original file name: Codeium Chat - 10mvF0nDJYeZoR892DMq2RAOhO1Bn4YY.md summary: The chat involves a user seeking assistance in expanding their AWS CloudFormation template to implement HttpOnly Cookies for added security and provide S3 access for storing user history. The user currently has a functional CloudFormation template for AWS Cognito but requires guidance on adding new functionalities.

I provided guidance on updating the CloudFormation template to include an S3 bucket named handterm-history, setting HttpOnly Cookies, Lambda@Edge function setup, IAM role configurations, and adjustments for session management. When the user expressed the need for assistance in creating a Lambda@Edge function for HttpOnly Cookies, I provided a basic outline for creating and deploying the function.

In later interactions, the user shared their updated CloudFormation template and sought feedback on the implemented changes. I offered additional tips on optimizing the Lambda function, securely managing user credentials without OAuth, and ensuring application security.

Note: This is purely the output of the chat conversation and does not contain any raw data, codebase snippets, etc. used to generate the output.

User at 9:10 am, Jun 27, 2024

I have this currently deployed AWS CloudFormation that's working and I am logging in to Cognito with:

Resources:
 CognitoUserPool:
  Type: "AWS::Cognito::UserPool"
  Properties:
   UserPoolName: "HandTermUserPool"
   Schema:
    - Name: "email"
     Required: true
     Mutable: false
   Policies:
    PasswordPolicy:
     MinimumLength: 8
     RequireUppercase: true
     RequireLowercase: true
     RequireNumbers: true
     RequireSymbols: true
 CognitoUserPoolClient:
  Type: "AWS::Cognito::UserPoolClient"
  Properties:
   UserPoolId: !Ref CognitoUserPool
   ExplicitAuthFlows:
    - "ALLOW_USER_SRP_AUTH"
    - "ALLOW_REFRESH_TOKEN_AUTH"
   GenerateSecret: false
 HandTermIdentityPool:
  Type: "AWS::Cognito::IdentityPool"
  Properties:
   IdentityPoolName: "HandTermIdentityPool"
   AllowUnauthenticatedIdentities: false
   CognitoIdentityProviders:
    - ClientId: !Ref CognitoUserPoolClient
     ProviderName: !GetAtt CognitoUserPool.ProviderName

Outputs:
 UserPoolId:
  Value: !Ref CognitoUserPool
  Description: The ID of the Cognito User Pool
 UserPoolClientId:
  Value: !Ref CognitoUserPoolClient
  Description: The ID of the Cognito User Pool Client
 HandTermIdentityPoolId:
  Value: !Ref HandTermIdentityPool
  Description: The ID of the Cognito Identity Pool

I want to expand it so that I can implement HttpOnly Cookies for added security and to add S3 access so that I can start migrating the users localStorage history to an S3 bucket that I can dedicate to their Cognito user account, so that their history remains private to the Cognito user account.

I am reading an AWS Cloudfront authorization example and it has some information about how I could add a Lamda@Edge function to add HttpOnly Cookies and provide S3 access, but I am not sure how to assemble the CloudFormation template. That's where I need your help.

# Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0

AWSTemplateFormatVersion: "2010-09-09"
Transform: AWS::Serverless-2016-10-31
Description: >
 Example stack that shows how to reuse the serverless application with a pre-existing User Pool and Client.
 The pre-existing User Pool Arn and Client ID can be provided to the Auth@Edge application through parameters.

 In this example we're creating the User Pool and Client, and the Auth@Edge application in the same stack in the same region.
 You could instead also use a pre-existing User Pool and Client from a different stack and region.

Parameters:
 EnableSPAMode:
  Type: String
  Description: Set to 'false' to disable SPA-specific features (i.e. when deploying a static site that won't interact with logout/refresh)
  Default: "true"
  AllowedValues:
   - "true"
   - "false"
 OAuthScopes:
  Type: CommaDelimitedList
  Description: The OAuth scopes to request the User Pool to add to the access token JWT
  Default: "phone, email, profile, openid, aws.cognito.signin.user.admin"

Conditions:
 GenerateClientSecret: !Equals
  - EnableSPAMode
  - "false"

Resources:
 UserPool:
  Type: AWS::Cognito::UserPool
  Properties:
   UserPoolName: !Ref AWS::StackName
   AdminCreateUserConfig:
    AllowAdminCreateUserOnly: true
   UsernameAttributes:
    - email
 UserPoolClient:
  Type: AWS::Cognito::UserPoolClient
  Properties:
   UserPoolId: !Ref UserPool
   PreventUserExistenceErrors: ENABLED
   GenerateSecret: !If
    - GenerateClientSecret
    - true
    - false
   AllowedOAuthScopes: !Ref OAuthScopes
   AllowedOAuthFlowsUserPoolClient: true
   AllowedOAuthFlows:
    - code
   SupportedIdentityProviders:
    - COGNITO
   CallbackURLs:
    # The following sentinel value will be replaced by Auth@Edge with the CloudFront domain name (if you let Auth@Edge create the CloudFront distribution)
    - https://example.com/will-be-replaced
   LogoutURLs:
    # The following sentinel value will be replaced by Auth@Edge with the CloudFront domain name (if you let Auth@Edge create the CloudFront distribution)
    - https://example.com/will-be-replaced
 UserPoolDomain:
  Type: AWS::Cognito::UserPoolDomain
  Properties:
   Domain: !Sub
    - "auth-${StackIdSuffix}"
    - StackIdSuffix: !Select
      - 2
      - !Split
       - "/"
       - !Ref AWS::StackId
   UserPoolId: !Ref UserPool
 MyLambdaEdgeProtectedSpaSetup:
  Type: AWS::Serverless::Application
  DependsOn: UserPoolDomain
  Properties:
   Location:
    ApplicationId: arn:aws:serverlessrepo:us-east-1:520945424137:applications/cloudfront-authorization-at-edge
    SemanticVersion: 2.3.0
   Parameters:
    UserPoolArn: !GetAtt UserPool.Arn
    UserPoolClientId: !Ref UserPoolClient
    EnableSPAMode: !Ref EnableSPAMode
    CreateCloudFrontDistribution: true
    OAuthScopes: !Join
     - ","
     - !Ref OAuthScopes
Outputs:
 WebsiteUrl:
  Description: URL of the CloudFront distribution that serves your SPA from S3
  Value: !GetAtt MyLambdaEdgeProtectedSpaSetup.Outputs.WebsiteUrl

I don't need to use any social logins. The users will type in their username and password, and I already have that part working.

