AI Analysis
Final verdict: SAFE
The package has minimal risks associated with network, shell, and obfuscation activities. The primary concern is the metadata risk due to its recent creation and limited maintainer history.
- Low network and shell execution risks
- No signs of code obfuscation or credential harvesting
- Metadata risk due to newness and limited maintainer history
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package is new with limited maintainer history and low repository activity, indicating potential risk.
Package Quality Overall: Low (4.6/10)
○ 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 (1359 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
19 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
7 unique contributor(s) across 60 commits in k0te1ch/aiogram_testsActive 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
Email domain looks legitimate: gmail.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "k0te1ch" 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 aiogram-testing
Create a Telegram bot using Python that helps users manage their daily tasks. This bot should allow users to add tasks, mark them as completed, view their task list, and delete tasks. Additionally, implement a feature where the bot sends reminders for upcoming tasks based on the user's preferences. To ensure your bot works as intended, utilize the 'aiogram-testing' package to write comprehensive tests. These tests should cover adding, completing, viewing, and deleting tasks, as well as handling different types of user inputs and edge cases. Steps to complete the project: 1. Set up a new Python project and install necessary packages including 'aiogram' and 'aiogram-testing'. 2. Create a Telegram bot through BotFather and obtain your bot token. 3. Design and implement the main functionalities of the bot (adding, completing, viewing, and deleting tasks). 4. Add a reminder system that allows users to set reminders for their tasks. 5. Write unit tests for each functionality using 'aiogram-testing'. Ensure you test various scenarios such as adding tasks, completing tasks, viewing lists, and handling incorrect commands. 6. Deploy your bot so it's accessible via Telegram. 7. Document your code and testing process thoroughly. Features: - Add tasks with descriptions and due dates. - Mark tasks as completed. - View a list of all tasks. - Delete specific tasks. - Set reminders for tasks based on due dates. - Handle errors gracefully, such as when a user tries to complete a non-existent task or deletes a task that doesn't belong to them. Utilize 'aiogram-testing' to simulate user interactions with the bot, allowing you to verify that your bot behaves correctly under different conditions. For example, use 'aiogram-testing' to send mock messages to the bot and check if the bot responds as expected.