LangChain Agent Security Hardening
Security hardening guide for LangChain agents. Covers prompt injection defense, tool sandboxing, output filtering, and monitoring.
pip install langchain langchain-core langsmithOverview
LangChain is the most popular framework for building AI agents, but its flexibility comes with security tradeoffs. This guide covers hardening LangChain agents for production: implementing input sanitization callbacks, configuring tool-level permissions, setting up output filters to prevent data leakage, monitoring agent behavior with LangSmith, and defending against prompt injection through retrieval-augmented generation (RAG) pipelines.
Features
- -Input sanitization callback chains
- -Tool permission and sandboxing setup
- -Output filtering for PII and credentials
- -LangSmith monitoring integration
- -RAG pipeline injection defense
Security Considerations
LangChain's tool-calling mechanism is one of the most exploited attack surfaces. Agents using web browsing tools, code execution, or database access are especially vulnerable. Always implement the principle of least privilege: give agents only the tools they need, with the minimum permissions required.
Scan for vulnerabilities: npx hackmyagent secure
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