Can you help me update my CloudFormation template to add HttpOnly Cookies, and to create an S3 bucket name handterm-history that I can write each users history to?

Codeium at 9:11 am, Jun 27, 2024

To expand your CloudFormation template to include the implementation of HttpOnly Cookies for added security and to provide access to an S3 bucket for storing user history, you can integrate the Lambda@Edge function for authentication with HttpOnly Cookies and add an S3 bucket with the appropriate permissions. Here's how you can update your template:

1. Add an S3 Bucket Resource: Define an S3 bucket named handterm-history to store user history.

2. Lambda@Edge for HttpOnly Cookies: You can use the Lambda@Edge setup from the provided CloudFront authorization example to handle HttpOnly Cookies. Ensure you have a Lambda function configured for this.

3. IAM Role for Lambda: Define an IAM role for the Lambda function to allow it to access the S3 bucket.

4. Update the UserPoolClient: Ensure the UserPoolClient is configured to allow OAuth flows if you plan to use OAuth features for securing the S3 access.

Here is the updated CloudFormation template, incorporating the necessary resources:

AWSTemplateFormatVersion: '2010-09-09'
Description: AWS CloudFormation for HandTerm application with HttpOnly Cookies and S3 access.

Resources:
  CognitoUserPool:
    Type: "AWS::Cognito::UserPool"
    Properties:
      UserPoolName: "HandTermUserPool"
      Schema:
        - Name: "email"
          Required: true
          Mutable: false
      Policies:
        PasswordPolicy:
          MinimumLength: 8
          RequireUppercase: true
          RequireLowercase: true
          RequireNumbers: true
          RequireSymbols: true
  
  CognitoUserPoolClient:
    Type: "AWS::Cognito::UserPoolClient"
    Properties:
      UserPoolId: !Ref CognitoUserPool
      ExplicitAuthFlows:
        - "ALLOW_USER_SRP_AUTH"
        - "ALLOW_REFRESH_TOKEN_AUTH"
      GenerateSecret: false
  
  HandTermIdentityPool:
    Type: "AWS::Cognito::IdentityPool"
    Properties:
      IdentityPoolName: "HandTermIdentityPool"
      AllowUnauthenticatedIdentities: false
      CognitoIdentityProviders:
        - ClientId: !Ref CognitoUserPoolClient
          ProviderName: !GetAtt CognitoUserPool.ProviderName

  HandTermHistoryBucket:
    Type: 'AWS::S3::Bucket'
    Properties:
      BucketName: 'handterm-history'
      AccessControl: Private
      VersioningConfiguration:
        Status: Enabled

  LambdaExecutionRole:
    Type: 'AWS::IAM::Role'
    Properties:
      AssumeRolePolicyDocument:
        Version: '2012-10-17'
        Statement:
          - Effect: Allow
            Principal:
              Service: [lambda.amazonaws.com, edgelambda.amazonaws.com]
            Action: 'sts:AssumeRole'
      Policies:
        - PolicyName: LambdaS3Access
          PolicyDocument:
            Version: '2012-10-17'
            Statement:
              - Effect: Allow
                Action: 's3:*'
                Resource: !Sub 'arn:aws:s3:::handterm-history/*'

# Add more resources as needed, for example, Lambda@Edge function and its association with CloudFront distribution.

Outputs:
  UserPoolId:
    Value: !Ref CognitoUserPool
    Description: The ID of the Cognito User Pool
  UserPoolClientId:
    Value: !Ref CognitoUserPoolClient
    Description: The ID of the Cognito User Pool Client
  HandTermIdentityPoolId:
    Value: !Ref HandTermIdentityPool
    Description: The ID of the Cognito Identity Pool
  HandTermHistoryBucketName:
    Value: !Ref HandTermHistoryBucket
    Description: The name of the S3 bucket for storing user history

Note:

• This template adds an S3 bucket named handterm-history for storing user history.
• It assumes you have a Lambda@Edge function ready for handling authentication with HttpOnly Cookies. You'll need to add that Lambda function to your template or ensure it's configured elsewhere.
• The LambdaExecutionRole is set up to allow the Lambda function to access the S3 bucket. Adjust the permissions according to your security requirements.
• The OAuth settings and Lambda@Edge configuration for handling HttpOnly Cookies should be adapted based on your specific use case and security requirements.

Ensure to review and adjust this template according to your project's specific needs and AWS's best practices, especially regarding IAM roles and permissions.

User at 9:36 am, Jun 27, 2024

I do not already have a Lambda@Edge function to handle the HttpOnly Cookies. I need your help in creating that.

I changed the bucket VersioningConfiguration to disabled, since the history records will be write-once-read-many.

Currently, users will be logging in by typing their username and password. I don't know if there is any need for OAuth with that use case.

Codeium at 9:37 am, Jun 27, 2024

Given your requirements and the absence of an existing Lambda@Edge function to handle HttpOnly Cookies, we'll create a basic outline for a Lambda function that can be associated with CloudFront to implement HttpOnly Cookies. This Lambda function will be triggered by CloudFront events, specifically on viewer response to insert HttpOnly Cookies into the responses returned to users.

