AI Analysis
Final verdict: SUSPICIOUS
The package exhibits a moderate risk level primarily due to its metadata, which suggests it may be newly created with little maintainer activity and no linked repository, raising concerns about its legitimacy.
- Metadata risk is high due to limited maintainer activity and no linked repository.
- Low risks in network, shell, obfuscation, and credential aspects.
Per-check LLM notes
- Network: The network calls suggest the package is interacting with an API, which is common for packages like 'arxivis' that might fetch data from arXiv.org or similar services.
- Shell: No shell execution patterns were detected, indicating low risk for direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of being newly created with limited maintainer activity and no linked repository, raising suspicion.
Package Quality Overall: Low (3.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (3475 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
59 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
pi/v1" self._client = httpx.Client( headers={"X-API-Key": api_key}, timpi/v1" self._client = httpx.AsyncClient( headers={"X-API-Key": api_key}, tim
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: v019labs.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 3.0
Repository not found (deleted or private)
Repository not found (deleted or private)
Maintainer History
score 6.0
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" 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 arxivis
Create a Python-based academic paper management tool using the 'arxivis' package. This tool should allow users to search for academic papers from various fields on the Arxiv server, save them locally, and manage a personal library of papers. Here’s a step-by-step guide on what your tool should include: 1. **Setup and Installation**: Start by setting up a virtual environment and installing necessary packages including 'arxivis'. Ensure all dependencies are listed in a requirements.txt file. 2. **User Interface**: Develop a simple command-line interface (CLI) where users can interact with the tool. Provide commands for searching papers, adding papers to a local database, listing saved papers, and removing papers. 3. **Searching Papers**: Implement a feature that allows users to search for papers by keyword, author, title, and date range. Use the 'arxivis' package to query the Arxiv API and retrieve relevant results. 4. **Saving Papers**: Once a user finds a paper they want to save, provide an option to download it locally and add it to their personal library. Store metadata like title, authors, abstract, and download link in a SQLite database. 5. **Managing Personal Library**: Allow users to view their saved papers, update metadata, and delete entries. Enhance usability by sorting and filtering options based on different criteria such as author name, publication date, etc. 6. **Notifications and Alerts**: Integrate a feature that sends email notifications when new papers matching certain criteria (e.g., specific keywords, authors) are added to Arxiv. 7. **Documentation and Testing**: Write comprehensive documentation for your tool and ensure you have unit tests covering major functionalities. Utilize the 'arxivis' package throughout your application for interacting with the Arxiv API, ensuring efficient and reliable data retrieval. Your goal is to create a robust, user-friendly tool that simplifies academic research and paper management.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue