AI Analysis
Final verdict: SUSPICIOUS
The package has a moderate risk score due to potential lack of maintenance and poor metadata quality, although direct security risks such as network, shell execution, obfuscation, and credential handling are minimal.
- Low maintainer activity and poor metadata quality
- No direct security threats detected
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, which could indicate it's not well-maintained or trustworthy.
Package Quality Overall: Low (2.8/10)
○ 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 (6427 chars)
○ 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
354 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with awsidr
Create a Python-based mini-application named 'IncidentWatcher' that leverages the AWS Incident Detection and Response (IDR) CLI package ('awsidr') to monitor and respond to incidents in real-time within an AWS environment. This application should serve as a user-friendly interface for security teams to quickly understand and act upon alerts from AWS IDR. Here are the key functionalities and steps for building this application:
1. **Setup**: Ensure your environment is set up with Python 3.8+ and the 'awsidr' package installed.
2. **Authentication**: Implement a secure way to authenticate users with their AWS credentials using the 'boto3' library, ensuring these credentials are stored securely and not hard-coded.
3. **Real-Time Monitoring**: Utilize the 'awsidr' package to periodically check for new incidents. The application should be able to run in the background and continuously monitor for any new alerts.
4. **Notification System**: Upon detecting a new incident, the application should notify the user via email or SMS. Integrate with a service like Twilio for SMS notifications and SMTP for emails.
5. **Actionable Insights**: Provide a summary of the incident details including severity, time of occurrence, and affected resources. Use the 'awsidr' package's capabilities to gather all relevant information.
6. **Response Actions**: Allow users to take predefined actions directly through the application such as acknowledging the incident, escalating it, or initiating a response plan. These actions should be executed via the 'awsidr' package's commands.
7. **Reporting**: Generate periodic reports summarizing the incidents detected over a certain period. Reports should include trends, common issues, and recommendations for mitigation.
8. **User Interface**: Develop a simple command-line interface (CLI) for interacting with the application. Commands should allow for starting monitoring, viewing incident logs, and performing response actions.
This project aims to demonstrate the practical application of the 'awsidr' package in enhancing the incident management process within AWS environments. It will serve as a valuable tool for security professionals looking to streamline their incident detection and response workflows.
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