Predictable S3 Buckets: A Security Risk in AWS CDK
A Hidden Danger in Open-Source Cloud Infrastructure
Amazon’s popular Cloud Development Kit (CDK) has been found to create predictable S3 bucket names by default, posing a significant security risk. These easily guessable names can be exploited by attackers to gain unauthorized access to AWS accounts.
Researchers from Aqua discovered that the vulnerability affects approximately 1% of CDK users. The issue arises during the bootstrapping process, where AWS creates a staging bucket with a predictable naming pattern: `cdk-{qualifier}-assets-{account-ID}-{Region}`. By leveraging this pattern and the account ID, attackers can easily target and compromise these buckets.
The Dangers of Predictable Bucket Names
Account Takeover: Attackers can gain administrative access to AWS accounts by compromising these staging buckets.
Malicious Code Execution: Once access is gained, attackers can execute malicious code within the target account, potentially leading to data breaches or other security incidents.
Tampered CloudFormation Templates: The staging buckets contain CloudFormation templates, which can be modified to inject malicious resources into the victim’s account during deployment.
Mitigating the Risk
To protect your AWS accounts from this vulnerability, it’s essential to take the following steps:
Avoid Predictable Bucket Names: Use custom and unpredictable names for your S3 buckets.
Keep Account ID Secret: Treat your AWS account ID as sensitive information and avoid exposing it publicly.
Update CDK: Ensure you are using the latest version of CDK, as it may include security patches to address this issue.
Implement Strong Access Controls: Use IAM roles and policies to restrict access to your AWS resources.
By following these best practices, you can significantly reduce the risk of your AWS accounts being compromised due to predictable S3 bucket names.
References: Undercode Ai & Community, Wikipedia, Darkreading.com, Internet Archive,es: Networking Ninjas
Image Source: Undercode AI DI v2, OpenAI