tool, it’s used both by IT professionals and by people without much experience in servers, programming, or cybersecurity.
The problem is that, while it enables powerful integrations, I see a huge number of potentially fragile automations. The risk is clear: a large-scale security collapse, especially when dealing with flows involving emails, databases, files, and external services. The result? An ecosystem with massive potential for failure.
⚠️ LLM Vulnerabilities in Automation
With the rise of Large Language Models (LLMs) inside automation workflows, specific vulnerabilities are emerging. These have already been documented in security reports and by the OWASP Top 10 for LLMs. Some include:
- Prompt Injection – inserting malicious commands into prompts
- Sensitive Information Disclosure – unintentional leakage of sensitive data
- Training Data Poisoning – manipulating or corrupting training data
- Insecure Output Handling – unsafe handling of model responses
- Model Denial of Service – DoS attacks aimed at exhausting model resources
- Supply Chain Vulnerabilities – weaknesses in dependencies and supply chains
- Insecure Plugin Design – poorly designed extensions or plugins
- Excessive Agency – overly autonomous AI leading to unintended actions
- System Prompt Leakage – leaking system instructions
- Vector and Embedding Weaknesses – flaws in embeddings that support response generation
🔒 Layered Security in N8N
To mitigate risks, it’s essential to approach automation with multiple layers of security.
For instance, an initial step could be implementing Prompt Injection Detection — a Node.js node in N8N capable of checking user inputs and detecting potential anomalies before they compromise workflows.
A practical example:
👉 GitHub repository with Prompt Injection Detection for N8N
It’s only one layer, but already an important step forward!
N8N Security Guide - Essential Best Practices
👉 GitHub repository Best Practices
🚀 The Future of AI-Driven Automation
As we move deeper into intelligent automation, awareness and responsibility are crucial. We are still building best practices to protect data, privacy, and infrastructure in this new era of artificial intelligence.
Automation is empowering — but automation without security is an open door to disaster.
Top comments (0)