AI Analysis
The package has low individual risk factors but shows unusual metadata patterns suggesting recent and rapid development, which could indicate potential malicious intent or supply-chain compromise.
- Recent and rapid commit history
- Low network, shell, obfuscation, and credential risks
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository was created recently and all commits happened within a short period, indicating potential low effort or suspicious activity.
Package Quality Overall: Low (2.2/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (1382 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Single-author or unverifiable project
1 unique contributor(s) across 14 commits in Xuanwo/asfmlSingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: Repository created very recently: 5 day(s) ago (2026-06-02T07:23:34Z)
Repository created very recently: 5 day(s) ago (2026-06-02T07:23:34Z)All 14 commits happened within 24 hours
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a command-line interface (CLI) tool named 'PonyMail Explorer' using the Python package 'asfml'. This tool should enable users to easily navigate through and extract information from Apache Pony Mail archives. Here are the steps and features you should include: 1. **Setup**: Begin by installing the necessary dependencies, including the 'asfml' package. 2. **Directory Navigation**: Implement functionality to allow users to browse through different directories within an Apache Pony Mail archive. 3. **Message Retrieval**: Enable users to retrieve specific messages based on search criteria such as sender, recipient, date, or subject. 4. **Content Extraction**: Provide options to extract plain text content, attachments, or HTML content from selected messages. 5. **Search Functionality**: Include a powerful search engine that allows users to find keywords across all messages in the archive efficiently. 6. **Export Options**: Offer export capabilities to save retrieved messages or extracted content in various formats like .txt, .html, or .pdf. 7. **User Interface**: Design a user-friendly CLI interface with clear prompts and instructions. 8. **Error Handling**: Ensure robust error handling to manage common issues such as invalid input or missing files gracefully. 9. **Documentation**: Write comprehensive documentation explaining how to install, use, and extend the tool. The 'asfml' package will primarily be used for parsing and manipulating the structure of Apache Pony Mail archives, facilitating efficient access to individual emails and their components. Your task is to design and implement a fully functional CLI tool that meets these requirements.
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