AI Analysis
The package shows no signs of malicious activity such as network calls, shell execution, or credential harvesting. However, the low activity level in the repository and the maintainer's sparse history warrant caution.
- No network calls detected
- Repository has low activity and sparse maintainer history
Per-check LLM notes
- Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity without more context about the package's intended functionality.
- Shell: No shell execution patterns detected, indicating the package does not appear to be executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository's low activity and the maintainer's sparse history raise some concerns but do not conclusively indicate malicious intent.
Package Quality Overall: Medium (5.8/10)
Test suite present — 21 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml21 test file(s) detected (e.g. conftest.py)
Some documentation present
Detailed PyPI description (13280 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
365 type-annotated function signatures detected in source
Active multi-contributor project
4 unique contributor(s) across 100 commits in PhishStick-hub/aws-expectSmall but multi-author team (3–4 contributors)
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: outlook.com>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based monitoring tool called 'AWS Watcher' using the 'aws-expect' package. This tool will allow users to monitor the status of various AWS resources such as S3 buckets, DynamoDB tables, and EC2 instances. Users should be able to specify conditions under which they want to be notified about these resources, such as when a file appears in an S3 bucket, a new item is added to a DynamoDB table, or an EC2 instance changes its state. The application should include the following features: 1. User-friendly command-line interface for setting up monitoring conditions. 2. Ability to specify multiple resources and conditions per resource. 3. Notifications via email or SMS when specified conditions are met. 4. A configuration file for storing user preferences and settings. 5. Support for logging activities and errors. To utilize the 'aws-expect' package, you will need to: - Define expected states or conditions for each monitored resource using the declarative syntax provided by 'aws-expect'. - Implement logic within your application to periodically check these expected states against the actual states of the AWS resources. - Use the package's wait functionality to pause execution until the expected conditions are met, before proceeding with any notifications or actions. - Ensure that your application handles potential errors gracefully, providing informative error messages and retry mechanisms where appropriate.
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