The introduction of serverless architectures is a positive development from a security perspective. Splitting up services into single-purpose functions with well-defined inputs and outputs helps reduce exposure to many types of threats. However, the security of serverless architectures is an under-studied topic. Many practices and tools available in more traditional architectures don’t apply.
This document will discuss methods of auditing and monitoring of AWS Lambda functions—a key component of serverless architectures in AWS — and how Cisco® Secure Cloud Analytics (formerly Stealthwatch Cloud) puts these methods into practice.
● Access to the function: Who or what can modify or invoke a function?
● Access from the function: What can the function access when it is running?
● Unintended behavior: Can the function be made to do something unexpected?
For each area, there is a question of auditing, or looking to see whether configurations match expectations, and monitoring, or keeping track of activities on an ongoing basis.
The AWS Lambda documents describe how to use the AWS Identity and Access Management (IAM) API and Lambda API for auditing policies related to function access. It’s important to audit policies periodically to check:
● Whether some policies are outdated. For example, they made sense in the past, but haven’t been updated to reflect changes (for instance, a user who has since moved to another team still has rights to change an Amazon Lambda function’s code)
● Whether some policies allow access to more resources than necessary (for example, an Amazon Lambda function that can write to any Amazon Simple Storage Service - Amazon S3 bucket
The AWS IAM API can be used to show which users (or roles) in an AWS account have the ability to change a Amazon Lambda function or its configuration. For example, we could query the AWS IAM API to see who has the Update Function Code permission. This would show who is allowed to change the code a function executes. The Amazon Lambda API can be used to show who (or what) is allowed to invoke a function. It’s common to allow other AWS services like Amazon S3 or API Gateway to call a function. An example of something to look for would be cross-account access for Amazon S3. Note that the AWS documents provide this warning for this problem:
The Amazon Lambda and AWS IAM APIs together can show what an Amazon Lambda function is allowed to do. For example, to see what permissions a particular Amazon Lambda function is granted (for instance, writing to an Amazon S3 bucket), you can use the Amazon Lambda API’s GetFunction call. That will help you determine which role to look up with the AWS IAM API.
“If you add a permission for the Amazon S3 principal without providing the source ARN, any AWS account that creates a mapping to your function ARN can send events to invoke your Lambda function from Amazon S3.”
The Amazon Lambda documents describe how to use AWS CloudTrail and Amazon CloudWatch
AWS CloudTrail tracks API activities. We can use AWS CloudTrail logs to look for changes to functions (for example, the UpdateFunctionCode call described above) as well as changes made by functions. This helps keep track of access between audits.
Amazon CloudWatch Logs track function invocations and their output. This can be used for billing purposes (they include information about duration and memory usage, which are part of Amazon Lambda pricing) as well as for monitoring purposes. For example, a function can be made to write its input to the log, which could be used to help look for injection attacks.
Amazon CloudWatch Metrics also track function usage, such as the number of invocations, the duration of each run, and other metrics. Manual alarms can be set for things like excessive invocations. This can be used to monitor for unintended behavior and abuse. For example, if the function can be invoked from the outside, an alarm could show whether it is being abused and wasting resources.
The auditing and monitoring resources described in the AWS documentation help answer some of our security-related questions, but miss some others. For example, it would be difficult to use the services above to determine whether an Amazon Lambda function is accessing an internal Amazon Relational Database Service (RDS) or Amazon ElastiCache instance inside a VPC.
We can get more detailed monitoring of an Amazon Lambda function activity by understanding how functions communicate. As the AWS documentation describes, Amazon Lambda functions are allocated temporary Elastic Network Interfaces (ENIs) and IP addresses when they need to communicate with a VPC resource. These ENIs can be enumerated with the Amazon Elastic Compute Cloud (EC2) API and matched to the requesting Lambda function.
Once the ENIs and IP addresses are known, an Amazon Lambda function’s activity can tracked using VPC Flow Logs. These flow logs describe all of the communication to, from, and within a VPC, so if a Lambda function interacts with an internal resource, the associated network activity will be logged.
Furthermore, Amazon Lambda functions need to use a Network Address Translation (NAT) instance or VPC NAT gateway to gain Internet access. This means their Internet activity will also go through the VPC and be logged as flow log records.
This level of detail helps answer other security questions about Amazon Lambda. More types of unintended behavior besides function invocation and API calls can be tracked. The effects of something exotic like container escape (a breach of the environment that runs the function) could be detected if it was followed by access to VPC resources.
Secure Cloud Analytics integration
Cisco Secure Cloud Analytics uses each of the resources described above to track Amazon Lambda functions. VPC Flow Logs allow monitoring of Amazon Lambda functions with Secure Cloud Analytics’ entity modeling service, which helps to enable a wide variety of security alert types. The screenshot below (from the Secure Cloud Analytics web portal) shows a set of VPC Flow Log records for a Amazon Lambda function accessing an Amazon RDS database running MySQL.
Amazon Lambda functions are tracked by name, so as they change ENIs and IP addresses, their activity will be updated:
Amazon Lambda functions are good examples of static devices, or entities that express a very narrow set of behaviors. This makes identifying even subtle changes that may indicate a security concern possible. The screenshot below shows an alert for an Amazon Lambda function that normally connects to two internal resources connecting to an unexpected third.
The Secure Cloud Analytics service also reads from AWS CloudTrail, so if an Amazon Lambda function executes an unusual API call (due to code injection, for example), that can generate an alert.
Additionally, Secure Cloud Analytics polls CloudWatch metrics, so if the function is invoked, many more times than normal (due to abuse from the outside), that would generate an alert.
The normal level of invocations is determined automatically, so a user doesn’t need to specify what the expected invocation rate is.
In this whitepaper, we have:
● Described the standard tools for auditing and monitoring Lambda function security— the Amazon Lambda and IAM APIs, AWS CloudTrail, and Amazon CloudWatch.
● Explored details of how Amazon Lambda functions access internal resources to discover another way to monitor behavior (VPC Flow Logs).
● Explained how Secure Cloud Analytics uses these tools to help enable entity modeling-based security alerts. There are some simple steps Lambda users can take to improve their security stance with standard tools:
● Auditing: At the very least, use the AWS Console to look through the list of the Lambda function’s execution roles and triggers. Check whether any seem overly broad (for instance, allowing Full Access to some service like Amazon S3) and set a reminder to do the same again in three months.
● Monitoring: Set up some Amazon CloudWatch metrics alarms for any Amazon Lambda functions that react to outside (such as untrusted) input. This will let you know if resources are being wasted, or if there was some latent behavior in the function’s code that’s now being expressed. Set a reminder to do this for new functions.
Amazon Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources.
Monitoring Amazon Lambda functions is included in the Secure Cloud Analytics entity modeling service.
If you’re using Secure Cloud Analytics already, you can make sure that the Secure Cloud Analytics policy for your account is up-to-date since this will let it use the AWS APIs for Amazon Lambda monitoring. If you’re new to Secure Cloud Analytics, you’ll be able to check on Amazon Lambda function activity shortly after you initiate monitoring.