Since you're handling user logins with username and password directly through Amazon Cognito without the explicit need for OAuth flows in your described use case, the emphasis will be on securely managing sessions through HttpOnly Cookies.

First, you'll need to write the Lambda function code. This example function sets an HttpOnly cookie on the viewer response:

'use strict';

exports.handler = (event, context, callback) => {
    const response = event.Records[0].cf.response;
    const headers = response.headers;

    // Set HttpOnly Cookie
    headers['set-cookie'] = [{
        key: 'Set-Cookie',
        value: `YourCookieName=YourCookieValue; Path=/; Secure; HttpOnly;`
    }];

    callback(null, response);
};

Replace YourCookieName and YourCookieValue with the actual cookie name and value you wish to set. You can generate or define these values based on your authentication flow, such as after a user successfully logs in.

After you've written your Lambda function, you need to deploy it to AWS Lambda, making sure to select a region that supports Lambda@Edge (e.g., US East (N. Virginia) us-east-1). When configuring the function in AWS Lambda:

• Ensure the Lambda function's execution role (LambdaExecutionRole) has permission to execute Lambda functions and to write logs to Amazon CloudWatch. The basic permissions for Lambda@Edge are automatically managed when you add the function to CloudFront.
• After creating your Lambda function, you need to add it to a CloudFront distribution. Choose the CloudFront distribution that serves your application, and associate the Lambda function with the distribution by creating a new behavior or updating an existing one. Specifically, you want to trigger the function on the Viewer Response CloudFront event.

To automate the deployment and association of the Lambda@Edge function with CloudFront, you'll need a more complex setup involving AWS SAM (Serverless Application Model) or custom resources, which might be beyond the initial scope. However, you can manually create and associate the Lambda function as described above, then adjust the CloudFormation template accordingly for other resources like the S3 bucket.

Given your update on the VersioningConfiguration for the S3 bucket, here's the adjusted section for your CloudFormation template:

  HandTermHistoryBucket:
    Type: 'AWS::S3::Bucket'
    Properties:
      BucketName: 'handterm-history'
      AccessControl: Private
      VersioningConfiguration:
        Status: Disabled

• Introducing HttpOnly Cookies for session management is a secure practice as it prevents client-side scripts from accessing the cookies. The Lambda@Edge function provided is a starting point. Depending on your application's authentication flow, you might need a more dynamic approach to generating and validating cookies.
• If you're not using OAuth, ensure your application securely handles user credentials, using HTTPS for communications and securely managing session tokens or cookies.
• Since Lambda@Edge functions execute in response to CloudFront events, ensure your function is optimized for performance to not introduce significant latency to your application responses.

For a comprehensive solution involving OAuth or more complex authentication and authorization flows, consider exploring AWS Amplify or other AWS services that offer more integrated and managed solutions.

User at 9:50 am, Jun 27, 2024

This is the current template:

# .aws/HandTermCognitoStackTemplate.yml

AWSTemplateFormatVersion: '2010-09-09'
Description: AWS CloudFormation for HandTerm application with HttpOnly Cookies
 and S3 access.

Resources:
 CognitoUserPool:
  Type: AWS::Cognito::UserPool
  Properties:
   UserPoolName: HandTermUserPool
   Schema:
    - Name: email
     Required: true
     Mutable: false
   Policies:
    PasswordPolicy:
     MinimumLength: 8
     RequireUppercase: true
     RequireLowercase: true
     RequireNumbers: true
     RequireSymbols: true

 CognitoUserPoolClient:
  Type: AWS::Cognito::UserPoolClient
  Properties:
   UserPoolId: !Ref CognitoUserPool
   ExplicitAuthFlows:
    - ALLOW_USER_SRP_AUTH
    - ALLOW_REFRESH_TOKEN_AUTH
   GenerateSecret: false

 HandTermIdentityPool:
  Type: AWS::Cognito::IdentityPool
  Properties:
   IdentityPoolName: HandTermIdentityPool
   AllowUnauthenticatedIdentities: false
   CognitoIdentityProviders:
    - ClientId: !Ref CognitoUserPoolClient
     ProviderName: !GetAtt CognitoUserPool.ProviderName

 HandTermHistoryBucket:
  Type: AWS::S3::Bucket
  Properties:
   BucketName: handterm-history
   AccessControl: Private
   VersioningConfiguration:
    Status: Disabled

 LambdaExecutionRole:
  Type: AWS::IAM::Role
  Properties:
   AssumeRolePolicyDocument:
    Version: '2012-10-17'
    Statement:
     - Effect: Allow
      Principal:
       Service:
        - lambda.amazonaws.com
        - edgelambda.amazonaws.com
      Action: sts:AssumeRole
   Policies:
    - PolicyName: LambdaS3Access
     PolicyDocument:
      Version: '2012-10-17'
      Statement:
       - Effect: Allow
        Action: s3:*
        Resource: !Sub arn:aws:s3:::handterm-history/*

# Add more resources as needed, for example, Lambda@Edge function and its association with CloudFront distribution.

Outputs:
 UserPoolId:
  Value: !Ref CognitoUserPool
  Description: The ID of the Cognito User Pool
 UserPoolClientId:
  Value: !Ref CognitoUserPoolClient
  Description: The ID of the Cognito User Pool Client
 HandTermIdentityPoolId:
  Value: !Ref HandTermIdentityPool
  Description: The ID of the Cognito Identity Pool
 HandTermHistoryBucketName:
  Value: !Ref HandTermHistoryBucket
  Description: The name of the S3 bucket for storing user history

I've stored that Lambda@Edge funciton you recommended in .aws/http-only-cookies.js

I noticed that you included the comment

# Add more resources as needed, for example, Lambda@Edge function and its association with CloudFront distribution.

in the template. Will cloudformation provide upload of the Lambda@Edge function through the aws cloudformation deploy command, or will I have to add SAM or CDK functionality to this project?

