I saw a video on YouTube about how to make your business card smart with a simple NFC sticker. The problem is that while you can program a vCard into a sticker, iOS devices don’t support them yet. The only way to get an iPhone to read an NFC vCard is to host the vCard file on the web. Then it hit me. Why not host the vCard on AWS using only free tier resources.

The obvious solution was Lambda and Lambda Function URLs since they are completely free. Plus, you can be sure that AWS will still be around in 5 or 10 years, so your digital business card will still be running.
Also, it’s very easy to update your information if something changes, you don’t have to buy a new one. Which is good for the environment too!

During development I ran into issues that required creating extra policies to make it work. Since I wanted to make it as simple as possible for everyone to use it I created a CloudFormation template that creates all the resources for you.
And when you no longer need it, CloudFormation can delete all the used resources. But why would you do that when it’s completely free.

The code is written in Node.js 18.x and produces a v. 3.0 vCard. You might ask why not v. 4.0 and the answer is simple. Apple doesn’t support it and I wanted to make it as compatible as possible.
The other problem I faced is that according to the vCard specifications you can link an image URL as your photo, but Apple devices don’t support that either. The photo should be Base64 encoded in your vCard.
That is why CloudFormation creates an S3 bucket where you can store your photo (avatar.jpeg) and the Lambda function will convert it to Base64 and include it in your card.

Not just Apple, AWS has some weird things too. For example, when you create a FunctionURL for your Lambda function, this URL is not defined in your Lambda environment variable. To get the FunctionURL, you need to grant the GetFunctionUrlConfig role to read your function URL. Since a vCard allows you to define the source of the vCard where you can always get the latest version, I had to create a policy and attach it to the Lambda role to include the FunctionURL in the vCard.

The other issue I faced is that while you can include your Lambda code in CloudFormation, it creates an index.js file instead of an index.mjs which is required for Node.js 18.x. There is a solution to include the code in an S3 bucket and CloudFormation will retrieve the code from there, but then you are stuck with the region where your S3 bucket is. So I created two CloudFormation templates.
If you want the easiest installation and don’t want to change your region, use the default template. This will run in US East (N. Virginia). If you want to host your business card in another region, use the template-with-code.yaml instead, but you will need to rename index.js to index.mjs for the code to work.

All the source code is available on GitHub under the Apache 2.0 license. See the GitHub page for detailed installation information.
Use template.yaml if you want the simplest installation.
If you want to specify the region in which the resources are created, use the template-with-code.yaml stack instead and rename the index.js source file to index.mjs.

I hope this little code is as useful as it was fun to write it.

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I chose Mastodon as my primary platform because it is the most popular of all. You may choose otherwise, as these networks can communicate seamlessly with each other no matter what server you are running.

Twitter (now: X) as a commercial company has the right to restrict or commercialize its API, which can be a struggle for startups or small developers. Mastodon is not only free and open source, but also much more developer friendly. One such feature is the support of bot accounts. You are not limited at these accounts, in fact you are encouraged to use them. In Mastodon, you can specifically mark if an account is a bot, making it more transparent to everyone.

The first step is always the hardest, choosing your Mastodon server. There are many to choose from, some are for specific communities, some are geographically restricted. If you are unsure, just stick with the oldest: mastodon.social.

Create an account here and check the This is an automated account box under your profile. This will let others know that this is a bot account. Under Development, create a new application and select the appropriate permissions. Since my bot will only publish, I only selected write:statuses.

In a previous blog post I created a website for Hungarian tech conferences. I will use this as my input source. Currently this site doesn’t offer an easy way to export information, so I modified the Jekyll code to generate a CSV file for the upcoming events. This way I can parse the data more easily.

The Serverless Approach

From the title of this post, you have probably guessed that I am going to take a serverless approach. I don’t want to deal with security updates and patches. I just want this bot to work with very little maintenance.

Tip: Choose arm64 as your Lambda architecture because it is cheaper to run.

