🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is suspected to have potential risks due to its interaction with external services, although there are no clear signs of malicious activities such as shell execution or credential harvesting.

network interactions suggest potential data exfiltration
low maintainer effort indicated by metadata

Per-check LLM notes

Network: The observed network calls suggest the package interacts with external services, possibly for authentication and file uploads, which could indicate legitimate functionality but also raises concerns about data exfiltration.
Shell: No shell execution patterns were detected, indicating a lower risk of direct system command injection.
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 effort and may be new or inactive, raising some suspicion but not definitive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

th/login" response = requests.post( login_url, json={ "
oad/init" init_resp = requests.post( init_url, json={"fileName": os.pat
as f: put_resp = requests.put(upload_url, data=f, headers={"Content-Type": "application/js
) response = requests.post( endpoint, headers=headers,
response = requests.post( endpoint, headers=headers,

✓ 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: example.com>

✓ 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 11automation

Create a fully-functional mini-app that leverages the '11automation' Python package to automate the uploading of dashboard reports to a specified server or cloud storage service. This application should streamline the process of generating, formatting, and delivering periodic business reports for stakeholders. Here’s a detailed breakdown of the project requirements and suggested features:

1. **Project Setup**: Start by setting up a virtual environment and installing the necessary packages including '11automation'. Ensure that you have the appropriate credentials and access permissions for the target upload destination.

2. **Dashboard Report Generation**: Develop a feature within your app that automatically generates dashboard reports based on predefined templates and data sources. These reports could include charts, tables, and summaries of key performance indicators (KPIs).

3. **Report Formatting**: Implement functionality to format these reports according to specific design guidelines, such as using consistent fonts, colors, and layout styles. This ensures that all reports maintain a professional appearance.

4. **Automated Upload Process**: Utilize the core functionalities of the '11automation' package to schedule and automate the upload of these formatted reports to a designated server or cloud storage solution like AWS S3 or Google Cloud Storage. Ensure that the upload process includes error handling and retry mechanisms for failed uploads.

5. **User Interface**: Design a simple yet intuitive user interface where users can manage their reports, view upload statuses, and configure settings such as report generation schedules and upload destinations. This UI should be accessible via a web browser.

6. **Security and Access Control**: Integrate security measures to protect sensitive data and ensure that only authorized users can access or modify report configurations. Consider implementing role-based access control (RBAC) to differentiate between different levels of user permissions.

7. **Monitoring and Alerts**: Implement monitoring capabilities to track the status of report generation and upload processes. Users should receive alerts via email or SMS in case of failures or delays.

8. **Testing and Documentation**: Thoroughly test your application to ensure reliability and performance. Document your code and provide clear instructions for installation, configuration, and usage.

By completing this project, you will have developed a powerful tool that significantly reduces manual effort and improves the efficiency of reporting processes. Remember to leverage the '11automation' package effectively to handle the automation aspects of your application.