Codeium at 9:50 am, Jun 27, 2024

To integrate a Lambda@Edge function with your CloudFormation template and deploy it via the aws cloudformation deploy command, you actually don't need to convert the entire project to use AWS SAM (Serverless Application Model) or AWS CDK (Cloud Development Kit). However, CloudFormation itself does not support directly uploading Lambda function code from local files like .aws/http-only-cookies.js in the same way AWS SAM does.

For Lambda@Edge specifically, you can include it in your CloudFormation template by referencing an existing Lambda function ARN and specifying the association with a CloudFront distribution. However, the process of creating the Lambda function, uploading its code, and publishing a version that can be used with Lambda@Edge needs to be done outside the scope of the initial CloudFormation deploy command.

Here's a general approach to achieve your goal:

1. Create the Lambda function in the AWS Management Console or using AWS CLI, specifying the runtime and role. Ensure the function is created in the US East (N. Virginia) region (us-east-1) because Lambda@Edge functions must be created in this region to be globally executed by CloudFront.
2. Upload your function code using the AWS CLI or the AWS Management Console. For example, using AWS CLI:

   aws lambda update-function-code --function-name YourFunctionName --zip-file fileb://path_to_your_function_code.zip

3. Publish a version of your Lambda function. Lambda@Edge requires using a specific version (not $LATEST). You can do this via AWS CLI:

   aws lambda publish-version --function-name YourFunctionName

   Take note of the version ARN, as you'll need it for the next step.

Once your Lambda function is ready and its version is published, update your CloudFormation template to associate this Lambda function with your CloudFront distribution. This step assumes you already have a CloudFront distribution configured. If not, you'll need to add that to your template as well.

  MyCloudFrontDistribution:
    Type: AWS::CloudFront::Distribution
    Properties:
      DistributionConfig:
        # Your distribution config here
        DefaultCacheBehavior:
          # Your cache behavior config here
          LambdaFunctionAssociations:
            - EventType: viewer-response
              LambdaFunctionARN: arn:aws:lambda:us-east-1:123456789012:function:YourFunctionName:YourFunctionVersion

Replace arn:aws:lambda:us-east-1:123456789012:function:YourFunctionName:YourFunctionVersion with the actual version ARN of your Lambda@Edge function.

Now, you can deploy your CloudFormation stack via the AWS CLI:

aws cloudformation deploy --template-file path_to_your_template.yml --stack-name YourStackName --capabilities CAPABILITY_IAM

• Manual Steps Required: The initial creation, uploading, and version publishing of the Lambda@Edge function are outside the CloudFormation deployment flow.
• Region-specific: Lambda@Edge functions must be created in the us-east-1 region.
• Updating Lambda@Edge Functions: To update the function code, you'll need to upload a new version and update the CloudFormation template with the new function version ARN.

For a more automated and integrated approach, consider using AWS SAM, which offers more streamlined support for deploying Lambda functions, including local testing and direct code uploads as part of the deployment process. However, integrating SAM into your workflow would require additional setup and changes to how you manage deployments.

User at 9:59 am, Jun 27, 2024

I am familiar with SAM and I have the SAM CLI installed. I like that it provides a more comprehensive record of what this project is creating and an automated process for updating it.

This project is different than other projects I have deployed with SAM, though, in that this project is a static website deployed to GitHub Pages by using a GitHub Action. That part is currently functioning well. It deploys the site updates every time I commit and push to GitHub.

I wouldn't mind having a second deployment step that I would need to do to deploy to AWS by using aws cloudformation deploy or by using SAM, but I would prefer using SAM since that can also handle the Lambda@Edge deployment in a recordable manner, in case I have to return to this project after a long hiatus and server state has changed.

Can I use SAM in this application to deploy the Lambda@Edge function without conflicting with my existing static site?

Codeium at 10:00 am, Jun 27, 2024

Yes, you can use AWS SAM (Serverless Application Model) alongside your existing static site deployment on GitHub Pages without any conflicts. AWS SAM focuses on deploying and managing resources within AWS, such as Lambda functions, APIs, and other serverless resources, and doesn't interact with or affect how your static site is deployed to GitHub Pages. Using SAM for the AWS-specific part of your project, particularly for deploying Lambda@Edge functions, can simplify the process and make your infrastructure as code more maintainable.

Here’s how you can integrate AWS SAM for deploying the Lambda@Edge function without affecting your static site deployment:

If you haven’t already, initialize a SAM application within your project. You can create a new SAM project in a separate directory or integrate SAM configuration files into your existing project structure. Use the SAM CLI to initialize a new SAM application:

sam init

Choose the runtime that matches your Lambda@Edge function (e.g., Node.js), and select a template that closely matches your use case or start with a quick start template.

Modify the generated template.yaml file to include your Lambda@Edge function. You'll also need to specify the IAM role that grants permission to your Lambda function to interact with necessary AWS services, and configure the function for deployment to CloudFront.

Here's an example snippet for template.yaml that defines a Lambda@Edge function:

Resources:
  MyLambdaAtEdgeFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: index.handler
      Runtime: nodejs14.x
      CodeUri: path/to/your/lambda/code
      Description: A Lambda@Edge function for HttpOnly Cookies
      MemorySize: 128
      Timeout: 5
      Role: arn:aws:iam::123456789012:role/your-lambda-execution-role
      Events:
        CloudFrontEvent:
          Type: CloudFront
          Properties:
            Distribution: YourCloudFrontDistributionId
            EventType: viewer-response

Make sure to replace path/to/your/lambda/code, your-lambda-execution-role, and YourCloudFrontDistributionId with your actual Lambda function code directory, IAM role ARN, and CloudFront distribution ID.