There are a handful of API clients for Mastodon to choose from. Since I will be using Node.js 18.x for the runtime, I wanted to find one that was compatible with it. My choice was Masto.js, which is maintained quite frequently and supports most of the Mastodon API features.

To download CSV data from techconf.hu, I will use Axios as in my previous projects. As for parsing CSV data my choice was csv-parse (watch out there are multiple CSV parsers out there, some names may only be different with a hyphen). I then created separate Layers for each function and attached it to my Lambda function.

Making it all work

The code is pretty simple. First I download the CSV file and parse it with csv-parse. Then I set up the Toot (Mastodon’s phrase for Tweet) and publish it with Masto.js.

One problem I faced is that in Mastodon every Toot has a language variable. If you don’t set it specifically, it defaults to the one set in your Mastodon account.

Tip: Since the Fediverse is so decentralized, it is a good idea to tag all your posts.

import { parse } from 'csv-parse';
import { login } from 'masto';
import axios from 'axios';

export const handler = async(event) => {
    var tweet = "Upcoming Hungarian Tech Conferences 🇭🇺\n\n";
    var conferencesThisWeek = false;
    const currentDate = new Date();
    const endOfWeek = new Date(new Date().setDate(new Date().getDate() + 7));
    currentDate.setHours(0,0,0,0);
    endOfWeek.setHours(0,0,0,0);
    var conferenceDate;
    var csv;
    
    await axios({
        url: 'https://techconf.hu/conferences.csv',
        method: 'GET',
        responseType: 'blob'
    }).then((response) => {
        csv = response.data;
    });
    
    const parser = parse(csv, {
        delimiter: ",",
        from_line: 2
    });
    
    for await (const record of parser) {
        conferenceDate = new Date(record[3]);
        if (currentDate <= conferenceDate && conferenceDate <= endOfWeek) {
            tweet += '👉 ' +record[0] + ' (' + record[2] + ')\n📅 ' + record[3] + ' - ' + record[4] + '\n🔗 ' + record[1] + '\n\n';
            conferencesThisWeek = true;
        }
    }
    
    if (conferencesThisWeek) {
        tweet += '#Hungary #Technology #Conference';
        
        const masto = await login({
            url: 'https://mastodon.social/api/v1/',
            accessToken: ''
        });
    
        await masto.v1.statuses.create({
            status: tweet,
            visibility: 'public',
            language: 'en'
        });
    }
    
    // TODO implement
    const response = {
        statusCode: 200,
        body: JSON.stringify('Hello from Lambda!'),
    };
    return response;
};

Scheduling

The easiest way to schedule a Lambda function is to use the Amazon EventBridge Scheduler. Simply select your schedule pattern and the Lambda function as the target, and it will execute your code at the given time.

Final Thoughts

Did I mention the best part? This is all free. The services I used are all covered by the AWS Free Tier (as of this writing).

Feel free to create similar bots or improve my code or just follow my bot at: https://mastodon.social/@techconf

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The basics: S3 static website hosting

Hosting your static website has never been easier. With Amazon S3 static hosting, you can serve your static pages by simply uploading it to an S3 bucket and enabling public access (be sure to name your bucket as your domain name). You can find a lot of articles on the web that explain how to set up S3 static hosting, which is why I am not going to go into any further details here.

But there are limitations: S3 static hosting doesn’t support HTTPS, the de-facto-minimum for website hosting. To use HTTPS, you need to set up Amazon CloudFront. This comes with a lot of extra features like GeoIP restrictions, caching and a free SSL certificate. Not to mention, you can finally disable your S3 public access (which could be a security risk) and give limited access to CloudFront only (with a bucket policy).

