algovoi-refund-receipt

v0.1.1 suspicious
4.0
Medium Risk

AlgoVoi refund receipt format reference implementation -- companion to algovoi-substrate compliance receipt, post-settlement counterpart pinning urn:x402:canonicalisation:jcs-rfc8785-v1

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks for common attack vectors such as network calls, shell execution, and obfuscation. However, the metadata risk due to low maintainer activity and repository engagement raises concerns about its long-term maintenance and security.

  • Low risk in common attack vectors
  • Repository lacks engagement and maintainer activity
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's lack of engagement and the maintainer's limited activity suggest potential risk.

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_refund_receipt.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.algovoi.co.uk/refund-receipt
  • Detailed PyPI description (9400 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 5 type-annotated function signatures (partial)
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 8 commits in chopmob-cloud/algovoi-refund-receipt
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 algovoi-refund-receipt 
Create a Python-based mini-application that helps businesses manage and generate standardized refund receipts according to the AlgoVoi refund receipt format. This application will utilize the 'algovoi-refund-receipt' package to ensure compliance with the specified canonicalization standards.

The application should have the following functionalities:
- User input for basic refund details such as customer name, transaction ID, amount refunded, and reason for refund.
- Integration of the 'algovoi-refund-receipt' package to process these inputs into a formatted refund receipt.
- Generation of a unique pinning URN (Uniform Resource Name) for each receipt, ensuring it complies with the urn:x402:canonicalisation:jcs-rfc8785-v1 standard.
- Storage of the generated receipts in a database for future reference.
- A simple user interface or command-line interface for users to interact with the application.
- Optional feature: email notification to the customer upon generating a refund receipt.

In your development process, focus on utilizing the 'algovoi-refund-receipt' package to handle the complex formatting and canonicalization processes, allowing you to concentrate on building an intuitive and user-friendly application.

💬 Discussion Feed

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