Once your SAM application is configured, you can build it:

sam build

And then deploy it to AWS:

sam deploy --guided

The --guided flag provides an interactive deployment experience where you can set parameters, including stack name, AWS Region, and other deployment configurations. This process creates a CloudFormation stack based on your SAM template.

• Deployment Separation: Your static site and AWS resources are deployed independently. The static site uses GitHub Actions for deployment to GitHub Pages, while AWS resources are managed through SAM and CloudFormation. This separation ensures that deploying one component doesn’t affect the other.
• Version Control: Keep your SAM templates and configuration files in your project’s version control. This inclusion ensures you have a comprehensive record of your infrastructure as code, aiding in future updates or if you return to the project after a hiatus.
• AWS Region: Lambda@Edge functions are replicated across AWS locations globally but must be created in the US East (N. Virginia) region (us-east-1). Ensure your SAM deployment specifies this region if it's not already your default.

By following these steps, you can effectively manage and deploy your Lambda@Edge functions with AWS SAM without interfering with your existing static site deployment process on GitHub Pages.

User at 10:31 am, Jun 27, 2024

Inside the Lambda@Edge, I have this:

  headers['set-cookie'] = [{
    key: 'Set-Cookie',
    value: `handterm-history=YourCookieValue; Path=/; Secure; HttpOnly;`
  }];

I am not sure what to put in YourCookieValue. Is that something I should calculate from the userId or something like that?

Codeium at 10:32 am, Jun 27, 2024

Yes, setting YourCookieValue to a value that correlates with the user's session or identity can be a good approach, especially for maintaining session integrity and security in your application. The exact value you choose for the cookie will depend on your application's authentication and session management strategy. Here are a few approaches you might consider:

Generate a unique session identifier (session ID) when the user successfully logs in. This session ID can then be stored in your backend (e.g., a database) alongside session data, such as the user ID, session expiration time, and any other relevant information. The session ID would then be used as the cookie value:

value: `handterm-history=SESSION_ID; Path=/; Secure; HttpOnly;`

If you're using tokens for session management (like JWTs), you can place a securely signed token as the cookie value. Ensure the token is signed and possibly encrypted to prevent tampering. Tokens can encode user identity and other claims, which can be verified and decoded by your server to authenticate requests.

value: `handterm-history=TOKEN; Path=/; Secure; HttpOnly;`

• Security: Ensure the value is generated in a secure manner. If using session IDs, they should be sufficiently random and unpredictable to prevent guessing attacks. If using tokens, they should be signed with a secure algorithm.
• HttpOnly: Setting the HttpOnly flag, as you have done, prevents client-side JavaScript from accessing the cookie, mitigating the risk of cross-site scripting (XSS) attacks.
• Secure: The Secure flag ensures that the cookie is sent only over HTTPS, protecting it from man-in-the-middle attacks.
• Path: The Path=/ attribute is appropriate if you want the cookie to be sent for all requests to your domain. Adjust if needed for more specific paths.

If you decide to use a JWT as the cookie value, here’s a simple example using Node.js:

1. Install jsonwebtoken Package: First, ensure you have the jsonwebtoken package installed in your project.

   npm install jsonwebtoken

2. Generate JWT:

   const jwt = require('jsonwebtoken');
   
   const user = { id: 'user123', name: 'John Doe' }; // Example user object
   const secretKey = 'yourSecretKey';
   const token = jwt.sign(user, secretKey, { expiresIn: '1h' });
   
   // Set the JWT as the cookie value
   headers['set-cookie'] = [{
     key: 'Set-Cookie',
     value: `handterm-history=${token}; Path=/; Secure; HttpOnly;`
   }];

In this example, replace 'yourSecretKey' with a secure, private key used for signing the JWT. The expiresIn option sets the token to expire in 1 hour. Adjust the payload and options according to your requirements.

Remember, the strategy you choose should align with your application's security requirements and user management strategy.

User at 10:36 am, Jun 27, 2024

This is my current code for authorization.

Would my Lambda@Edge accept some value from the context parameter and use tht for the cookie value?

// src/lib/useAuth.ts

import { useState } from 'react';
import { CognitoUserPool, AuthenticationDetails, CognitoUser, CognitoUserAttribute, CognitoRefreshToken } from 'amazon-cognito-identity-js';

const poolData = {
 UserPoolId: 'us-east-1_apGvoR62E',
 ClientId: '776i4gt2nij7ce30m9jlo9fcq0'
};

const userPool = new CognitoUserPool(poolData);

export const useAuth = () => {
 const [isLoggedIn, setIsLoggedIn] = useState(false);

 const signUp = (username: string, password: string, email: string, callback: (error: any, result: any) => void) => {
  const attributeList = [
   new CognitoUserAttribute({
    Name: 'email',
    Value: email
   }),
   // Add other attributes here
  ];

  userPool.signUp(username, password, attributeList, attributeList, (err, result) => {
   if (err) {
    console.error(err);
    callback(err, null);
    return;
   }
   console.log('Sign up successful!', result);
   callback(null, result);
  });
 };

 const changePassword = (oldPassword: string, newPassword: string, callback: (error: any, result: any) => void) => {
  const cognitoUser = userPool.getCurrentUser();
  if (cognitoUser) {
   cognitoUser.changePassword(oldPassword, newPassword, (err, result) => {
    if (err) {
     console.error(err);
     callback(err, null);
     return;
    }
    console.log('Password changed successfully!', result);
    callback(null, result);
   });
  } else {
   console.error('User not authenticated!');
   callback('User not authenticated!', null);
  }
 };

 const getCurrentUser = () => {
  const result = userPool.getCurrentUser()?.getUsername();
  return result;
 }


 const login = (username: string, password: string, callback: (error: any, result: any) => void) => {
  const authenticationDetails = new AuthenticationDetails({
   Username: username,
   Password: password,
  });

  const cognitoUser = new CognitoUser({
   Username: username,
   Pool: userPool
  });

