🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with low risks across all categories. It uses standard practices for network requests and data encoding without any clear indicators of malicious behavior.

No shell execution detected
No suspicious credential handling
Maintainer has only one package

Per-check LLM notes

Network: The use of a requests session with custom adapters is common for handling network requests efficiently and does not inherently suggest malicious intent.
Shell: No shell execution patterns were detected.
Obfuscation: Base64 decoding is commonly used for data encoding and may not indicate malicious intent without additional context.
Credentials: No suspicious patterns related to credential harvesting were detected.
Metadata: The maintainer has only one package, which could indicate a new or less active user, but no other red flags are present.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

tries=retry) session = requests.Session() session.mount("http://", adapter) session.mount(

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

64: file_bytes = base64.b64decode(screenshot_base64) with open(caminho_validacao,

✓ 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 2.0

1 maintainer concern(s) found

Author "Tainan Ramos" 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 Cronify-Orchestrator

Create a fully-functional mini-application called 'SchedulerPro' using the Python package 'Cronify-Orchestrator'. This application will serve as a personal task scheduler that allows users to manage their daily tasks more efficiently by setting up recurring tasks based on a cron-like schedule.

Step-by-step requirements:
1. Users should be able to add new tasks with specific details such as task name, description, start time, frequency (using cron syntax), and any associated parameters.
2. Implement a feature where users can view all scheduled tasks, including their current status (e.g., pending, running, completed).
3. Add functionality to modify or delete existing tasks.
4. Ensure the application can handle exceptions gracefully and log errors effectively.
5. Include a notification system that alerts users when a task is about to start or has been completed.
6. Integrate a simple UI using a web framework like Flask to make the application user-friendly.
7. Use Cronify-Orchestrator to manage the scheduling of these tasks according to the specified cron expressions.
8. Make sure the application persists data across sessions, possibly using SQLite for simplicity.

Suggested Features:
- A reminder feature that sends notifications before a task starts.
- An option to set priority levels for different tasks.
- Historical logs of completed tasks for future reference.
- Support for different types of notifications (email, SMS, etc.).
- A feature to import/export task schedules from/to CSV files.

How to Utilize Cronify-Orchestrator:
- Import the Cronify-Orchestrator library in your Python application.
- Define tasks with their respective cron expressions.
- Use Cronify-Orchestrator to schedule these tasks at the specified intervals.
- Handle the execution of each task by defining appropriate handlers within your application.
- Ensure that Cronify-Orchestrator is integrated seamlessly with the rest of the application logic to manage task execution efficiently.