Greetings, fellow hackers! In our previous article, “Cloud Security - Best Practices and Common Vulnerabilities,” we delved into the vast world of cloud security, discussing the best practices and common pitfalls. Today, we’re going to dive deeper into advanced cloud security, specifically focusing on serverless security and misconfiguration. Our aim is to provide you with valuable insights and tools to help you harden your serverless environment and detect misconfigurations. So, strap in and get ready for an exciting ride!
Introduction to Serverless Security
Serverless computing is a relatively new paradigm that has been gaining traction in recent years. Instead of spinning up and managing server instances, serverless allows developers to build and deploy applications on a pay-as-you-go basis, freeing them from the need to manage and scale infrastructure. While serverless architectures offer many advantages, they also bring unique security challenges that demand new strategies and techniques for protection.
In serverless environments, the cloud provider takes care of most of the infrastructure security, but the responsibility for securing application code and configurations still falls on the developers and operators. This is where we, as red teamers and pen testers, come into play.
Securing Serverless Applications
When securing serverless applications, several aspects need to be considered. In this section, we will cover three critical areas: authentication and authorization, vulnerability management, and serverless monitoring and logging.
Authentication and Authorization
In serverless architectures, ensuring proper authentication and authorization is crucial. One of the most effective ways to do this is by leveraging Identity and Access Management (IAM) services, like AWS IAM, Azure Active Directory, or Google Cloud IAM.
To demonstrate how to secure a serverless application, let’s take a look at an example using AWS Lambda functions and API Gateway.
First, ensure that your Lambda function has the correct execution role. This role should have the minimum necessary permissions to execute the function without allowing any unnecessary access.
Here’s an example of a Lambda execution role with minimal permissions:
Resources:
MyLambdaFunctionRole:
Type: AWS::IAM::Role
Properties:
AssumeRolePolicyDocument:
Version: "2012-10-17"
Statement:
- Effect: Allow
Principal:
Service:
- lambda.amazonaws.com
Action: sts:AssumeRole
Policies:
- PolicyName: MyLambdaFunctionPolicy
PolicyDocument:
Version: "2012-10-17"
Statement:
- Effect: Allow
Action:
- logs:CreateLogGroup
- logs:CreateLogStream
- logs:PutLogEvents
Resource: arn:aws:logs:*:*:*
- Effect: Allow
Action:
- s3:GetObject
Resource: arn:aws:s3:::my-bucket/*
In this example, the Lambda function has permissions to read from a specific S3 bucket and write logs to CloudWatch Logs. No other permissions are granted.
Next, secure your API Gateway endpoints with proper authentication and authorization. For example, you can use Amazon Cognito or a custom authorizer to authenticate users and validate their access.
Here’s a simple example of using Amazon Cognito:
Resources:
MyApiGateway:
Type: AWS::Serverless::Api
Properties:
Auth:
DefaultAuthorizer: MyCognitoAuthorizer
Authorizers:
MyCognitoAuthorizer:
UserPoolArn: !GetAtt MyCognitoUserPool.Arn
StageName: prod
MyCognitoUserPool:
Type: AWS::Cognito::UserPool
Properties:
UserPoolName: MyUserPool
In this example, the API Gateway is configured to use Amazon Cognito as the default authorizer. This means that every request to the API will be authenticated using the specified Cognito User Pool.
Vulnerability Management
Vulnerability management is essential for securing serverless applications, as it helps identify and mitigate potential security risks in your application code and dependencies. One of the critical practices in vulnerability management is to keep your application dependencies up-to-date and use tools like Snyk, Dependabot, or WhiteSource to identify and fix vulnerabilities in your dependencies.
Additionally, consider using static application security testing (SAST) and dynamic application security testing (DAST) tools to find vulnerabilities in your code. Popular SAST tools include SonarQube, Checkmarx, and Fortify, while DAST tools like OWASP ZAP, Burp Suite, and Arachni can help you test your applications in runtime.
Let’s take a look at an example using Snyk to scan a Node.js project for vulnerabilities:
First, install the Snyk CLI:
npm install -g snyk
Next, navigate to your project directory and run the following command to test your project for vulnerabilities:
snyk test
If vulnerabilities are found, you can run the following command to automatically fix them:
snyk wizard
This command will guide you through the process of updating your dependencies and creating patches, if necessary.
Serverless Monitoring and Logging
Monitoring and logging are critical in serverless environments, as they help you identify and respond to security incidents. In addition to the built-in monitoring and logging services provided by cloud providers, like AWS CloudWatch or Azure Monitor, consider using third-party tools like Dashbird, Thundra, or Datadog to gain additional insights and automate the monitoring process.
For example, let’s take a look at how to set up monitoring for a Lambda function using Dashbird:
First, create an account on Dashbird and follow the instructions to set up the required IAM permissions.
