🤖 AI Analysis

Final verdict: SAFE

The package is generally safe with minor concerns. It has some obfuscation practices and lacks detailed metadata, but there are no indications of malicious behavior or supply-chain attacks.

Obfuscation risk due to base64 decoding
Incomplete author information and lack of GitHub repository

Per-check LLM notes

Network: The package makes network calls which seem to be part of its intended functionality, possibly for API interactions.
Shell: No shell execution patterns were detected.
Obfuscation: The use of base64 decoding with validation suggests potential obfuscation, but it could also be legitimate for data encoding purposes.
Credentials: No clear patterns indicating credential harvesting were detected.
Metadata: The package has no associated GitHub repository and the author information is incomplete, suggesting potential unreliability.

📦 Package Quality Overall: Low (3.6/10)

○ 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 (18309 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 7.0

Partial type annotation coverage

Classifier: Typing :: Typed
165 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 score 6.0

Found 4 network call pattern(s)

ects/*). self._http = httpx.AsyncClient( base_url=f"{self._base_url}/api/v1/objects",
self._datasets_http = httpx.AsyncClient( base_url=self._base_url, headers=_h
objects) self._http = httpx.Client( base_url=f"{self._base_url}/api/v1/objects",
self._datasets_http = httpx.Client( base_url=self._base_url, headers=_h

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

try: return base64.b64decode(value, validate=True) except (binascii.Error, ValueE

✓ 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: agimus.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 agimus

Create a Python-based mini-application named 'AgimusTaskScheduler' that leverages the Agimus SDK to manage task scheduling and execution. This application will serve as a user-friendly interface for users to schedule tasks on their Agimus platform accounts. Here’s a detailed breakdown of the project requirements and steps:

1. **Project Setup**: Start by setting up a virtual environment and installing the necessary packages, including the Agimus SDK.
2. **User Authentication**: Implement a simple authentication system where users can log in using their Agimus credentials. Ensure secure handling of user data.
3. **Task Management Interface**: Develop an interactive command-line interface (CLI) or a basic web UI using Flask that allows users to view, add, edit, and delete tasks scheduled through the Agimus platform.
4. **Task Scheduling**: Utilize the Agimus SDK to schedule tasks based on user input. Tasks can be scheduled once, daily, weekly, or monthly.
5. **Execution Monitoring**: Provide functionality to monitor the status of scheduled tasks, such as whether they have started, completed successfully, or encountered errors.
6. **Notifications**: Integrate a notification system that alerts users via email or SMS when tasks start, complete, or fail.
7. **Documentation**: Write comprehensive documentation for both end-users and developers, explaining how to install and use the application, as well as any API endpoints if a web UI is chosen.

**Utilizing the Agimus Package**: Throughout the development process, ensure that all interactions with the Agimus platform, such as task scheduling and monitoring, are performed through the Agimus SDK. This includes authenticating users, retrieving task information, scheduling new tasks, and receiving notifications about task statuses.

This project aims to showcase the capabilities of the Agimus SDK while providing a practical tool for managing tasks more efficiently.