What safety measures are provided for tool execution?

It demonstrates how to implement strict command whitelisting, input validation using shlex, and directory restriction to prevent arbitrary code execution.

How does this skill help prevent prompt injection?

It provides patterns for isolating user input from system instructions and includes sanitization functions to redact dangerous override patterns like 'ignore previous instructions'.

Can I use this for production secret management?

Yes, the skill includes implementations for using environment variables with python-dotenv and cloud-based solutions like Google Cloud Secret Manager.

Does it include output monitoring for sensitive data?

Yes, it features Pydantic models with custom field validators to check for leaked API key patterns or PII before the response is delivered to the user.

LangChain Security Essentials

Name: LangChain Security Essentials
Author: Brmbobo

byBrmbobo

0•

Security & Testing

Implements industry-standard security practices for LangChain applications to prevent prompt injection and secure sensitive data.

LangChain Security Essentials provides a comprehensive set of guidelines and implementation patterns to harden LangChain-based applications for production environments. It focuses on critical security pillars including robust API key management using secrets managers, prompt injection mitigation through input sanitization, and safe tool execution via command whitelisting. By following these patterns, developers can protect their LLM-powered applications from common vulnerabilities like unauthorized code execution and sensitive data leakage while maintaining detailed audit logs for compliance and monitoring.

Key Features

01Secure API key management patterns using environment variables and cloud secret managers

02Comprehensive audit logging for LLM starts, tool calls, and final generation events

03Prompt injection mitigation through template isolation and regex-based input sanitization

040 GitHub stars

05Safe tool execution with command whitelisting, shlex parsing, and sandboxed environments

06Pydantic-based output validation to detect and redact PII or leaked credentials

Use Cases

01Implementing secure shell command tools for LLM agents with restricted permissions

02Hardening a production chatbot against adversarial prompt injection attacks

03Setting up enterprise-grade secrets management for multi-provider AI applications

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add brmbobo/web2podcast langchain-security-basics

For use in Claude.ai and ChatGPT

Download Skill