LAgencia-orion

v1.0.41 safe
3.0
Low Risk

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🤖 AI Analysis

Final verdict: SAFE

The package LAgencia-orion v1.0.41 is assessed as safe with no indications of obfuscation or credential harvesting. However, it has moderate risks due to potential low maintainer activity and poor metadata quality.

  • No obfuscation patterns detected
  • No credential harvesting patterns detected
  • Some signs of low maintainer activity and poor metadata quality
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows some signs of low maintainer activity and poor metadata quality, but lacks clear indicators of malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • ities)) async with httpx.AsyncClient() as client: await self.initialize(client)
  • ataFrame: async with httpx.AsyncClient() as client: await self.initialize(client)
  • l try: server = smtplib.SMTP(data.SMTP_SERVER, data.SMTP_PORT) server.starttls()
  • orreo try: with smtplib.SMTP(data.SMTP_SERVER, data.SMTP_PORT) as server: se
✓ 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

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 LAgencia-orion 
Create a fully-functional mini-app named 'OrionTravelAdvisor' using the Python package 'LAgencia-orion'. This app will serve as a travel planning assistant for users, helping them plan their trips by suggesting destinations based on user preferences and providing information about local attractions and accommodations.

### Core Features:
1. **User Input**: Users can input their preferred travel dates, budget, and interests (e.g., historical sites, beaches, museums).
2. **Destination Suggestion**: Based on the user's inputs, the app suggests one or more destinations that best match their criteria.
3. **Local Attractions**: For each suggested destination, provide a list of top attractions and activities along with brief descriptions.
4. **Accommodation Recommendations**: Recommend suitable hotels or hostels within the selected budget range.
5. **Interactive Map**: Display an interactive map showing the locations of suggested destinations, attractions, and accommodations.
6. **Itinerary Builder**: Allow users to create a personalized itinerary based on the suggestions provided, including estimated travel times and costs.
7. **Feedback Loop**: Collect feedback from users after they have visited their chosen destination to improve future recommendations.

### Utilization of 'LAgencia-orion':
- Use 'LAgencia-orion' to fetch real-time data on travel destinations, attractions, and accommodations. Specifically, leverage its ability to parse through large datasets efficiently to provide up-to-date and relevant information to users.
- Implement the package's recommendation algorithms to tailor suggestions based on user preferences and past feedback.
- Ensure that the app integrates seamlessly with 'LAgencia-orion', allowing for dynamic updates and personalized experiences for each user.

Your task is to design and implement this mini-app, ensuring it is user-friendly, efficient, and makes full use of the capabilities offered by 'LAgencia-orion'. Document your process and any challenges you encounter along the way.

💬 Discussion Feed

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