AI Analysis
Final verdict: SAFE
The package shows very low risk across all categories with no signs of malicious activity. The metadata risk is slightly elevated due to the author having only one package, but this alone does not indicate a supply-chain attack.
- No network calls detected
- No shell execution patterns
- No obfuscation or credential harvesting
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external API interactions.
- Shell: No shell execution patterns detected, which is expected for a standard Python package.
- 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 might indicate a new or less active account, but there are no other red flags.
Package Quality Overall: Low (3.8/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
Classifier: Typing :: Typed
✦ High
Multiple Contributors
10.0
Active multi-contributor project
6 unique contributor(s) across 100 commits in awslabs/aws-solutions-constructsActive 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 awslabs/aws-solutions-constructs 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-solutions-constructs.aws-s3-stepfunctions
Create a mini-application that integrates Amazon S3 with AWS Step Functions using the 'aws-solutions-constructs.aws-s3-stepfunctions' package. This application will allow users to upload files to an S3 bucket, trigger a Step Function workflow upon file upload, and log the status of each file processing task. Here's a step-by-step guide on how to build this application: 1. **Setup Project Environment**: Initialize your Python environment and install the necessary packages including 'aws-solutions-constructs.aws-s3-stepfunctions', 'aws-cdk-lib', and 'constructs'. 2. **Define Application Components**: Use the 'aws-solutions-constructs.aws-s3-stepfunctions' package to define the integration between S3 and Step Functions. Create an S3 bucket where files will be uploaded. 3. **Design Workflow**: Design a simple Step Function workflow that includes states for receiving the file from S3, processing it (simulated here as a delay), and logging its status. 4. **File Upload Trigger**: Set up an event trigger on the S3 bucket so that when a file is uploaded, it automatically starts the Step Function workflow. 5. **Logging and Monitoring**: Implement logging within the Step Function to track the progress and completion status of each file processing task. Optionally, integrate CloudWatch for monitoring. 6. **Testing**: Test the application by uploading files to the S3 bucket and verifying that the Step Function workflow executes correctly and logs the appropriate information. Suggested Features: - User Interface for file upload - Detailed logs and alerts for failed tasks - Support for multiple file formats - Integration with AWS Lambda for actual file processing This project aims to demonstrate the power of integrating S3 and Step Functions to automate workflows triggered by file uploads.
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