GeoAlchemy2

v0.20.0 safe
4.0
Medium Risk

Using SQLAlchemy with Spatial Databases

🤖 AI Analysis

Final verdict: SAFE

The package GeoAlchemy2 v0.20.0 has low risks associated with network calls, shell execution, and credential harvesting. While there is some obfuscation and metadata risk due to handling of WKB format and sparse author information, these do not strongly suggest a supply-chain attack.

  • Low network and shell execution risk
  • Some obfuscation and metadata concerns
  • No evidence of supply-chain attack
Per-check LLM notes
  • Network: No network calls detected, which is normal for GeoAlchemy2 as it primarily deals with database operations without external communications.
  • Shell: No shell execution patterns detected, aligning with the package's purpose of working with spatial data in databases.
  • Obfuscation: The observed patterns are likely related to the handling of spatial data in WKB format, which is common in GeoAlchemy2 for geometry operations.
  • Credentials: No credentials or secrets harvesting patterns detected.
  • Metadata: The author's information is sparse and the website link is non-HTTPS, which may indicate a lack of transparency or maintenance effort.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • urn WKBElement( b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@" ) elif request.p
  • n_wkb = memoryview( b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00@" ) _hex_ewkb = "01010
  • : rast_data = ( b"\x01\x00\x00\x01\x00\x9a\x99\x99\x99\x99\x99\xc9?\x9a\x99\x99\x99\x99\x99" b"\xc9\xbf\x00\x00\x00\x0
  • 99\x99\x99\x99\x99" b"\xc9\xbf\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00" b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0
  • 0\x00\x00\xf0?\x00" b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xe6\x10\x00" b"\x00\x05\x00\x05\x00D\x00\x01\x01\x01\x01\x01\x0
  • b"\x00\x05\x00\x05\x00D\x00\x01\x01\x01\x01\x01\x01\x01\x01\x01\x00\x01\x01" b"\x01\x00\x00\x01\x01\x00\x00\x00\x01\x00\x00\x00
✓ 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: gmail.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.sqlalchemy.org/
✓ Git Repository History

Repository geoalchemy/geoalchemy2 appears legitimate

⚠ 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 GeoAlchemy2 
Your task is to develop a small, fully-functional application that leverages the GeoAlchemy2 package to manage and query spatial data stored in a PostgreSQL database with PostGIS extension. This application will serve as a basic tool for visualizing and managing geographic information systems (GIS) data. Here’s a step-by-step guide on what your application should achieve and how it should utilize GeoAlchemy2:

1. **Setup**: Begin by setting up a PostgreSQL database with the PostGIS extension enabled. Ensure you have the necessary environment variables set up for connecting to this database.

2. **Database Model**: Define a model using GeoAlchemy2 to represent a geographical entity such as a park or a building. Your model should include fields like `name`, `address`, and a geometry field representing the shape of the entity.

3. **CRUD Operations**: Implement Create, Read, Update, and Delete (CRUD) operations for the geographical entities. Use GeoAlchemy2’s capabilities to handle spatial queries efficiently.

4. **Spatial Queries**: Incorporate functionality to perform spatial queries. For example, allow users to find all parks within a certain distance from a given point or to retrieve all buildings that intersect with a specified polygon.

5. **Visualization**: Integrate a simple web interface or command-line interface (CLI) that allows users to visualize the spatial data. This could involve plotting points, lines, and polygons on a map.

6. **Advanced Features**: Consider adding advanced features such as calculating areas, distances between points, or even performing buffer operations around geometries.

7. **Documentation**: Provide comprehensive documentation explaining how to use the application, including setup instructions and examples of how to execute various queries.

GeoAlchemy2 will be central to this application, providing the bridge between your Python code and the spatial capabilities of the PostgreSQL database. By leveraging GeoAlchemy2, you’ll be able to seamlessly integrate spatial data handling into your application.