🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no detected obfuscation, shell execution, or credential harvesting. The moderate metadata risk suggests caution, but does not outweigh the otherwise benign indicators.

moderate network risk due to external API calls
sparse author metadata

Per-check LLM notes

Network: The package makes network calls which may indicate legitimate functionality but could also suggest potential data exfiltration or C2 activity.
Shell: No shell execution patterns detected, suggesting low risk of 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 secret theft.
Metadata: The author's information is sparse, suggesting a potentially new or less active maintainer.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

6 test file(s) detected (e.g. test_client.py)

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://www.sunholo.com/ailang-parse/api.html
Detailed PyPI description (12193 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

58 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 100 commits in sunholo-data/ailang-parse
Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

sg).encode("utf-8") req = urllib.request.Request(endpoint, data=body, headers=headers, method="POST")
POST") try: with urllib.request.urlopen(req) as resp: _handle_response(resp)
icy() self._session = requests.Session() # Resolve API key: explicit > env var > saved cre
): self._session = requests.Session() # Resolve key: explicit > env var > saved credenti

✓ 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: sunholo.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository sunholo-data/ailang-parse 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 ailang-parse

Create a document parsing mini-app using the 'ailang-parse' Python package. This app will allow users to upload various types of documents (e.g., PDFs, Word docs, etc.) and parse them into structured data. The goal is to extract key information such as headings, paragraphs, tables, and metadata from these documents. Here are the steps and features you need to implement:

1. **Setup**: Install the 'ailang-parse' package and set up a basic Flask web application.
2. **User Interface**: Develop a simple UI where users can select and upload their documents.
3. **Document Parsing**: Use 'ailang-parse' to convert uploaded documents into a format that can be parsed effectively.
4. **Data Extraction**: Implement functionality within your app to extract key elements like headings, paragraphs, and tables from the uploaded documents.
5. **Metadata Handling**: Ensure that metadata (author, date, title) from the documents is also extracted and displayed.
6. **Output Display**: Provide a clean display of the extracted data on the same web interface.
7. **Error Handling**: Add error handling to manage cases where document parsing fails or the document type is not supported.
8. **Security Measures**: Implement basic security measures to protect user data and ensure safe file uploads.

This project aims to demonstrate the power of 'ailang-parse' in making document parsing accessible and easy to integrate into web applications.