Securing Your AWS Lambda Functions: Top 7 Best Practices
Dive into 7 AWS Lambda Security Best Practices and discuss the importance of properly configuring Lambda functions.
AWS Lambda is a serverless computing service that allows you to run your code without provisioning or managing servers. It provides a highly scalable, event-driven architecture, capable of handling any type of application or backend service. To take advantage of this service, all you need to do is supply your code in one of the languages that AWS Lambda supports, such as Node.js, Python, Java, Go, Ruby, or .NET/C#. You can see more details here.
The running cycle of Lambda functions is straightforward: You package your code into Lambda functions, which AWS Lambda then runs only when necessary. This service scales automatically, handling anything from a few requests per day to thousands per second. Your Lambda functions can be invoked using the Lambda API, or they can be triggered by events from other AWS services.
As you can see, AWS Lambda is a flexible, powerful, and increasingly popular service. Consequently, maintaining its security is of paramount importance. While AWS’ serverless architecture already lends a high degree of security to the service by default, users still bear a significant portion of security responsibilities.
In this blog post, we will dive into 7 AWS Lambda Security Best Practices and discuss the importance of properly configuring Lambda functions. Let’s dive in!
1) Apply ‘Principle of Least Privilege’ to Your IAM Policies
The Principle of Least Privilege (PoLP) is a fundamental best practice in AWS security. It recommends that IAM roles should have just the bare minimum permissions needed to accomplish their tasks within AWS Lambda functions. By adopting this principle, you can create a more secure environment for your serverless applications.
Let’s consider an example. Assume we have a Lambda function whose responsibility is to read data from a specific S3 bucket, ‘my-special-bucket’. An overly permissive policy might look like this:
{
"Version": "2012–10–17",
"Statement": [
{
"Effect": "Allow",
"Action": "*",
"Resource": "*"
}
]
}In this bad example, the wildcard ‘*’ grants access to all AWS services and resources. Such broad permissions introduce significant security risks. If an attacker manages to exploit this function, they gain extensive access to your AWS resources.
{
"Version": "2012–10–17",
"Statement": [
{
"Effect": "Allow",
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::my-special-bucket/*"
}
]
}This improved policy only allows ‘s3:GetObject’ permission on ‘my-special-bucket’, exactly fitting the function’s requirement. In case of a security breach, the potential damage is significantly limited to data read from ‘my-special-bucket’.
Following the Principle of Least Privilege when defining your IAM policies minimizes your exposure to threats. It’s an effective and proactive approach to strengthening your AWS Lambda security.
2) Avoid Storing Sensitive Data in Lambda Function Code or Configurations
Storing sensitive data directly in Lambda function code or configurations is a serious security risk that can expose your sensitive information. A well-known real-world example that underscores the severity of this misconfiguration, though not Lambda function-based, occurred with Uber in 2016. Uber engineers stored sensitive access keys in their code, which was then accidentally uploaded to a public GitHub repository. This security oversight led to a data breach that exposed the data of 57 million Uber users and drivers.
Despite its simplicity, this approach is a potential security nightmare, making your AWS environment vulnerable to breaches. Luckily, AWS provides methods to prevent this:
Use Environment Variables: AWS Lambda allows you to use environment variables to store sensitive information securely.
- Encryption at Rest: Assign a KMS key to each Lambda function to encrypt these environment variables when not in use. You can choose AWS-managed or customer-managed keys based on your preference.
- Encryption in Transit: To ensure that these secrets are not exposed unencrypted, enable the “Encryption helpers” feature in the AWS Lambda console, CLI, or API.
Adopt AWS Secret Management Services: AWS offers dedicated services for secure storage, rotation, and access of sensitive information.
- AWS Secrets Manager: This service helps protect access to your applications, services, and IT resources without the upfront investment and on-going maintenance costs of operating your own infrastructure.
- AWS Systems Manager Parameter Store: This service provides secure, hierarchical storage for configuration data management and secrets.
By following these best practices, you can enhance the security of your AWS Lambda functions and significantly reduce the risk of exposing sensitive data.
3) Enable Comprehensive Logging and Monitoring
Maintaining a clear view of your AWS Lambda functions’ behavior is essential for identifying and responding to potential security incidents. Comprehensive logging and monitoring enable you to detect unusual activity, investigate potential threats, and maintain optimal performance.
