Exercise 12: Misconfigured Cloud Function Triggers

Objective:

Understand how cloud functions, such as AWS Lambda, can be misconfigured when triggered by public events (e.g., HTTP endpoints). Learn how attackers can exploit these vulnerabilities and implement best practices to secure cloud function triggers.

Scenario:

An AWS Lambda function is configured with a public HTTP trigger, allowing anyone to invoke it. The function processes inputs without proper validation, creating an opportunity for attackers to send malicious payloads and trigger unintended behavior. Your goal is to exploit this misconfiguration and recommend strategies to secure such triggers.

Lab Setup:

Prerequisites:

1. AWS account (free-tier works for this lab).
2. Installed tools:
   • Postman (Download Postman).
   • aws-cli (Installation Guide).

Steps to Set Up the Lab:

Deploy an AWS Lambda Function:

Log in to the AWS Management Console and navigate to Lambda > Create Function.

Choose Author from scratch and configure:

Function name: misconfigured-trigger-lambda.

Runtime: Python 3.x.

Add the following vulnerable function code:

import json

def lambda_handler(event, context):
    # Log the event (potentially sensitive data)
    print(f"Received event: {event}")
    
    # Simulate unintended behavior
    if "malicious_input" in event.get("queryStringParameters", {}):
        return {
            'statusCode': 500,
            'body': json.dumps('Malicious input triggered unintended behavior!')
        }
    
    return {
        'statusCode': 200,
        'body': json.dumps('Function executed successfully')
    }

Deploy the function.

Set Up a Public HTTP Trigger:

Create an API Gateway trigger for the Lambda function:

Navigate to API Gateway > Create API > HTTP API.

Integrate the API with the Lambda function.

Deploy the API to get a public Invoke URL (e.g., https://<api-id>.execute-api.<region>.amazonaws.com).

Verify the Public Endpoint:

Test the endpoint using a web browser or Postman:

Send a GET request to the URL:

https://<api-id>.execute-api.<region>.amazonaws.com/

Verify that the Lambda function responds successfully.

Exercise: Exploiting Misconfigured Triggers

Objective:

Simulate an attacker exploiting the public trigger by sending malicious input to the Lambda function.

Send Malicious Input:

Use Postman to send a request with a malicious query parameter:

Method: GET

URL:

https://<api-id>.execute-api.<region>.amazonaws.com/?malicious_input=1

Observe the response indicating that the malicious input triggered unintended behavior.

Enumerate Potential Inputs:

Test additional query parameters to simulate reconnaissance:

https://<api-id>.execute-api.<region>.amazonaws.com/?test_input=123

Check the Lambda function logs in CloudWatch to see if sensitive information is exposed.

Simulate Overloading the Function:

Use a script or tool (e.g., Postman Runner) to send multiple concurrent requests to the endpoint, simulating a Denial of Service (DoS) attack.

Access Sensitive Resources:

If the Lambda function interacts with other AWS resources (e.g., S3 or DynamoDB), observe if the attacker can indirectly access or manipulate those resources by sending crafted inputs.

Tools Required:

1. AWS Lambda: For deploying the cloud function.
2. API Gateway: For setting up the public HTTP trigger.
3. Postman: For sending requests and testing inputs.
4. aws-cli: For monitoring logs and invoking the Lambda function programmatically.

Deliverables:

1. Exploit Report:
   • Evidence of exploiting the public trigger using malicious inputs.
   • Screenshots or logs showing unintended behavior or sensitive data exposure.
   • Examples of overloading the function with multiple requests.
2. Recommendations for Securing Cloud Function Triggers:
   • Detailed steps to implement authentication and input validation.

Solution:

1. Identified Vulnerabilities:
   • Public Trigger: Anyone can invoke the function without authentication.
   • Lack of Input Validation: The function processes inputs without sanitization or validation.
   • Log Exposure: Sensitive information, such as event data, is logged to CloudWatch.
2. Consequences:
   • Unauthorized Access: Attackers can invoke the function and manipulate inputs.
   • Data Breach: Logs may expose sensitive information, such as API keys or user data.
   • Service Disruption: Overloading the public endpoint can result in a DoS attack.
3. Prevention Techniques:
   • Enforce Authentication:
     • Use API Gateway Authorizers to validate requests (e.g., AWS IAM, Cognito User Pools, or Lambda Authorizers).
   • Validate Inputs:
     • Add input validation logic in the Lambda function to reject malicious or malformed requests.
   • Restrict Public Access:
     • Use resource policies in API Gateway to restrict access to specific IP ranges or accounts.
   • Monitor and Throttle Requests:
     • Enable API Gateway throttling to limit the number of requests per client.
     • Use AWS WAF to block malicious traffic.
   • Secure Logging:
     • Avoid logging sensitive data, such as query parameters or payloads, in plaintext.

Conclusion:

This exercise demonstrates how misconfigured cloud function triggers can expose vulnerabilities and lead to unauthorized access or service disruption. By enforcing authentication, validating inputs, and restricting access, organizations can secure cloud functions against similar attacks.