Hello fellow hackers and enthusiasts! 🚀 I hope you’re as excited as I am to dive deep into the world of serverless security. As our digital infrastructure evolves at a breakneck pace, so does the environment for hackers - both white and black hat. In the vast sea of cloud deployments, serverless is emerging as an alluring island. But like any treasure island, it comes with its own set of challenges.

Today, we’re going to explore the landscape of serverless security, pulling from real-world examples, and of course, spiced up with some delicious code snippets! 🤖 Let’s embark on this exhilarating voyage!

The New Frontier - What is Serverless?

Before diving into the technical details, let’s set the stage. Serverless computing allows developers to write and deploy code without worrying about the underlying infrastructure. Systems like AWS Lambda, Azure Functions, and Google Cloud Functions are revolutionizing how we think about application back-ends.

Why Should Hackers Care?

Serverless might sound all neat and tidy, but it’s like a fresh garden with its own set of pests. Each new architecture introduces new vectors for attack. For red teamers and pen testers, understanding these vectors is crucial.

Best Practices in Serverless Security

Function-Level Permissions

In serverless, you deploy tiny bits of your application, often as individual functions. So, instead of giving blanket permissions, granular, function-level permissions make a lot of sense.

For instance, let’s consider AWS Lambda. Instead of providing an execution role with full access, you’d want to restrict access.

{
    "Version": "2012-10-17",
    "Statement": [{ "Effect": "Allow", "Action": "dynamodb:GetItem", "Resource": "YOUR_DYNAMODB_TABLE_ARN" }],
}

In the above IAM policy for Lambda, the function can only access GetItem for a specific DynamoDB table. Granular, right?

Monitor and Log ALL The Things!

One cannot stress this enough. Monitoring provides insights not just into application performance but also into potential malicious activity. Platforms like AWS CloudWatch or Azure Monitor can provide invaluable information about how your serverless functions are operating.

For instance, an unexpected spike in Lambda executions could indicate someone trying to exploit your function.

Secure Your Serverless API Endpoints

Many serverless applications expose their functions via APIs, typically managed by AWS API Gateway, Azure API Management, etc. This becomes a crucial attack vector.

  • Ensure HTTPS: Always use HTTPS endpoints, even internally.
// Bad
http://myserverlessfunction.xyz/api/data

// Good
https://myserverlessfunction.xyz/api/data
  • Rate Limiting: Implement rate limits to protect your serverless endpoints.

Keep Third-Party Libraries Updated

Remember the Equifax breach? An old and vulnerable version of Apache Struts was to blame. Serverless functions often include third-party libraries. Ensure they are updated regularly.

You can use tools like OWASP Dependency-Check to scan your functions for known vulnerabilities:

dependency-check --scan /path/to/project

Input Validation

You’ve heard this a million times. “Always validate your inputs!” But, with serverless, the risk is compounded. Malformed inputs can cause your functions to behave unpredictably.

Consider this simple AWS Lambda function:

def lambda_handler(event, context):
    user_name = event['userName']
    return 'Hello, ' + user_name

If an attacker sends a payload that doesn’t contain the ‘userName’ key, this function would crash. Worse yet, if they can manipulate inputs, they might trigger unintended behavior.

Beware of Function Event Data

Serverless functions are event-driven. AWS Lambda functions, for instance, can be triggered by AWS S3 bucket changes, DynamoDB streams, and many other event sources. Be wary of the event data and how your function processes it.

Consider a Lambda function triggered by an S3 upload:

import boto3

def lambda_handler(event, context):
    s3_client = boto3.client('s3')

    # Extracting bucket and filename from the event
    bucket = event['Records'][0]['s3']['bucket']['name']
    file_key = event['Records'][0]['s3']['object']['key']

    response = s3_client.get_object(Bucket=bucket, Key=file_key)

    # Process the S3 file...

If an attacker can manipulate the file_key, they might be able to make your function read a malicious file.

Don’t Overlook the Basics

Even though serverless abstracts a lot of infrastructure, it doesn’t mean we can forget the basics. Regular patching, maintaining a strong password policy, rotating secrets, and using multi-factor authentication are just as essential.

Real-world Example - Capital One Breach

Remember the Capital One breach in 2019? Among the causes was a misconfigured AWS Web Application Firewall (WAF) for a web application, enabling certain commands to run, which in turn allowed data extraction from their AWS environment. This kind of misconfiguration, combined with serverless environments, can be a recipe for disaster.

Conclusion

Serverless is promising and offers a lot of advantages, but like any other technology, it comes with its unique set of challenges from a security perspective. For us, as hackers, pen-testers, or red teamers, staying ahead means constantly updating our knowledge and toolset.

So, until our next hacking adventure, keep your tools sharp, and your code even sharper! 🛡️🔐

Happy Hacking!