amfs-adapter-postgres

v0.1.5 suspicious
4.0
Medium Risk

AMFS Postgres adapter with back-propagation triggers

πŸ€– AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risk in terms of network calls, shell execution, and obfuscation. However, the metadata quality is poor and there's low maintainer activity, which raises concerns about potential supply-chain risks.

  • Low maintainer activity
  • Poor metadata quality
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
  • Metadata: The package shows low maintainer activity and poor metadata quality, raising suspicion but not conclusive evidence of malice.

πŸ“¦ Package Quality Overall: Low (2.0/10)

β—‹ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
β—‹ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
β—‹ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β—ˆ Medium Type Annotations 5.0

Partial type annotation coverage

  • 91 type-annotated function signatures detected in source
β—‹ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked β€” contributor count unavailable

πŸ”¬ Heuristic Checks

βœ“ Outbound Network Calls

No suspicious network call patterns found

βœ“ Code Obfuscation

No obfuscation patterns detected

βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

βœ“ Typosquatting

No typosquatting candidates detected

βœ“ Registered Email Domain

No author email provided

βœ“ Suspicious Page Links

All external links appear legitimate

βœ“ 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)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with amfs-adapter-postgres
Create a mini-application called 'DataWatcher' that monitors changes in a PostgreSQL database and logs these changes into another table within the same database using the 'amfs-adapter-postgres' package. This tool will help users keep track of modifications made to their data over time, such as insertions, deletions, and updates. Here’s a detailed breakdown of the requirements and features:

1. **Database Setup**: Set up a PostgreSQL database with at least two tables - one for the primary data and another for logging changes.
2. **Integration with 'amfs-adapter-postgres'**: Utilize the 'amfs-adapter-postgres' package to set up triggers that automatically log changes to the primary data table into the change log table whenever there is an insert, update, or delete operation.
3. **User Interface**: Develop a simple command-line interface (CLI) where users can interact with the application to view the current state of the primary data table, see recent changes logged in the change log table, and perform basic CRUD operations on the primary data table.
4. **Security Measures**: Implement basic security measures like user authentication before allowing any CRUD operations on the primary data table through the CLI.
5. **Real-time Monitoring**: Ensure that the application can monitor the database in real-time and immediately log any changes into the change log table without requiring manual intervention.
6. **Reporting Feature**: Include a feature that allows users to generate reports based on the change logs, such as identifying frequent data modifications or tracking changes over a specific period.
7. **Documentation**: Provide comprehensive documentation detailing how to install and use the 'DataWatcher' application, including setup instructions for the PostgreSQL database and the 'amfs-adapter-postgres' package.
8. **Testing**: Write unit tests to ensure that all functionalities work as expected and that the integration with 'amfs-adapter-postgres' is seamless.

πŸ’¬ Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!