AWS Lambda 中 /tmp 目录是唯一可写入的本地文件系统。但是，这个目录可能无法满足一些应用程序的安全性要求，特别是涉及到敏感数据的情况。

为了解决这个问题，我们可以考虑以下两种方法：

1. 使用 AWS S3 存储敏感数据

import boto3
import os

s3_client = boto3.client('s3')

def lambda_handler(event, context):
    # Here, we are reading sensitive data from S3 bucket and writing it to /tmp directory
    
    s3_client.download_file('MyBucket', 'sensitive.txt', '/tmp/sensitive.txt')
    
    # Here, we are processing sensitive data from /tmp directory
    
    with open('/tmp/sensitive.txt', 'r') as f:
        sensitive_data = f.read()
    
    # Here, we are deleting sensitive data from /tmp directory
    
    os.remove('/tmp/sensitive.txt')
    
    # Here, we are returning the response
    
    return {
        'statusCode': 200,
        'body': json.dumps('Sensitive Data Processed Successfully!')
    }

2. 使用 AWS Secrets Manager 存储敏感数据

import boto3
import json

secrets_manager_client = boto3.client('secretsmanager')

def get_secret():

    # Here, we are getting sensitive data from AWS Secrets Manager
    
    get_secret_value_response = secrets_manager_client.get_secret_value(
        SecretId='MySecrets',
    )
    
    secret = json.loads(get_secret_value_response['SecretString'])
    
    # Here, we are returning the sensitive data
    
    return secret.get('sensitive_data', '')

def lambda_handler(event, context):
    
    # Here, we are processing sensitive data
    
    sensitive_data = get_secret()
    
    # Here, we are returning the response
    
    return {
        'statusCode': 200,
        'body': json.dumps('Sensitive Data Processed Successfully!')
    }

上述两种方法可以帮助我们更加安全地在 AWS Lambda 中处理敏感数据，避免了