AI Analysis
Final verdict: SAFE
The package shows very low risk indicators with no network calls, shell executions, obfuscations, or credential harvesting activities observed. The metadata risk is slightly elevated due to the author's limited number of packages, but this alone does not suggest malicious intent.
- No network calls
- No shell execution patterns
- No obfuscation
- No credential harvesting
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author has only one package, which may indicate a new or less active account, but no other suspicious flags are present.
Package Quality Overall: Medium (5.4/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (2803 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
7.0
Partial type annotation coverage
Classifier: Typing :: Typed32 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
32 unique contributor(s) across 100 commits in aws/aws-cdkActive community — 5 or more distinct contributors
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository aws/aws-cdk appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Amazon Web Services" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with aws-cdk.aws-pipes-sources-alpha
Create a mini-application that leverages AWS CDK constructs to automate data processing workflows using Amazon EventBridge Pipes. Your task is to build a system where data from an S3 bucket triggers an event which then invokes a Lambda function to process the data. This Lambda function will transform the data and store it in another S3 bucket. The application should use the 'aws-cdk.aws-pipes-sources-alpha' package to define the source of the EventBridge Pipes as an S3 bucket trigger. Step-by-Step Instructions: 1. Set up your development environment with the necessary AWS SDK and CDK packages installed. 2. Define an S3 bucket as the source for the EventBridge Pipe using 'aws-cdk.aws-pipes-sources-alpha'. 3. Create a Lambda function that processes the incoming data from the S3 bucket. 4. Configure the EventBridge Pipe to invoke the Lambda function whenever there's a new object uploaded to the source S3 bucket. 5. Implement a mechanism within the Lambda function to move processed data to a different S3 bucket. 6. Ensure that all resources are properly cleaned up when the application is destroyed. Suggested Features: - Add logging to track the flow of data from S3 to the Lambda function and back to S3. - Implement error handling within the Lambda function to manage any issues that arise during data processing. - Allow configuration of the source and destination S3 buckets via environment variables or command-line arguments. - Include unit tests to verify the functionality of your CDK stack and Lambda function. This project will demonstrate the power of AWS CDK constructs in building scalable and automated data processing pipelines.
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