ansel-cli

v0.3.1 suspicious
5.0
Medium Risk

don't leave crumbs in the woods

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to its use of GitHub CLI commands and potential for unauthorized access, despite having low risks in credential handling and obfuscation.

  • High shell risk due to GitHub CLI command usage
  • Suspicious metadata indicating a single package from an unassociated GitHub repository
Per-check LLM notes
  • Network: The network calls appear to be making HTTP requests with custom headers, possibly for authentication or API interaction.
  • Shell: The shell execution patterns indicate the package uses GitHub CLI commands for authentication and repository operations, which could imply it's designed to interact with GitHub but poses a higher risk due to potential unauthorized access.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package and no associated GitHub repository, which raises some suspicion.

📦 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 (4280 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

  • 90 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 3.0

Found 2 network call pattern(s)

  • ry: req = urllib.request.Request( url, headers={"User-Agent":
  • ) with urllib.request.urlopen(req) as response: data = jso
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • out = False auth_status = subprocess.run(["gh", "auth", "status"], capture_output=True) if auth_s
  • needs_logout = True subprocess.run(["gh", "auth", "login", "--web"], check=True) try:
  • ) try: api_res = subprocess.run( [ "gh", "repo",
  • if needs_logout: subprocess.run(["gh", "auth", "logout", "--hostname", "github.com"]) from
  • th: # Install subprocess.run( ["pre-commit", "install"], cwd=str(
  • ) # Run subprocess.run( ["pre-commit", "run", "--all-files"],
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com

✓ 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 "brokenpip3" 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 ansel-cli 
Create a Python-based utility named 'TrailBlazer' that leverages the 'ansel-cli' package to help hikers manage their trails and waypoints efficiently. This utility will serve as a command-line tool that allows users to store, retrieve, and manage trail information such as waypoints, elevation data, and photos taken during hikes.

### Core Features:
1. **Waypoint Management**: Users should be able to add new waypoints to their trail, including latitude and longitude coordinates. These waypoints should also support additional metadata such as names, descriptions, and timestamps.
2. **Elevation Data Retrieval**: Using 'ansel-cli', TrailBlazer should fetch elevation data for each waypoint. This data will be displayed alongside the waypoint details.
3. **Photo Integration**: Allow users to associate photos taken at specific waypoints. Photos should be uploaded to a cloud storage service (like AWS S3), and the URLs of these photos should be stored in the database.
4. **Trail Visualization**: Implement a feature that visualizes the entire trail on a map using the waypoints. This map can be generated as an image file or displayed directly within the CLI using ASCII art or a simple graphical interface.
5. **Backup and Restore**: Enable users to back up their trail data to a local file or cloud storage, and restore it when needed.

### Utilization of 'ansel-cli':
- Use 'ansel-cli' to integrate with an API that provides elevation data based on geographic coordinates. This integration is crucial for fetching accurate elevation information for each waypoint.
- Explore additional functionalities provided by 'ansel-cli' that might enhance the user experience, such as integrating with other location-based services or enhancing the way data is fetched and processed.

### Step-by-Step Guide:
1. **Setup Environment**: Install necessary packages including 'ansel-cli', 'requests', and any required libraries for photo upload and map generation.
2. **Database Design**: Design a database schema to store trail information, waypoints, elevation data, and associated photos.
3. **CLI Development**: Develop the CLI using Python's argparse module to handle commands like adding waypoints, fetching elevation data, uploading photos, and visualizing trails.
4. **Integration Testing**: Test the integration with 'ansel-cli' to ensure that elevation data is correctly fetched and integrated into the application.
5. **User Interface Enhancements**: Consider adding color coding or ASCII maps to improve the CLI's user interface.
6. **Backup and Restore Mechanism**: Implement functionality to back up trail data to a local file or cloud storage, and restore it from there.
7. **Documentation**: Provide comprehensive documentation on how to use the CLI, including examples and best practices.

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