Pro tip: Give CloudFront ListBucket permissions in your S3 bucket policy, otherwise the client will not receive HTTP status codes, including a 404 when trying to access non-existent content:

Mishi

{
    "Version": "2008-10-17",
    "Id": "PolicyForCloudFrontPrivateContent",
    "Statement": [
        {
            "Effect": "Allow",
            "Principal": {
                "Service": "cloudfront.amazonaws.com"
            },
            "Action": "s3:ListBucket",
            "Resource": "arn:aws:s3:::roadtoaws.com",
            "Condition": {
                "StringEquals": {
                    "AWS:SourceArn": "arn:aws:cloudfront::111111111111:distribution/AAAAAAAAAAAAA"
                }
            }
        },
        {
            "Sid": "AllowCloudFrontServicePrincipal",
            "Effect": "Allow",
            "Principal": {
                "Service": "cloudfront.amazonaws.com"
            },
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::roadtoaws.com/*",
            "Condition": {
                "StringEquals": {
                    "AWS:SourceArn": "arn:aws:cloudfront::111111111111:distribution/AAAAAAAAAAAAA"
                }
            }
        }
    ]
}

Because of the caching involved with CloudFront, this is not ideal for development. You either have to test your code locally or without HTTPS enabled.  This is the main reason why I would still like to see HTTPS support in S3 in the future.

Make it dynamic

Static websites are a thing of the past. You will most likely need some kind of dynamic content. While there are a lot of services that provide functionality, like E-mail sending, Comments, that you could include in your static code to make it dynamic, you’d most likely have to write your own code. This is where Lambda Function URLs come in handy. With a simple Lambda function, you can execute code or use other AWS resources that you can invoke with a simple HTTP request in your browser. But how do you restrict it to a specific IP, domain, or CloudFront?

AWS recommends authenticating through IAM, and while this is really a secure way, it makes development challenging.  The first thing you see is CORS where you can set your origin to a domain. Unfortunately, this didn’t work for me the way I wanted it to. This doesn’t restrict your Lambda from being called from any IP. You can also set an X-Custom header here, but that doesn’t really limit external access.

Then you look for matching IAM permissions that you can attach to Lambda functions. In the available Policies you can find InvokeFunctionUrl where you can add an IP address to limit the invocation to a specific IP. This sounds great! You create a policy and attach it to your Lambda Role. Unfortunately, this does not restrict your Lambda access either.

So what was my solution?

1. Restrict in code

The first obvious solution is to check the source IP with your Lambda function. Here is a sample code in Node.js (you can find a similar code for other languages online):

const ipAddress = event.identity.sourceIP;

if (ipAddress === '52.84.106.111') {
  const error = {
      statusCode: 403,
      body: JSON.stringify('Access denied'),
  };
  
  return error;
} else {
  const hello = {
      statusCode: 200,
      body: JSON.stringify('Hello World!'),
  };
  
  return hello;
}

While this obviously works, you’re adding extra code to a Lambda function that’s primary role is to do something else. Not to mention that this will increase the runtime and the resources used by Lambda. Most importantly, how can you be sure that the IP you get in the sourceIP variable is really the IP the client comes from.

My biggest concern with this solution was that I not only wanted to restrict my functions to one specific IP but to the whole CloudFront distribution – so that I can be sure that it is called from one of my static pages –. With this method, it would be a hassle to maintain an up-to-date list of all CloudFront servers.

2. reCAPTCHA

Yes, you heard it right, Google reCAPTCHA. This may sound strange at first, but this is the solution I have implemented in my work and provides the solutions to the above challenges.

Embeding the reCAPTCHA code in your static web pages is a good idea. In fact, Google recommends that you include the code in all of your pages – not just the ones that you need it, such as form validations – because that way the algorithm can more effectively detect fraudulent use. Within the lambda function, I can now validate whether or not the user really invoked my Lambda function URL from my static web page. Here is the code I use to verify the reCAPTCHA request:

const gRecaptchaResponse = event.queryStringParameters["g-recaptcha-response"];
    
    var verificationUrl = "https://www.google.com/recaptcha/api/siteverify?secret=AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA&response=" + gRecaptchaResponse;
    const recaptchaResult = await getRequest(verificationUrl);
    
    if (false == recaptchaResult.success || 0.5 > recaptchaResult.score) {
      return error;
    }

In conclusion

S3 static website hosting is the easiest way to start with your serverless journey. While there are obstacles ahead you can always find a serverless solution.