  cognitoUser.authenticateUser(authenticationDetails, {
   onSuccess: (session) => {
    console.log('Authentication successful!', session.getIdToken().getJwtToken());
    setIsLoggedIn(true);
    // Store tokens in sessionStorage
    sessionStorage.setItem('idToken', session.getIdToken().getJwtToken());
    sessionStorage.setItem('accessToken', session.getAccessToken().getJwtToken());
    sessionStorage.setItem('refreshToken', session.getRefreshToken().getToken());
    const refreshTokenTimeout = (
     session.getIdToken().getExpiration() 
     - Math.floor(Date.now() / 1000) - 300
    ) * 1000;
    setTimeout(refreshSession, refreshTokenTimeout);
    callback(null, session);
   },
   onFailure: (err) => {
    console.error('Authentication failed!', err);
    setIsLoggedIn(false);
    callback(err, null);
   },
   // Add newPasswordRequired, mfaRequired, etc. as needed
  });
 };

 const refreshSession = () => {
  const currentUser = userPool.getCurrentUser();
  if (currentUser != null) {
   currentUser.getSession((err: any, session: { isValid: () => any; getRefreshToken: () => CognitoRefreshToken; }) => {
    if (err) {
     console.error(err);
     return;
    }
    if (session.isValid()) {
     currentUser.refreshSession(session.getRefreshToken(), (refreshErr, newSession) => {
      if (refreshErr) {
       console.error(refreshErr);
      } else {
       // Update state/session storage with new tokens
       console.log('Session refreshed successfully.', newSession.getIdToken().getJwtToken());
       // Optionally decode new ID token for user data
      }
     });
    }
   });
  }
 };

 const logout = () => {
  if (userPool.getCurrentUser()) {
   userPool.getCurrentUser()?.signOut();
  }
  setIsLoggedIn(false);
 };

 return { isLoggedIn, login, logout, signUp, refreshSession, getCurrentUser, changePassword };
};

Codeium at 10:37 am, Jun 27, 2024

In your current architecture, the useAuth function handles authentication with Amazon Cognito within your React application. This means the authentication process, including token generation, occurs client-side. However, the Lambda@Edge function for setting HttpOnly cookies operates at the CDN level (CloudFront), and it's triggered by CloudFront events, not directly by client-side operations.

To utilize values from your authentication process (like a session identifier or token) in your Lambda@Edge function for setting cookies, you need to pass these values from your client-side application to the server in a secure manner. However, directly accessing context parameters like user IDs or tokens in Lambda@Edge from client-side authentication is not straightforward because Lambda@Edge functions are designed to modify HTTP requests or responses, not to directly share runtime data with client-side code.

A common way to handle this is to use the tokens generated by Amazon Cognito (ID token, access token) and securely transmit them to the server (Lambda@Edge in your case) via HTTP headers or query parameters in requests that require authentication. Then, Lambda@Edge can extract these tokens, validate them, and potentially use their information to set specific HttpOnly cookies.

However, for setting HttpOnly cookies specifically aimed at enhancing session management or security, consider these points:

1. Token Storage and Transmission: After successful authentication, you store tokens in sessionStorage. For Lambda@Edge to set a cookie based on these tokens, your application would need to send these tokens in subsequent requests to your server/CloudFront distribution. This approach might not align with the security advantages of HttpOnly cookies since you'd be relying on client-side logic to send tokens back to the server.

2. Direct Cookie Setting by Lambda@Edge: If you're using Lambda@Edge to set HttpOnly cookies without relying on client-side token handling, you might consider generating a session identifier or token server-side (or within the Lambda@Edge function) and then setting that value as a cookie. This approach is more secure for session management but requires a server-side component or mechanism to validate these session identifiers or tokens on subsequent requests.

3. Secure Token Validation: If you choose to send Cognito tokens to Lambda@Edge for validation or for use in cookie generation, ensure the Lambda@Edge function validates the token (e.g., by checking the signature against the AWS Cognito public keys) before trusting any data within it. AWS Cognito provides public keys for token verification, and libraries like jsonwebtoken can help with this in a Node.js environment.

If transmitting tokens to Lambda@Edge for the purpose of setting a session cookie based on validated token data:

• Send Token in Secure Headers: On requests needing authentication, include the ID or access token in a secure, HTTP-only header. This requires modifying client-side logic to attach the token.
• Lambda@Edge Token Validation and Cookie Setting: Modify the Lambda@Edge function to read the token from the request headers, validate it, and if valid, use some part of its payload (e.g., the sub claim for the user ID) as the value for setting an HttpOnly cookie.

The direct interaction between client-side useAuth functions (like generating YourCookieValue) and Lambda@Edge for setting HttpOnly cookies is limited. A shift in strategy towards either server-side token generation and validation or secure transmission of client-generated tokens to the server for validation and cookie setting is required. The optimal approach depends on your application's specific security requirements, user flow, and architecture.

User at 10:43 am, Jun 27, 2024

Ok, I think I understand.

My current app is a client-side static site hosted in GitHub Pages. I would like to pursue your idea of a shift in strategy towards a server-side token generation and validation, as long as that can still work with a static website deployed to GitHub Pages.

Do you think that would be the better approach? The static content would be in GitHub Pages, but any user-private data would be in AWS and handled by AWS secure services.

Codeium at 10:44 am, Jun 27, 2024

Yes, adopting a strategy that combines your static site on GitHub Pages with server-side token generation and validation using AWS services is a viable and secure approach. This method allows you to leverage the best of both worlds: serving static content efficiently from GitHub Pages while handling authentication, authorization, and user-private data securely through AWS. Here's how this strategy could work for your application:

• Static Content: Continue hosting your static content (HTML, CSS, JavaScript) on GitHub Pages. This content is publicly accessible and doesn't contain sensitive user data.
• Client-Side Authentication Flow: Use AWS Cognito for user authentication. Your static site can include client-side JavaScript that interacts with Cognito for sign-ups, logins, and handling authentication tokens.

