🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to its use of obfuscation techniques and lack of maintainer activity, raising concerns about its legitimacy and intentions.

High obfuscation risk
Low maintainer activity

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external communication for its functionality.
Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
Obfuscation: The use of base64 decoding suggests an attempt to obfuscate code, which is suspicious without clear justification.
Credentials: No direct evidence of credential harvesting found, but further investigation into the package's functionality is recommended.
Metadata: The package shows low maintainer activity and poor metadata quality, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (7078 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

628 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 score 2.0

Found 1 obfuscation pattern(s)

ta: str) -> bytes: return base64.b64decode(data) class OTSCheckpointSaver(BaseCheckpointSaver[str]):

✓ 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 short
Author "" 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 agentrun-inner-test

Create a mini-application named 'AgentTaskManager' using the Alibaba Cloud Agent Run SDK (package name: agentrun-inner-test). This application will serve as a task management system specifically designed for managing tasks within an organization's internal processes. It will allow users to create, update, delete, and view tasks, all while leveraging the capabilities of the Agent Run SDK for enhanced functionality and integration with Alibaba Cloud services.

The application should have the following core features:
1. User Authentication: Implement a simple user authentication mechanism to ensure only authorized users can access and manage their tasks.
2. Task Management: Users should be able to create new tasks, assign them to specific categories (e.g., 'Development', 'Marketing', 'Finance'), set due dates, and mark tasks as completed.
3. Real-time Updates: Utilize the Agent Run SDK to enable real-time updates for task status changes, ensuring all users see the latest information without needing to refresh the page.
4. Notification System: Integrate the SDK to send notifications (via email or SMS) when a task reaches its due date or is updated.
5. Reporting: Generate reports on task completion rates and user activity, which can be exported in CSV format for further analysis.

Detailed Steps:
1. Set up the environment by installing necessary packages including 'agentrun-inner-test'.
2. Design the database schema to store user information and task details efficiently.
3. Implement the user authentication system, focusing on security best practices.
4. Develop the task creation, updating, deletion, and viewing functionalities, making sure to utilize the Agent Run SDK for real-time updates.
5. Add the notification system, configuring it to use the SDK for sending timely reminders.
6. Create a reporting module that leverages the SDK's capabilities for data processing and export options.
7. Test the application thoroughly, paying special attention to how well the real-time updates and notifications work.
8. Deploy the application in a secure manner, ensuring all data transmitted is encrypted.

By completing this project, you'll gain hands-on experience with the Alibaba Cloud Agent Run SDK and learn how to integrate it into a practical, real-world application.