Chatbot Security and Privacy: What You Need to Know

Introduction

AI chatbots inherently process sensitive information. Customers share personal questions, employees ask about internal processes, and business knowledge is entered as system prompts. This makes security and privacy not an afterthought but a core requirement when deploying a chatbot.

In this article, we cover the most important security and privacy considerations for AI chatbots, with concrete tips for OpenClaw users who want to secure their installation according to best practices and GDPR.

Understanding Data Flows

To understand privacy risks, you need to know which data goes where. In an OpenClaw installation, there are three data flows: messages from users to your server, API calls from your server to the LLM model, and storage of conversation history in your database. Each of these flows has its own security considerations.

Messages from users to your server are encrypted via HTTPS — provided you have configured a reverse proxy with SSL, which is strongly recommended. API calls to the LLM model are also encrypted, but the data is temporarily processed by the provider. OpenAI and Anthropic state that API data is not used for model training, but you should carefully review their privacy policies.

Conversation history in PostgreSQL is not encrypted at rest by default. For sensitive applications, you can configure PostgreSQL with encryption at rest and regular backups to an encrypted location.

GDPR Compliance and Data Protection

If you deploy a chatbot that processes personal data — and that is almost always the case if the bot interacts with customers — it falls under GDPR. Concretely, this means you need a legal basis for processing, you must inform users about what data you process, and you need a data processing agreement with your LLM provider.

With OpenClaw, you have the advantage of fully controlling data location. Choose a server in the EU, configure automatic deletion of conversations after a set period, and document your processing activities in your privacy policy. This is considerably simpler than with a SaaS chatbot where you have little influence over data processing.

Server Security and Access Control

Your chatbot's security is only as strong as your server's security. Use SSH keys instead of passwords for server access, configure a firewall that only opens necessary ports (22 for SSH, 80 and 443 for web), and keep your operating system and Docker installation up to date with security patches.

The OpenClaw dashboard should be secured with strong authentication. Use a long, unique password and consider making the dashboard accessible only through a VPN or specific IP address. API keys for LLM providers should be stored as environment variables, never hardcoded in configuration files.

Conclusion

Security and privacy are not optional extras when deploying an AI chatbot — they must be considered from day one in your setup. With OpenClaw, you have the tools and control to run a secure, GDPR-compliant chatbot, but it requires deliberate choices in server configuration, data management, and access control. Take the time to set it up properly, and you will have a chatbot you can confidently use to serve your customers.