• Secure Token Handling and Authorization: Instead of relying on the client to handle tokens securely (which exposes them to risks), use AWS services (Lambda, API Gateway) to create a server-side layer that manages authentication tokens and user sessions.
• API Gateway and Lambda: Create an API with AWS API Gateway that serves as the backend for your static site. Use Lambda functions to handle API requests, such as validating Cognito tokens, generating HttpOnly cookies, and accessing or modifying user-private data stored in AWS (e.g., in DynamoDB, S3).
• Lambda@Edge for Enhanced Security: Use Lambda@Edge in conjunction with CloudFront (AWS's CDN) to intercept requests to your static site or API. Lambda@Edge can inspect and modify HTTP requests and responses, allowing you to implement additional security measures, such as validating tokens or setting HttpOnly cookies, closer to your users.

• Security: By handling sensitive operations server-side (AWS), you minimize the exposure of tokens and sensitive data to the client-side environment, reducing the risk of XSS and CSRF attacks.
• Performance: Serving static content from GitHub Pages is fast and efficient, while dynamic content and operations that require security are handled by AWS, ensuring that user-private data remains secure.
• Scalability: AWS services like Lambda, API Gateway, and CloudFront can scale automatically to handle varying loads, making your application both performant and resilient.

• Architecture Complexity: This approach introduces more components into your architecture (e.g., API Gateway, Lambda), which may increase the complexity of your setup and require additional configuration and maintenance.
• Costs: While GitHub Pages hosting is free for public and private repositories, AWS services incur costs based on usage. It's important to monitor and manage your AWS usage to keep costs in check, especially for Lambda, API Gateway, and CloudFront.

Adopting server-side token generation and validation for a static site hosted on GitHub Pages is a sound approach that enhances security without sacrificing the benefits of static site hosting. By leveraging AWS services for sensitive operations, you create a robust architecture that efficiently separates public content from secure, user-specific functionalities.

User at 10:45 am, Jun 27, 2024

I think that would mean we have to rewrite useAuth. How would we do that?

Codeium at 10:46 am, Jun 27, 2024

To adapt your existing useAuth hook for a scenario where authentication and session management are handled by AWS services in a server-side manner, you would need to modify it to interact with an API (built with AWS API Gateway and Lambda functions) for operations like signing up, logging in, and session management. This API would communicate with Amazon Cognito on the server side, ensuring secure handling of tokens and user sessions.

Here's an outline of how you can rewrite the useAuth hook to work with a server-side authentication model:

First, assume you have the following API endpoints set up using AWS API Gateway, which interact with AWS Lambda functions:

• POST /signup: For user registration
• POST /login: For user login, returns session data and sets HttpOnly cookie
• GET /logout: To invalidate the user session
• POST /refresh-session: To refresh the session tokens

Each Lambda function behind these endpoints would interact with Amazon Cognito as needed.

import { useState, useEffect } from 'react';
import axios from 'axios';

const API_BASE_URL = 'https://your-api-gateway-url';

export const useAuth = () => {
  const [isLoggedIn, setIsLoggedIn] = useState<boolean>(false);

  useEffect(() => {
    // Optionally check session validity on hook mount
    const checkSession = async () => {
      try {
        // This could be a call to a `/session` endpoint that verifies the session
        await axios.get(`${API_BASE_URL}/session`);
        setIsLoggedIn(true);
      } catch (error) {
        console.error('Session check failed:', error);
        setIsLoggedIn(false);
      }
    };

    checkSession();
  }, []);

  const signUp = async (username: string, password: string, email: string) => {
    try {
      await axios.post(`${API_BASE_URL}/signup`, { username, password, email });
      // Handle post-signup logic (e.g., auto-login or redirect to login page)
    } catch (error) {
      console.error('Signup failed:', error);
      throw error;
    }
  };

  const login = async (username: string, password: string) => {
    try {
      const response = await axios.post(`${API_BASE_URL}/login`, { username, password });
      // The API should set an HttpOnly cookie directly, no need to handle tokens here
      setIsLoggedIn(true);
      return response.data; // Return session data if needed
    } catch (error) {
      console.error('Login failed:', error);
      throw error;
    }
  };

  const logout = async () => {
    try {
      await axios.get(`${API_BASE_URL}/logout`);
      setIsLoggedIn(false);
    } catch (error) {
      console.error('Logout failed:', error);
      throw error;
    }
  };

  const refreshSession = async () => {
    try {
      // This endpoint should refresh the session and set a new HttpOnly cookie
      await axios.post(`${API_BASE_URL}/refresh-session`);
      setIsLoggedIn(true);
    } catch (error) {
      console.error('Session refresh failed:', error);
      setIsLoggedIn(false);
      throw error;
    }
  };

  return { isLoggedIn, login, logout, signUp, refreshSession };
};

• HttpOnly Cookie Handling: The client-side code no longer directly handles tokens. Instead, the server (AWS Lambda) is responsible for setting an HttpOnly cookie via the API responses. This cookie is automatically sent with each subsequent request by the browser but is not accessible via JavaScript.
• Session Validation and Refresh: You should implement server-side logic to validate sessions (e.g., by verifying the HttpOnly cookie) and refresh them as needed. The client-side code can call /refresh-session as necessary, based on application logic or in response to API requests failing due to expired sessions.
• Error Handling: The example includes basic error handling. Depending on your application's requirements, you may want to implement more sophisticated error handling and user feedback mechanisms.
• Security: Ensure your API is secured and implements proper validation, error handling, and protection against common web vulnerabilities.

This approach moves sensitive operations like token handling to the server side, enhancing the security of your application while still allowing you to maintain a static frontend hosted on GitHub Pages.