In AWS, CloudWatch is the service you need. It collects monitoring and operational data in the form of logs, metrics, and events, providing you with a unified view of your AWS resources, applications, and services. For Lambda functions, particularly crucial metrics include:
- Concurrent Executions: This metric shows the number of function instances that are processing events concurrently at any given point in time. Unusual spikes in this metric might indicate unauthorized or unexpected usage of your functions.
- Lambda Throttling: This metric counts the number of function invocation attempts that were throttled due to exceeding concurrent execution limits. An unexpected increase in throttling events may be a sign of a Denial of Service (DoS) attack.
- AWS Lambda Error Metrics: This metric tracks the number of invocations that failed due to errors in your function. A sudden rise in error rates might signify issues in your code or an active attack on your system.
In addition to CloudWatch, consider enabling AWS X-Ray for your Lambda functions. X-Ray provides insights into the behavior of your applications, helping you understand how they are performing and where bottlenecks are occurring.
By keeping a vigilant eye on these metrics and logs, you can enhance the security posture and performance of your Lambda functions.
4) Secure Your APIs using AWS API Gateway
Securing your APIs is just as crucial as securing your AWS Lambda functions. APIs often act as the front door to your applications, meaning they need stringent security measures. AWS API Gateway provides several powerful features to enhance the security of your APIs:
Authentication and Authorization: Controlling who can access your APIs is essential to maintaining their security. API Gateway offers several mechanisms for this:
- API Keys: They are alphanumeric string values that you distribute to app developer customers to grant access to your API. They’re like a username-password pair; clients send these keys with requests, and API Gateway verifies them before allowing requests to proceed.
- IAM Policies: AWS Identity and Access Management (IAM) allows you to create policies that grant permissions to access your API Gateway resources. These policies provide fine-grained control over who can access your API Gateway. For instance, the below policy allows access only from a specific VPN IP address:
{
"Version": "2012–10–17",
"Statement": [
{
"Effect": "Allow",
"Action": "execute-api:Invoke",
"Resource": "arn:aws:execute-api:region:account-id:api-id/stage-name/*/*",
"Condition": {
"IpAddress": {
"aws:SourceIp": "vpn-ip-address"
}
}
}
]
}- AWS Cognito: It provides user and identity management, and when integrated with API Gateway, it can authenticate and authorize users. For instance, you can use Cognito User Pools where users can sign up and access AWS resources, including API Gateway.
- Lambda Authorizer: You can use a Lambda function to control access to your API methods based on a bearer token (like a JWT or an OAuth token). For instance, a Lambda authorizer function can verify an incoming token’s signature and claims, and then pass access control to API Gateway based on that. Here’s an example of a simple Lambda authorizer function in Python:
def lambda_handler(event, context):
token = event['authorizationToken']
method_arn = event['methodArn']
if token.lower() == 'allow':
return generate_policy('user', 'Allow', method_arn)
elif token.lower() == 'deny':
return generate_policy('user', 'Deny', method_arn)
else:
raise Exception('Unauthorized')
def generate_policy(principal_id, effect, resource):
policy = {
'principalId': principal_id,
'policyDocument': {
'Version': '2012–10–17',
'Statement': [
{
'Action': 'execute-api:Invoke',
'Effect': effect,
'Resource': resource
}
]
}
}
return policyIn this example, access is granted or denied based on the token provided in the request.
Protection against Layer 7 attacks: These are attacks at the application layer of the OSI model, like SQL injection and Cross-Site Scripting (XSS). There are several services:
- AWS WAF: AWS Web Application Firewall protects your API Gateway from common web exploits and unusual traffic patterns. For example, you can create a rule that blocks requests from IP addresses that are known sources of malicious traffic.
- CloudFlare: An external service that can be used for additional protection. It offers security features including DDoS protection, Web Application Firewall (WAF), and rate limiting.
By using these features in AWS API Gateway, you can ensure that only authorized users can access your APIs and that your APIs are shielded against the most common types of web attacks.
5) Leverage Reserved Concurrency for Function Scaling
Properly managing concurrency in AWS Lambda is key to maintaining the performance and security of your applications. By using the Reserved Concurrency feature, you can have fine-grained control over the scaling of your Lambda functions.
