Exercise 4: Serverless Function Vulnerability (AWS Lambda)

Objective:

Understand potential vulnerabilities in serverless functions, such as insecure deserialization or misconfigured permissions. Learn how attackers can exploit these vulnerabilities and implement best practices to secure serverless applications.

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Scenario:

You are tasked with assessing the security of a serverless application deployed using AWS Lambda. During your review, you identify vulnerabilities, such as insecure deserialization and excessive permissions in the function’s IAM role. Your goal is to simulate an attack, demonstrate the impact of these vulnerabilities, and provide mitigation strategies.

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Lab Setup:

Prerequisites:

1. AWS account (free-tier is sufficient).
2. Basic knowledge of AWS Lambda and Python.
3. Installed tools:
   • aws-cli (Installation Guide)
   • Python 3.x
   • Burp Suite Community Edition (Download Burp Suite)

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Steps to Set Up the Lab:

1. Create an AWS Lambda Function:
   • Log in to the AWS Management Console.
   • Navigate to Lambda > Create function.
   • Choose Author from scratch and provide:
     • Function name: vulnerable-lambda.
     • Runtime: Python 3.x.
   • Attach an IAM role with excessive permissions (e.g., AWSLambdaFullAccess).
2. Deploy a Vulnerable Lambda Function:
   • In the Function code editor, paste the following vulnerable function:pythonCopyEditimport json import pickle def lambda_handler(event, context): try: # Simulating insecure deserialization vulnerability payload = event['payload'] deserialized_data = pickle.loads(bytes(payload, 'utf-8')) return { 'statusCode': 200, 'body': json.dumps({ 'message': 'Function executed successfully', 'data': deserialized_data }) } except Exception as e: return { 'statusCode': 500, 'body': json.dumps({ 'message': 'An error occurred', 'error': str(e) }) }
   • Deploy the function by clicking Deploy.
3. Test the Function:
   • Use the Test tab in AWS Lambda to invoke the function:
     • Test payload:jsonCopyEdit{ "payload": "gASVBgAAAAAAAAB9lCiMBGRhdGWUjAR0ZXN0lGV1Lg==" }
     • This payload is a serialized Python object representing {"data": "test"}.
4. Allow Public Invocation:
   • Create an API Gateway trigger for the Lambda function.
   • Deploy the API to make the function accessible over the internet.

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Exercise: Exploiting the Vulnerability

Objective:

Exploit the insecure deserialization vulnerability and abuse excessive permissions in the Lambda function’s role.

1. Exploit Insecure Deserialization:
   • Craft a malicious payload that executes arbitrary code upon deserialization.
   • Example payload (malicious command execution):pythonCopyEditimport pickle malicious_payload = pickle.dumps(eval("lambda x: __import__('os').system('whoami')")) print(malicious_payload)
   • Use a tool like Burp Suite to send the payload to the Lambda function via the API Gateway endpoint.
2. Abuse Excessive Permissions:
   • Use the function’s IAM role to access other AWS resources.
   • Modify the Lambda function to list all S3 buckets:pythonCopyEditimport boto3 def lambda_handler(event, context): s3 = boto3.client('s3') buckets = s3.list_buckets() return { 'statusCode': 200, 'body': json.dumps(buckets) }

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Tools Required:

1. AWS Lambda: For deploying the vulnerable function.
2. Burp Suite: For crafting and sending malicious requests.
3. aws-cli: For testing permissions and invoking the function programmatically.
4. Python: For creating serialized payloads.

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Deliverables:

1. Exploit Report:
   • Evidence of executing arbitrary code using deserialization (e.g., output of the whoami command).
   • Evidence of abusing excessive permissions (e.g., listing S3 buckets).
2. Mitigation Strategies:
   • Detailed recommendations for securing serverless applications.

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Solution:

1. Identified Vulnerabilities:
   • Insecure Deserialization: Arbitrary code execution via untrusted input.
   • Excessive Permissions: The Lambda function’s role has more privileges than necessary.
2. Consequences:
   • Code Execution: Attackers can run commands or scripts on the Lambda environment.
   • Data Breach: Access to other AWS resources can lead to sensitive data leaks.
   • Service Disruption: Attackers can modify or delete resources.
3. Prevention Techniques:
   • Input Validation: Validate all inputs and reject untrusted or malformed data.
   • Use JSON Instead of Pickle: Avoid insecure deserialization formats like pickle.
   • Least Privilege Principle: Assign minimal permissions to the Lambda function’s IAM role.
   • Monitor Activity: Use AWS CloudTrail to monitor Lambda function invocations and detect anomalies.
   • Enable VPC for Lambda: Isolate Lambda functions by deploying them within a Virtual Private Cloud (VPC).

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Conclusion:

This exercise demonstrates how vulnerabilities in serverless functions, such as insecure deserialization and misconfigured IAM roles, can be exploited by attackers. By validating inputs, minimizing permissions, and implementing proper monitoring, organizations can secure their serverless environments against similar attacks.