User at 11:15 am, Jun 27, 2024

You said "This cookie is automatically sent with each subsequent request by the browser but is not accessible via JavaScript."

How are save requests handled, when I want to save data to S3?

Codeium at 11:16 am, Jun 27, 2024

When you want to save data to S3 securely in an application where authentication and session management are handled server-side, and where an HttpOnly cookie is used to manage session state, the process involves a few steps that ensure security and proper authorization. The HttpOnly cookie, while not accessible via JavaScript, is automatically sent with each HTTP request made to your server or API, allowing your server-side logic to authenticate and authorize the request before interacting with AWS S3.

Here's a high-level overview of how save requests can be handled securely:

When the user performs an action that requires data to be saved to S3, the client-side application sends a request to your backend service (e.g., via AWS API Gateway) instead of directly interacting with S3. This request includes any necessary data but relies on the HttpOnly cookie for session authentication.

For example, to save a new document, your client-side code might make a POST request:

const saveDocument = async (documentData) => {
  const response = await axios.post(`${API_BASE_URL}/saveDocument`, documentData);
  return response.data; // Handle the response accordingly
};

The server (e.g., an AWS Lambda function triggered by API Gateway) receives the request and automatically has access to the HttpOnly cookie sent by the browser. The server should then:

• Validate the session based on the cookie (e.g., by verifying it against session information stored in a database or using AWS Cognito for session validation).
• Determine if the user is authorized to perform the requested action (e.g., saving data to S3).

Once the request is authenticated and authorized, the server-side logic interacts with S3 to save the data. This interaction is securely handled server-side, using AWS SDKs and the server's AWS credentials (with the appropriate IAM permissions).

For example, a Lambda function might use the AWS SDK for JavaScript to upload the document:

const AWS = require('aws-sdk');
const s3 = new AWS.S3();

const saveDataToS3 = async (bucketName, key, data) => {
  const params = {
    Bucket: bucketName,
    Key: key,
    Body: JSON.stringify(data),
  };
  return s3.putObject(params).promise();
};

After the data is successfully saved to S3, the server sends a response back to the client. This response can include confirmation of the action, any relevant data, or IDs that the client might need.

• IAM Permissions: Ensure the IAM role assumed by your AWS Lambda function has the minimal necessary permissions to perform actions on S3. Follow the principle of least privilege.
• Input Validation: Always validate and sanitize inputs on the server side to prevent injection attacks and ensure data integrity.
• Secure Transmission: Ensure that your API Gateway and client-server communications are secured using HTTPS to protect data in transit.

By following this approach, your application can securely handle save requests to AWS S3, leveraging server-side session management and the inherent security benefits of HttpOnly cookies, without exposing sensitive operations or credentials to the client side.

User at 11:29 am, Jun 27, 2024

How can I implement the getCurrentUser function with the new strategy?

Codeium at 11:30 am, Jun 27, 2024

Implementing getCurrentUser with the new server-side authentication strategy involves a slightly different approach compared to direct client-side access. Since your authentication state is managed server-side, and you're using HttpOnly cookies for session management, you'll need to rely on a server-side endpoint to determine the current user's identity based on the session information associated with the HttpOnly cookie.

First, you need to create an endpoint in your backend (e.g., an AWS Lambda function triggered by API Gateway) that can respond with the current user's information. This endpoint would read the session identifier from the HttpOnly cookie, validate it, possibly query Amazon Cognito or your session store to retrieve the session details, and then return the user's information to the client.

Example of such a Lambda function in Node.js:

const AWS = require('aws-sdk');
const cognito = new AWS.CognitoIdentityServiceProvider();

exports.handler = async (event) => {
  try {
    // Assume the session token or user ID is stored in the HttpOnly cookie
    // You need to extract and validate it. Here, we just show a placeholder.
    const userSub = extractUserSubFromCookie(event.headers.Cookie);

    // Assuming you have the user's sub (unique identifier), fetch user details from Cognito
    const userPoolId = 'yourUserPoolId';
    const params = {
      UserPoolId: userPoolId,
      Filter: `sub = "${userSub}"`,
    };

    const userData = await cognito.listUsers(params).promise();
    if (userData.Users.length > 0) {
      const user = userData.Users[0];
      // Simplify the response for the example
      return {
        statusCode: 200,
        body: JSON.stringify({
          username: user.Username,
          attributes: user.Attributes,
        }),
      };
    } else {
      return { statusCode: 404, body: 'User not found' };
    }
  } catch (error) {
    console.error(error);
    return { statusCode: 500, body: 'Server error' };
  }
};

// Placeholder function for extracting user identifier from cookie
function extractUserSubFromCookie(cookieHeader) {
  // Implement cookie parsing to extract the session/user identifier
  return 'extractedSub';
}

On the client side, you can adjust the getCurrentUser function to make an HTTP request to the new endpoint, which will use the session cookie to authenticate and return the current user's details.

Example in your React application:

import axios from 'axios';

const API_BASE_URL = 'https://your-api-gateway-url';

const getCurrentUser = async () => {
  try {
    const response = await axios.get(`${API_BASE_URL}/currentUser`);
    return response.data; // Contains username, attributes, etc.
  } catch (error) {
    console.error('Error fetching current user:', error);
    return null;
  }
};

• Security: Ensure the endpoint securely validates the session token or identifier extracted from the HttpOnly cookie. It should only return user information if the session is valid and active.
• CORS: If your backend and frontend are served from different origins, configure CORS (Cross-Origin Resource Sharing) on your API Gateway to allow requests from your frontend domain.
• Https Only: Make sure that communication between the client and server is over HTTPS to protect the integrity and confidentiality of the transmitted data.

By following this approach, you effectively delegate the responsibility of identifying the current user to the server side, which can securely manage sessions and user information while leveraging HttpObjects for enhanced security.