Reserved Concurrency allows you to specify the maximum number of instances that a function can use concurrently. These reserved instances are exclusively for that function and cannot be used by other functions in your account. Importantly, there is no additional cost for configuring Reserved Concurrency.
One of the main benefits of using Reserved Concurrency is to limit the potential impact of overloading your function, which could occur during events such as a Denial of Service (DoS) attack or during the processing of an unexpectedly high number of requests. By setting the maximum number of concurrent instances, you can ensure that your function won’t exhaust your account’s concurrency limit and will always have the necessary resources to run when needed.
For example, a Lambda function receives messages from an SQS queue and writes to a DynamoDB table. It has a reserved concurrency of 10 with a batch size of 10 items. The SQS queue rapidly receives 1,000 messages. The Lambda function scales up to 10 concurrent instances, each processing 10 messages from the queue. While it takes longer to process the entire queue, this results in a consistent rate of write capacity units (WCUs) consumed by the DynamoDB table.
Remember, carefully managing Reserved Concurrency can help ensure your function’s availability and can help prevent overuse or misuse that could lead to a service disruption.
6) Clean up and Delete Unused Lambda Functions
Proper management and maintenance of your AWS Lambda functions is an essential aspect of cloud security. Unused or forgotten Lambda functions can become an unintentional security liability. These unused functions may contain outdated libraries, deprecated APIs, or unpatched vulnerabilities that an attacker might exploit.
Furthermore, unused functions could have been configured with access to sensitive data or resources, making them a potential entry point for unauthorized users. Even functions that were only created for testing purposes but then forgotten can pose a risk.
Therefore, it’s highly recommended to periodically review all of your Lambda functions and delete those that are no longer in use. This will permanently remove the function and its configuration, including environment variables and IAM roles, from your AWS account, thereby eliminating the potential risk it might pose.
Remember, good housekeeping practices like these not only help to maintain security but also help to avoid unnecessary costs, as you only pay for what you use with AWS Lambda. It also keeps your environment clean, making it easier to manage and understand.
7) Ensure Secure Coding Practices for Lambda Functions
Secure coding practices are a cornerstone of cybersecurity. While AWS Lambda’s serverless architecture inherently reduces the surface area of attacks, vulnerabilities can still be introduced through insecure code.
To maintain the security of your Lambda functions, consider the following measures:
Use AWS Security Services: Services such as AWS CodeGuru and Amazon Inspector can assist in identifying common coding flaws that may lead to security vulnerabilities.
- AWS CodeGuru provides essential tools for maintaining the security of your Lambda functions. It offers a centralized interface for managing your software development process, automating crucial security checks, and seamlessly handling access control across your codebase. This helps ensure your Lambda functions are secure, robust, and reliable. You can see more details from here.
- Amazon Inspector is an automated security assessment service that helps improve the security and compliance of applications deployed on AWS. Inspector automatically assesses applications for vulnerabilities or deviations from best practices, including impact of the exposure of sensitive data or system availability.
Use Code Analysis Tools: There are several third-party tools that can analyze your code for security vulnerabilities. These tools can be integrated into your CI/CD pipeline to catch potential issues early in the development process.
- SonarQube is an open-source platform for continuous inspection of code quality. It performs automatic reviews with static code analysis to detect bugs, code smells, and security vulnerabilities.
- Snyk focuses on finding and fixing vulnerabilities in open-source libraries. It offers direct and seamless integration with AWS Lambda, providing automatic scanning for open-source vulnerabilities.
- Checkmarx is a provider of static and interactive application security testing, software composition analysis, and developer AppSec training to embed security within your code.
The above practices and tools not only help to maintain the security of your Lambda functions but also ensure compliance with best practices and standards. Always remember, the security of your application is largely determined by the security of your code.
Conclusion
In wrapping up, maintaining a secure AWS Lambda environment isn’t a one-time effort, but a continuous process. From implementing the ‘Principle of Least Privilege’ to avoiding storing sensitive data in function code, from monitoring activities via CloudWatch to practicing secure coding, every step contributes to a more secure serverless architecture. Don’t forget to routinely check for unused functions too — a tidy workspace is a safer workspace. These practices aim to not only strengthen your security but also improve operational efficiency. So, as we continue to explore the many facets of AWS in my upcoming blogs, make sure you’re applying these security best practices to your AWS Lambda functions. Stay tuned for more insights on cloud and DevSecOps strategies!
