AI Analysis
Final verdict: SAFE
The package shows low risks across all assessed categories and lacks any suspicious or malicious indicators. It appears to be a legitimate tool from AWS.
- No network calls
- No shell execution
- No obfuscation
- No credential harvesting
- Low metadata risk
Per-check LLM notes
- Network: No network calls detected, which is normal for many packages that do not require real-time interactions with external services.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands which is typical and safe.
- Obfuscation: No obfuscation patterns detected, indicating normal and transparent code practices.
- Credentials: No credential harvesting patterns detected, suggesting secure handling of sensitive information.
- Metadata: The author has only one package, which might indicate a new or less active account, but no other red flags are present.
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-lambda-sqs
Create a small project called 'LambdaSQSSample' which serves as a basic yet powerful data processing pipeline using AWS Lambda and Amazon SQS. This mini-app will demonstrate how messages sent to an SQS queue can trigger a Lambda function for processing. Your task is to design and implement a system where incoming messages are placed into an SQS queue, and upon arrival, each message triggers a Lambda function to perform some predefined action (e.g., logging the message content, performing simple transformations on the data, or even invoking another service based on the message content). The project should include the following features: 1. An SQS queue that accepts messages from an external source. 2. A Lambda function that processes each message received in the SQS queue. 3. A mechanism to send test messages to the SQS queue. 4. Logging of processed messages for monitoring purposes. 5. Basic error handling to ensure failed messages are not lost and can be reprocessed. Utilize the 'aws-solutions-constructs.aws-lambda-sqs' package to streamline the integration between the Lambda function and the SQS queue. This package provides pre-built constructs that simplify the setup and management of these services, allowing you to focus more on the business logic within your Lambda function rather than the infrastructure setup. In addition to the core functionality, consider adding optional features such as: - Support for multiple Lambda functions triggered by different types of messages within the same SQS queue. - Integration with AWS CloudWatch for alerting based on certain conditions. - Enhanced logging and monitoring capabilities using AWS X-Ray or similar services. - Message deduplication and idempotency mechanisms to prevent duplicate processing.
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