Next, configure Dashbird to monitor your Lambda function by adding the following environment variable to your function’s configuration:
Resources:
MyLambdaFunction:
Type: AWS::Serverless::Function
Properties:
Environment:
Variables:
DASHBIRD_API_KEY: YOUR_DASHBIRD_API_KEY
Replace YOUR_DASHBIRD_API_KEY with the API key provided by Dashbird.
Finally, deploy your function and start monitoring it using the Dashbird dashboard.
Serverless Misconfigurations
Misconfigurations are a common cause of security vulnerabilities in serverless environments. In this section, we will discuss three types of misconfigurations: function-level, resource-level, and infrastructure-level misconfigurations.
Function-Level Misconfigurations
Function-level misconfigurations are those that affect individual serverless functions, such as:
- Excessive permissions: Granting functions more permissions than required can lead to unintended access to sensitive resources. Ensure that your functions adhere to the principle of least privilege by only granting the necessary permissions for their intended purpose.
- Overly permissive CORS policies: Cross-Origin Resource Sharing (CORS) policies define how resources are shared between different origins. Be cautious when configuring CORS policies to avoid exposing sensitive data to unauthorized origins.
- Insecure function triggers: Ensure that your functions are triggered by secure and authenticated sources. Avoid exposing public HTTP endpoints without proper authentication and authorization.
Resource-Level Misconfigurations
Resource-level misconfigurations affect resources that are used by serverless functions, such as databases, storage services, and messaging services. Examples of resource-level misconfigurations include:
- Publicly accessible storage buckets: Ensure that your storage buckets, like Amazon S3 or Google Cloud Storage, are not publicly accessible unless explicitly intended. Use IAM policies and bucket policies to restrict access to authorized users and services only.
- Unencrypted data: Always encrypt sensitive data, both in transit and at rest. Use encryption features provided by cloud services, like AWS KMS, Azure Key Vault, or Google Cloud KMS, to encrypt data in storage services and databases.
- Insecure messaging services: Messaging services, like AWS SQS or Google Cloud Pub/Sub, should be secured using proper authentication and authorization mechanisms to prevent unauthorized access and data tampering.
Infrastructure-Level Misconfigurations
Infrastructure-level misconfigurations are related to the overall configuration of your serverless environment, including networking, IAM policies, and deployment configurations. Examples of infrastructure-level misconfigurations include:
- Unrestricted security groups or network ACLs: Ensure that security groups and network ACLs are configured to allow only necessary traffic. Be cautious when opening ports to the public internet, and always use the principle of least privilege.
- Weak IAM policies: Review and audit IAM policies regularly to ensure they adhere to the principle of least privilege. Avoid using overly permissive policies or granting excessive permissions to users and services.
- Insecure deployment pipelines: Secure your deployment pipelines by implementing proper access controls, secrets management, and code signing to ensure that only trusted and authorized code is deployed to your serverless environment.
Real-World Examples and Tools
To help you identify and prevent misconfigurations in your serverless environment, there are several tools and resources available. Some popular tools for detecting and fixing misconfigurations include:
- ScoutSuite: An open-source multi-cloud security auditing tool that can help you identify misconfigurations in AWS, Azure, Google Cloud, and Oracle Cloud environments.
- Prowler: A command-line tool for auditing AWS environments against security best practices, including the AWS CIS Benchmark and GDPR guidelines.
- Checkov: An open-source infrastructure-as-code (IaC) scanner that checks Terraform, CloudFormation, and other IaC files for security and compliance misconfigurations.
Now, let’s look at a real-world example of a serverless misconfiguration that led to a security incident. In 2018, the fitness tracking app Strava suffered a data breach caused by an exposed Amazon S3 bucket. The bucket contained sensitive data, including user data, GPS location data, and workout details. This incident highlights the importance of properly configuring access controls on storage services to prevent unauthorized access.
To mitigate such risks, you can use tools like Amazon Macie, an AWS service that uses machine learning to discover, classify, and protect sensitive data in S3 buckets. Here’s an example of how to enable Amazon Macie for an S3 bucket:
First, enable Amazon Macie in the AWS Management Console.
Next, navigate to the Amazon Macie dashboard and add your S3 bucket as a data source:
aws macie2 create-bucket-selection --bucket my-bucket --configuration '{"is_enabled": true}'
Replace my-bucket with the name of your S3 bucket.
Amazon Macie will now monitor your S3 bucket for sensitive data and notify you of any policy violations or suspicious activity.
Conclusion
Securing serverless environments requires a deep understanding of the unique security challenges and risks associated with this paradigm. By focusing on authentication and authorization, vulnerability management, monitoring and logging, and addressing serverless misconfigurations, you can significantly improve the security posture of your serverless applications.
As red teamers and pen testers, we have a crucial role to play in helping organizations identify and mitigate security risks in their serverless environments. By staying informed of the latest security best practices and leveraging the available tools and resources, we can continue to make a positive impact on the security landscape.
So, keep learning, keep hacking, and stay secure! Remember, the best way to stay ahead of the game is to continuously improve our knowledge and skills in the ever-evolving world of cybersecurity. Together, let’s make the cloud a safer place for everyone!