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Lambda environment variables are a key-pair of strings that are stored in a function’s version-specific configuration. The latter is important if we use versioning in Lambda. For now, we will focus on the key-pair part, we will talk about Lambda versions at a later time.

Defining environment variables

We can specify environment variables under the Configuration tab, Environment variables section.

Clicking on Edit we can set the key and value of the environment variable. For this tutorial let’s create two variables: one for storing a username and another one for storing a password.

After clicking Save our environment variables are created and are available through the Lambda runtime. We can access them with the process environment, like this:

const username = process.env.username;
const password = process.env.password;

Creating a key for encryption

Our password is a piece of very sensitive information and we would like to modify our code that only our Lambda code can decrypt it. Environment variables support encryption with AWS Key Management Service (KMS).

Let’s go to the KMS Console and create a new key. Under Customer managed keys we click Create key.

We then configure the key type to Symmetric and name our key “simple-api-key” under Alias. You can change the alias at any time. For educational purposes let’s not define key administrative permissions and key usage permissions for now.

Encrypting Lambda environment variables with KMS

Now when we go back to Lambda let’s check the Enable helpers for encryption in transit option. A new Encrypt button appears next to each variable. When clicking on Encrypt we can now select our newly created key.

Decrypting our variable

If we look at our variable or print out it’s value from Lambda we would see something like this: AQICAHhc385PwJyf/tV5ZOhskZFcr5b6NMe/u3YFxJEWOhlnxQG776g/ozncvTV1p5KoSQucAAAAZzBlBgkqhkiG9w0BBwagWDBWAgEAMFEGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMGdpuISr9cRZoNj8TAgEQgCTHd1A1f6zmXa7cCbt8Q9UJqSetCvZ6m/I8VZuLC54k/0934ZE=

In order to decrypt it we need two things:

1. decrypt the variable with the KMS Decrypt operation
2. grant our function permission to call the KMS Decrypt operation

First let’s modify our code to decrypt our variable. Here is a sample code:

const plainUsername = process.env.username;
const encryptedPassword = process.env.password;
let decryptedPassword;

if (!decryptedPassword) {
    const kms = new AWS.KMS();
    try {
        const req = {
            CiphertextBlob: Buffer.from(encryptedPassword, 'base64'),
            EncryptionContext: {
                LambdaFunctionName: process.env.AWS_LAMBDA_FUNCTION_NAME
            },
        };
        const data = await kms.decrypt(req).promise();
        decryptedPassword = data.Plaintext.toString('ascii');
    } catch (err) {
        console.log('Decrypt error:', err);
        throw err;
    }
}

When executing this code we will get an error in CloudWatch:

“errorType”:”AccessDeniedException”,”errorMessage”:”The ciphertext refers to a customer master key that does not exist, does not exist in this region, or you are not allowed to access.”

In order to decrypt the environment variable, our function needs access to the key that we used to encrypt it. Let’s go back once more to the KMS Console and modify its Key users. We now add our Lambda execution role to the key users. In our case simple-api-role.

And Done! We have successfully created Lambda environment variables that we can now use in multiple source files and secured our password with KMS!

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Cognito User Pools

Amazon Cognito is a simple and Secure User Sign-Up, Sign-In, and Access Control tool. It can manage User Pools and Identity Pools. User pools are user directories that provide sign-up and sign-in options for your app users. Identity pools provide AWS credentials to grant your users access to other AWS services.

For our API Gateway, we will create a Cognito User Pool that will handle all of our authorization tasks, including managing usernames, passwords, and access tokens.

Let’s start with Cognito and selecting Manage User Pools. Here we Create a user pool. We name our pool simple-api-AUTH and review the Step through settings as we customize our pool. Remember that we cannot change these attributes after we have created the pool. Policies and other pool settings can be changed later but attributes cannot. When we are at the “App client” settings we create a new app client for our API Gateway.

Here we set up our App client. For simplicity, we will uncheck the Generate client secret option and enable the ALLOW_ADMIN_USER_PASSWORD_AUTH that we will need for our Lambda function to access.

Our User Pool is now ready. It’s that easy.

