anth-security-basics

name	anth-security-basics
description	Apply Anthropic Claude API security best practices for key management, input validation, and prompt injection defense. Use when securing API keys, validating user inputs before sending to Claude, or implementing content safety guardrails. Trigger with phrases like "anthropic security", "claude api key security", "secure anthropic", "prompt injection defense".
allowed-tools	Read, Write, Grep
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","ai","anthropic"]
compatible-with	claude-code

Anthropic Security Basics

Overview

Security practices for Claude API integrations: API key management, input sanitization, prompt injection defense, and output validation.

API Key Security

Environment-Based Key Management

# .env (NEVER commit)
ANTHROPIC_API_KEY=sk-ant-api03-...

# .gitignore
.env
.env.*
!.env.example

# .env.example (commit this)
ANTHROPIC_API_KEY=sk-ant-api03-your-key-here

Key Rotation Procedure

# 1. Generate new key at console.anthropic.com/settings/keys
# 2. Deploy new key (zero-downtime: set both temporarily)
export ANTHROPIC_API_KEY_NEW="sk-ant-api03-new..."

# 3. Verify new key works
python3 -c "
import anthropic
client = anthropic.Anthropic(api_key='$ANTHROPIC_API_KEY_NEW')
msg = client.messages.create(model='claude-haiku-4-20250514', max_tokens=8, messages=[{'role':'user','content':'hi'}])
print('New key works:', msg.id)
"

# 4. Swap to new key
export ANTHROPIC_API_KEY="$ANTHROPIC_API_KEY_NEW"

# 5. Revoke old key in Console

Workspace Key Isolation

Use Anthropic Workspaces to isolate keys per team/environment:

Workspace	Purpose	Key Prefix
dev	Development/testing	sk-ant-api03-dev-...
staging	Pre-production	sk-ant-api03-stg-...
production	Live traffic	sk-ant-api03-prd-...

Prompt Injection Defense

import anthropic

def safe_user_query(user_input: , system_prompt: ) -> :
    
    client = anthropic.Anthropic()

    
    
    message = client.messages.create(
        model=,
        max_tokens=,
        system=system_prompt,  
        messages=[{
            : ,
            : user_input  
        }]
    )
     message.content[].text


SYSTEM =