Adding a user to a Cognito User Pool

We have several options to create users in our user pool. The default settings allow users to sign themselves up. We can create a simple UI or enable other identity providers like Facebook or “Sign in with Apple”. For simplicity, we will create the user manually under Users and groups.

After we have created the user the user will receive an Email with the following information:

Your username is misi and temporary password is 00eEhtI;.

It looks like everything is ready in Cognito but if we look closely we see that the user is not yet activated. The account status is: FORCE_CHANGE_PASSWORD

We cannot change this in the Cognito UI so we will do this in Lambda instead.

Connecting our API Gateway to Cognito

We now head back to our API Gateway and select Authorizers. Here we Create New Authorizer.

We select the type to be Cognito and select our Cognito User Pool that we have created earlier. You can name your token source whatever you like but for following standards, we name it Authorization.

Securing an API method with Cognito

Let’s start securing our methods with Cognito authorization. I will select the GET method inside the hello resource that we have created earlier. We have set up API Keys before for this method so I will remove the API Key required option and select Cognito for our Authorization.

If we check out our method we now see that Cognito is the Authorizer.

Preparing our auth function for authentication

When we added a new Lambda function to our API Gateway we have created an auth method for our gateway. We will use this for authentication. It’s a good idea to rely on the features that Amazon API Gateway already has, including request validations. The API Gateway can validate the query string, the headers, and the body. The latter we will discuss in a later post because it requires creating a model. Setting up query string parameters is much more simple.

Let’s supply username and password as URL Query String Parameters and mark them Required. Under the Request Validator select Validate query string parameters and headers.

The AWS API Gateway will now check for these parameters and if they don’t exist the gateway will throw an error to the user.

Don’t forget to Deploy the API.

Setting up the necessary permission for Lambda

Our Lambda function needs to access our Cognito user pool. Yes, you guessed right we are going to IAM.

There is no default policy for the permissions we would like to issue so we will create a new policy for it. We need AdminInitiateAuth and AdminSetUserPassword permissions for our Lambda function to manage our Cognito user pool.

Under Policies we “Create policy” and at services, we select Cognito User Pools. Under Action we select the two permissions and under Resources we add the ARN of the Cognito User Pool.

We then create this policy and attach it to our simple-api-Role as we learned in the previous post.

Confirming the user

Let’s go back to Lambda and get rid of that pesky “FORCE_CHANGE_PASSWORD” status. For this, we will write a simple Lambda function that will change the password of our user.

This is the code I used to verify the user:

const params = {
    Password: 'password',
    UserPoolId: 'Pool Id',
    Username: 'username',
    Permanent: true
};
    
await cognito.adminSetUserPassword(params).promise();

Run the code and if we set up everything correctly Cognito will show that the account status is now CONFIRMED.

Final touches

We are almost finished! We just have to write a small code that will call Cognito for authorization. Luckily we already have a sample Lambda function that we can modify: simple-api-auth

Replace the code we had earlier with this sample code:

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

exports.handler = async (event) => {
    const params = {
        AuthFlow: 'ADMIN_NO_SRP_AUTH',
        ClientId: 'App client id',
        UserPoolId: 'Pool Id',
        AuthParameters: {
            USERNAME: event.queryStringParameters.username,
            PASSWORD: event.queryStringParameters.password
        }
    };
    
    var authResponse = await cognito.adminInitiateAuth(params).promise();
    
    const response = {
        statusCode: 200,
        body: JSON.stringify(authResponse),
    };
    return response;
};

Deploy and we are done!

Testing our API Gateway authentication

Let’s go to Postman and see if everything is working as expected.

If we call our /hello method we will receive the following error:

“message”: “Unauthorized”

Great! We need an IdToken to access this method. Let’s call our auth method to get the token. API Gateway will check if we have the username and password params. If not, we will receive an error.

We received our token. Now if we go back to our /hello method and set the Authorization header we will have access to our function. Be sure to use the IdToken for Authorization.

And voila! Our API Gateway is now using Cognito for authentication.

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